Engineering Commons^™

Scalar Source Localization Using Multi-Sensor Domains Of Dependence In Turbulent Channel Fow, Zejian You, Xiaowei Zhu, Qi Wang

Mechanical and Materials Engineering Faculty Publications and Presentations

Tracking hazardous events such as wildfire smoke, coastal oil spills, or chemical releases in natural environments is complicated by turbulent dispersion and molecular diffusion. This study presents a method to localize pollutant sources rapidly and accurately using infinite time-averaged measurements from a multi-sensor network, leveraging the duality between mean forward and adjoint scalar fields. The forward-adjoint duality states that measurements at the sensor (forward feld) are equal to the adjoint field at the source, providing crucial spatial information about the source. Consequently, the adjoint scalar fields can be interpreted as the domain of dependence for the sensor observations [1, 2]. …

Analysis Of Pull-Out Tests For Resin-Grouted Rib Bolts, Khaled Mohamed, Yuting Xue, Dogukan Guner, Alper Kirmaci, Taghi Sherizadeh

Mining Engineering Faculty Research & Creative Works

Resin-grouted rib bolts serve as a crucial means of stabilizing spalling of coal ribs in underground coal mines. A comprehensive investigation into their efficacy was undertaken by a collaborative effort between the National Institute for Occupational Safety and Health (NIOSH) and Missouri University of Science and Technology (MST). This study involved pull-out tests of rib bolts in multiple locations, including six coal mines and the NIOSH research mine. A total of seventy-three (73) pull-out tests were conducted for rib bolts installed at different rotation speeds and a wide range of anchorage lengths, ranging from a short encapsulation length of 0.305 …

Recycling Waste Polyethylene Terephthalate For Asphalt Modification: A Comprehensive Review On Material Properties, Processing Techniques, And Engineering Applications, Ruizhe Huang, Feng Ma, Ke Shi, Zhen Fu, Jenny Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Polyethylene terephthalate (PET) is a thermoplastic polyester widely used in beverage bottles and packaging materials, accounting for approximately 60% of global plastic production. Due to its non-biodegradable nature, the accumulation of waste PET has posed a serious environmental challenge worldwide. In recent years, the recycling of PET for use in road engineering has been considered an effective approach to promote resource circulation and reduce plastic pollution. This paper first reviews the main recycling methods of PET, including mechanical shredding and chemical depolymerization, and analyzes its molecular structure, thermal properties, and reprocessing adaptability. Two typical engineering application paths are then evaluated: …

Femtosecond-Laser-Inscribed Cladding Fiber Bragg Gratings: Architectures, Design Trade-Offs And Future Sensing Opportunities, Koustav Dey, Rex E. Gerald, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Femtosecond (fs) laser inscription enables fiber Bragg gratings (FBGs) to be positioned beyond the fiber core, including within the cladding, thereby expanding control over modal interactions and directional sensing. These cladding fiber Bragg gratings (CLFBGs) extend FBG functionality through interactions with core, cladding, and evanescent fields. Their operation does not involve fundamentally different grating physics; rather, core-mode, cladding-mode, and coupled-mode responses depend on power distribution, modal overlap with the laser-inscribed refractive-index modulation (RIM), grating position, fiber geometry, modal excitation, and interrogation configuration. This Perspective reviews advances in CLFBG fabrication, optical characteristics, sensing mechanisms, and applications. Cladding-waveguide-assisted, evanescent-field-coupled, and direct cladding-mode-excitation …

Evaluating The Use Of Machine Learning For Road Maintenance Cost Estimation, Shahla Shirinzad, David Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Accurate estimation of highway maintenance costs is essential for efficient resource allocation and long-term infrastructure sustainability. This study evaluates the effectiveness of advanced machine learning models, including ResNet, Transformer, and other neural network architectures, for forecasting maintenance costs using historical data from the Highway Maintenance Improvement Program (HMIP) provided by the North Carolina Department of Transportation (NC DOT). A comprehensive comparative analysis is conducted across multiple models using standard performance metrics, including R², MAE, RMSE, and MSE. The results demonstrate that advanced architectures, particularly ResNet and Transformer, consistently outperform traditional statistical approaches and baseline machine learning models, achieving …

Sustmine: A Framework For Integrating Sustainable Development Dimensions Into Strategic Mine Planning, Hussam Altalhi, Kwame Awuah-Offei, Gabriel Nicolosi, Abdullah Al Moinee, Nasib Al Habib

Mining Engineering Faculty Research & Creative Works

Strategic mine planning involves optimizing resource extraction to achieve economic, environmental, and social objectives. However, only a few frameworks offer a unified approach that simultaneously employs systematic indicator selection and weightless trade-off evaluation. This study addresses these issues by proposing a comprehensive framework for integrating sustainability into strategic mine planning, named SustMine. SustMine introduces two key advancements: (1) a rigorous, systematic, criteria-based process for selecting site-specific sustainable development indicators (SDIs), and (2) a weightless evaluation strategy that utilizes Pareto front analysis to construct composite indices. This allows decision-makers to identify non-dominated (optimally balanced) alternatives without relying on arbitrary or subjective …

N-Radii Approach For Multi-Scale Characterization Of Graphite Shape In Cast Iron, Simon N. Lekakh, Laura Bartlett

Materials Science and Engineering Faculty Research & Creative Works

Knowledge of multi-scale particle macro-shape and micro-surface topology is critical in many technical disciplines. Specifically, quality assessment of the shape of the graphite phase in cast irons is essential for day-to-day metal casting operations. Common methods for evaluating particle macro-shape have several drawbacks, often resulting in underestimation of sharp corners and surface texture. In this article, a method based on plotting n-radii from the center of mass to the perimeter and computing multi-scale topological characteristics is described and tested. Parametric tests, involving variations in the number of n-radii and image resolution, were performed to optimize the test parameters. The method …

Modeling Of Transformation Temperatures In Cast Martensitic Stainless Steels-Ca6nm: Effects Of Composition, Heating Rate, And Grain Size, Ugochukwu Agbedo, Mario Buchely, Laura Bartlett, Caelan Kennedy

Materials Science and Engineering Faculty Research & Creative Works

Accurate prediction of the critical transformation temperatures Ac1 and Ac3 is one of the essential factors in the heat treatment of CA6NM cast martensitic stainless steel. In this study, the influence of alloy composition, heating rate, and prior austenite grain size on the critical temperatures was quantified using dilatometric measurements and statistical modeling. Six heat treatment conditions produced prior austenite grain sizes ranging from ~75 to 247 µm. Experimental results showed that grain size variations produced only minor changes in Ac1 and Ac3, indicating a weak dependence of transformation temperatures on prior austenite grain size within the investigated range. In …

Corrigendum To “3d Semi-Analytical Thermo-Elasto-Plastic Model For Additive Manufacturing”(Additive Manufacturing, (2026), 127, C, (105308), (S2214860426002344), 10.1016/J.Addma.2026.105308), Tao Liu, Ming C. Leu, Edward C. Kinzel, Chinedum Okwudire

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The author regret about the correction in the Equation B(1) in original article. The corrected version of the Equation B(1) is given below,(1.1)∂uxxx,ξ∂x=116πμ1−ν4ν−1x−ξxR3−3x−ξx3R5−8ν−5x−ξxR13+34ν−3x−ξx3R15−18x−ξxzξzR15+30x−ξx3zξzR17−12ν−12ν−1x−ξxR1R1+z+ξz2+4ν−12ν−1x−ξx3R13R1+z+ξz2+8ν−12ν−1x−ξx3R12R1+z+ξz3 The authors would like to apologise for any inconvenience caused. DOI of original article: < 10.1016/j.addma.2026.105308>

Multiphysics Simulation And Experimental Validation Of Phase Transformation And Hardness In Jominy End-Quenched Low-Alloy Steels, J. S. Alabi, E. Heidari, M. F. Buchely, K. Chandrashekhara, S. N. Lekakh, R. J. O'Malley, V. A. Athavale, A. Kumar

Materials Science and Engineering Faculty Research & Creative Works

High-volume industrial continuous hot-rolled steel heat treatment processes involve sophisticated multi-phase modeling. The performance of a given process can be optimized by coupling phase transformation kinetics with the cooling conditions of the process. This study develops a multiphysics model to simulate an intensive quenching process for steel, which is inherently transient and highly dependent on numerous parameters. The simulated object was a Jominy end-quenched specimen geometry using two commercial steels, AISI 4130 and AISI 4140, with the goal of transferring a verified methodology to the heat treatment process for industrial heavy-section products (bars, slabs). The simulation employs thermal, mechanical, and …

Effect Of Graphene Oxide On The Upconversion Photoluminescence Behavior Of Er/Yb Co-Doped Pvdf-Go Composite Nanofibers, Saptasree Bose, Jack Ryan Summers, Bhupendra B. Srivastava, Karen Lozano, Victoria Padilla-Gainza

Mechanical Engineering Faculty Publications

Upconversion photoluminescence (UCPL) materials, particularly rare-earth (RE) doped nanoparticles, have garnered significant attention due to their ability to convert near-infrared (NIR) excitation into visible emission, offering benefits such as high photostability, long lifetimes, low autofluorescence, and deep tissue penetration. Among various platforms, polymer-based one-dimensional (1D) nanofibers with in-situ lanthanide doping remain relatively unexplored, despite their superior mechanical flexibility, processability, and potential for improved luminescence performance. In this study, we report the fabrication and UCPL quenching behavior of Er3+/Yb3+ co-doped polyvinylidene difluoride (PVDF) nanofibers incorporated with graphene oxide (GO), synthesized for the first time using the scalable Forcespinning® technique. PVDF, a …

Wideband Acoustic Immittance: Suitable Quantities For Assessing Middle-Ear Status, Kren Monrad Nørgaard, Jingxin Jessica Feng, Susan E. Voss

Engineering: Faculty Publications

This paper investigates the physical significance of ear-canal wave quantities—such as absorbance—that are commonly measured in wideband-acoustic-immittance tests and evaluates whether these quantities uniquely characterize middle-ear function. This is explored using simulations of lumped-element and transmission-line ear canals, along with measurements in three-dimensional-printed uniform and anatomical ear canals of varying geometry, terminated by the same middle-ear simulator. The results demonstrate the following points: (1) Wave quantities computed using estimated or geometrical cross-sectional areas do not uniquely characterize the middle ear because they describe the wave interaction between ear canal and middle ear and are therefore confounded by variations in ear-canal …

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 …

Pafex: Compiler-Based Floating-Point Exception Detection For Gpu Kernels With Papispecific Software-Defined Events, Samin Islam, Shirley V. Moore, Christoph Q. Lauter

Graduate Student Papers (CS)

As high-performance computing becomes progressively heterogeneous, the dependence upon vendor specific tools for numerical correctness has become an impediment to portability. Although modern GPUs comply with the IEEE 754 standard, the lack of practical native hardware support to raise and handle exceptions (special values like ±∞ or NaN) is a well-known architectural limitation. To embed portable numerical correctness across heterogeneous systems, we propose an architecture agnostic prototype based on LLVM-compiler infrastructure. This framework detects floating-point exceptions in GPU kernels at the Intermediate Representation (IR) level, instrumenting both device code and host code, strictly complying with the 2019 IEEE 754 standard. …

Toward Neurosymbolic Reinforcement Learning Via Editable Specifications, Vedant Khandelwal, Hong Yung Yip, Amit Sheth

Publications

Reinforcement learning systems are commonly adapted to new settings by retraining or fine-tuning policies. This default is costly, difficult to audit, and poorly aligned with structured requirement changes such as revised safety rules, new operational constraints, or updated user preferences. We argue for an alternative abstraction: adaptation via edits to an external, human-readable specification that the agent consults at execution time. We propose conditioning decision-making on an editable knowledge graph encoding (i) rules capturing action applicability and high-level effects, (ii) hard constraints defining feasibility, and (iii) soft preferences shaping tradeoffs among feasible behaviors. Requirement changes become graph edits, not policy …

Gaze Transition Entropy And Automation Trust In Multitasking Workspace, Yusuke Yamani, Austin Jackson, Tetsuya Sato, Feyishola Ashimi, Michael S. Politowicz, Eric T. Chancey, Makoto Itoh

Psychology Faculty Publications

Safe flight operation requires visual scanning across multiple displays in a cockpit, which collectively represent the state of the aircraft and supporting automation. Trust is a crucial factor that drives human-automation interaction, and recent work has suggested a relationship between an operator's visual attention and automation trust. One index that captures predictability of eye movements between different areas of interest is gaze transition entropy. The current work reanalyzed data from Sato et al., which examined eye movement patterns and trust in automation associated with the system monitoring task of the Multi-Attribute Task Battery. Results showed credible positive correlations between the …

Implications Of Quantum Computing For Enterprise Cybersecurity And Data Integrity, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Quantum computing represents a paradigm shift in computational capabilities that poses both unprecedented threats and opportunities for enterprise cybersecurity. This research examines the implications of quantum computing advancement on current cryptographic systems, data protection mechanisms, and organizational security frameworks. Through analysis of quantum computing developments from 2019-2024 and surveys of 280 cybersecurity professionals across various industries, this study identifies critical vulnerabilities in existing encryption standards and explores emerging quantum-resistant solutions. The findings reveal that approximately 78% of enterprises remain unprepared for quantum threats, with current RSA and ECC encryption systems facing potential compromise within the next 10-15 years. The research …

Nanofibrous Materials And Nanoparticles For Combating Antimicrobial Resistance: Synthesis, Integration, And Translational Perspectives, Rewati Raman Ujjwal, Ashish Dilip Sutar, Rahul Shukla, Gymama Slaughter

Center for Bioelectronics Publications

Antimicrobial resistance (AMR) is a major global health challenge driven by mechanisms such as biofilm formation, efflux pumps, and genetic mutations. Nanoparticulate and fibrous materials have emerged as promising strategies to overcome these limitations through multimodal antimicrobial action and controlled drug delivery. This review highlights recent advances in electrospun nanofibrous systems, including natural and synthetic polymer-based scaffolds, stimuli-responsive nanofibers, and functionalized patches. Nanoparticle-loaded nanofiber systems demonstrate enhanced performance, including bacterial eradication, sustained drug release, and significant biofilm disruption. Multifunctional systems combining antimicrobial, antioxidant, and immunomodulatory properties further show synergism. Emerging innovations, such as piezoelectric and smart sensing systems, enable self-powered …

Osmotic Dilators Vs. Foley Balloons: Bayesian Secondary Analyses Of The Dilafol Trial, Antonio F. Saad, Elenir B. C. Avritscher, Claudia Pedroza, Xiao Han, George R. Saade

Department of Obstetrics & Gynecology Faculty Publications

Background: Dilapan-S, a synthetic osmotic dilator used for pre-induction cervical ripening, has proven to be as effective as the Foley balloon in terms of vaginal versus cesarean delivery and has been associated with increased patient satisfaction. Nevertheless, its ability to lower cesarean rates and its cost-effectiveness remain poorly studied.

Objectives: To estimate the likelihood that synthetic osmotic dilators reduce cesarean deliveries and to evaluate their health system costs (2026 US$) and incremental cost-effectiveness compared to the Foley balloon during cervical ripening.

Study Design: Secondary Bayesian analyses were conducted using data from the single-center DILAFOL randomized controlled trial, which enrolled 419 …

Optimizing Maintenance Routes For Highway Infrastructure Using Leader-Follower Autonomous Vehicles, Qing Tang, Chenxi Chen, Xianbiao Hu, Yuxin Ding, Tianjia Yang

Civil & Environmental Engineering Faculty Publications

The Autonomous Truck Mounted Attenuator (ATMA), a leader–follower style connected and automated vehicle system, enhances safety during transportation infrastructure maintenance in work zones. However, the significantly lower speed of ATMA, compared to regular vehicles, causes moving bottlenecks that reduce roadway capacity and prolong queuing, leading to further delays. Different ATMA routes lead to varying patterns of time-dependent capacity drop, affecting the user equilibrium traffic assignment and resulting in differing system costs. This study aims to optimize ATMA routing within a network to minimize the system cost associated with its slow-moving operation. To this end, a queuing-based traffic assignment approach is …

Biomechanical Advancements In Hydroxyapatite, Magnesium-Substituted Hydroxyapatite, And Strontium-Substituted Hydroxyapatite In Clinical And Non-Clinical Studies For Maxillofacial Bone Tissue Engineering: A Review, Elham Zafarrazzaghnia, Stuart Hampshire, Aran Rafferty, Dermot Brabazon, Eamonn Debarra, Maura Kelleher

Articles

Hydroxyapatite (HA) is a bioceramic known for its bioactivity and osteoconductivity, which should make it an ideal candidate for maxillofacial bone regeneration. However, its brittleness limits its suitability for load-bearing applications. Over recent decades, substantial efforts have focused on enhancing its performance, particularly through ionic substitution, including magnesium-substituted HA (Mg-HA) and strontium-substituted HA (Sr-HA). This review summarises the available information on the structural, physical and mechanical properties of facial bones (maxilla, mandible, zygoma and frontal bone). The crystal structure, physical, and mechanical properties and in-vitro biological responses of dense and porous HA, Mg-HA and Sr-HA ceramics are described, with particular …

Harnessing Activated Sludge For The Treatment Of Hydrothermal Liquefaction Wastewater: A Proof-Of-Concept Study, Cyrus Li, Jiefu Wang, Meicen Liu, Yi Zheng, Sandeep Kumar, Isamu Umeda, Chandan Mahata, John Norton

Civil & Environmental Engineering Faculty Publications

Although hydrothermal liquefaction (HTL) is the leading technology in converting wet biomass into bioenergy, the treatment of its toxic-laden aqueous phase wastewater presents a major challenge on its path toward commercial viability. This study presents the first-ever assessment of sewage sludge-fed HTL wastewater (SS-HTLWW) treatment and toxic compound removal using municipal activated sludge (AS) by optimizing its cultivation condition. It was found that AS with optimized pretreatment can remove up to 91.2% of the soluble chemical oxygen demand (sCOD) in SS-HTLWW, of which up to 82% can be attributed to biological mineralization and adsorption of sCOD by AS. Conventional bioprocess …

When Slides Replace Thinking: How Powerpoint Culture Undermines Conceptual Learning In Engineering Education, Shahin Nayyeri Amiri, Hamid Eisazadeh

Civil & Environmental Engineering Faculty Publications

Engineering education has gradually shifted from deep conceptual teaching to a culture dominated by presentation slides. In many universities today, core courses such as Statics, Dynamics, and Mechanics of Materials are taught through PowerPoint files rather than through reasoning, derivation, and problem solving. While slide-based instruction may appear efficient, it encourages passive learning and has severely weakened students’ ability to think independently and make sound engineering judgments. Traditionally, these fundamental courses were taught by seasoned instructors who had mastered the subjects and took genuine pride in explaining complex ideas with clarity and passion. They guided students through the logic behind …

Circulating Biomarker Results From A Phase 2 Study Of Seralutinib In Pulmonary Arterial Hypertension, Robin Osterhout, Athénaïs Boucly, Raymond L. Benza, Richard N. Channick, Kelly M. Chin, Robert P. Frantz, Anna R. Hemnes, Luke S. Howard, Vallerie V. Mclaughlin, Olivier Sitbon, Jean-Luc Vachiéry, Rotham T. Zamanian, Richard Aranda, Matt Cravets, Zhaoqing Ding, Thao Duong-Verlé, David Mattola, Robert F. Roscigno, Ravikumar Sitapara, Lawrence S. Zisman, Jean-Marie Bruey, Hossein-Ardeschir Ghofrani

Department of Medicine Faculty Publications

[Introduction] To the Editor: Pulmonary arterial hypertension (PAH) is a progressive disease characterized by obstructive pulmonary arterial remodeling (1). Seralutinib, an investigational inhaled tyrosine kinase inhibitor, potently and selectively targets kinases relevant to PAH pathobiology including platelet-derived growth factor receptors (PDGFR) α and β, colony stimulating factor 1 receptor (CSF1R), and mast/stem cell growth factor receptor kit (c-KIT) (2). In preclinical models, seralutinib improved cardiopulmonary hemodynamics, reversed pulmonary vascular pathology and decreased right ventricular hypertrophy (3). In TORREY, a phase 2, multicenter, double-blind, randomized, placebo-controlled trial in PAH, seralutinib significantly reduced pulmonary vascular resistance (PVR) after 24 weeks with good …

Micro- And Nanoplastics: A Paradigm Shift In The Pathogenesis Of Inflammatory Bowel Disease, Michael Saadeh, Priyata Dutta, Gordon Hong, Edward Oldfield, David A. Johnson

Department of Medicine Faculty Publications

Micro- and nanoplastics (MNPs) are pervasive environmental contaminants with growing recognition as potential contributors to human disease. Widespread human exposure occurs primarily through ingestion of contaminated food and water, and MNPs have been detected in multiple human tissues, including the gastrointestinal tract. Experimental evidence provides a plausible biological basis for disease associations, including impairment of intestinal barrier integrity, activation of mucosal immune pathways, and alteration of gut microbial communities caused by MNP exposure. Although human data remain limited, early studies demonstrate MNP detection in stool and suggest potential correlations with inflammatory biomarkers such as fecal calprotectin. These findings, together with …

A Comprehensive Survey Of Prompt Engineering Techniques In Large Language Models, Tonmoy Debnath, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Prosenjit Das, Antu Kumar Guha, Muhammad Rezaur Rahman, H. M. Dipu Kabir

Electrical & Computer Engineering Faculty Publications

Prompt engineering has arisen as a pivotal discipline in optimizing the performance of Large Language Models (LLMs) by structuring inputs to enhance coherence, accuracy, and task alignment. This paper comprehensively surveys various prompting techniques, systematically categorizing them according to their application domains and methodological foundations. Fundamental approaches like zero-shot and few-shot prompting are examined along with advanced strategies, including chain-of-thought reasoning, retrieval-augmented generation, and self-consistency mechanisms. A rigorous qualitative analysis is conducted to evaluate each technique's strengths, limitations, and optimal use cases, offering a structured framework for selecting the most effective prompting strategies. Theoretical insights and empirical findings are consolidated …

Physics-Informed Temperature Prediction Of Lithium-Ion Batteries Using Decomposition-Enhanced Lstm And Bilstm Models, Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, François Allard

Electrical & Computer Engineering Faculty Publications

Accurately forecasting the operating temperature of lithium-ion batteries (LIBs) is essential for preventing thermal runaway, extending service life, and ensuring the safe operation of electric vehicles and stationary energy-storage systems. This work introduces a unified, physics-informed, and data-driven temperature-prediction framework that integrates mathematically governed preprocessing, electrothermal decomposition, and sequential deep learning architectures. The methodology systematically applies the governing relations to convert raw temperature measurements into trend, seasonal, and residual components, thereby isolating long-term thermal accumulation, reversible entropy-driven oscillations, and irreversible resistive heating. These physically interpretable signatures serve as structured inputs to machine learning and deep learning models trained on temporally …

Machine Learning-Based Lifetime Prediction Of Lithium Batteries: A Comparative Assessment For Electric Vehicle Applications, Abdelilah Hammou, Raffaele Petrone, Demba Diallo, Boubekeur Tala-Ighil, Philippe Makany Boussiengue, Hicham Chaoui, Hamid Gualous

Electrical & Computer Engineering Faculty Publications

This paper evaluates and compares four data-driven methods (Gaussian Process Regression (GPR), echo state network (ESN), gated recurrent unit (GRU), and long short-term memory (LSTM)) for lithium-ion capacity prognostics adapted to electric vehicle conditions. This comparison aims to find the most efficient prognosis method considering two constraints: the limitation of computational power and the unavailability of on-board capacity measurement that requires full charge and discharge conditions. The machine learning models are trained using capacity values estimated under vehicle conditions. The ageing data is collected from cycling tests of two battery chemistries, Lithium Fer Phosphate (LFP) and Nickel Manganese Cobalt (NMC), …

Recent Insight And Perspective Of Marine-Inspired Biopolymers For Wound Healing Applications - A Review, Muhammad Umar Aslam Khan, Saiqa Yousaf, Abdalla Abdal-Hay, Mohd Faizal Bin Abdullah, Sahar Madani, Muhammad Shahzad Zafar, Goran M. Stojanović, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

There is an increasing necessity for advanced, sustainable, and biocompatible materials for wound healing as therapeutic and diagnostic products. Marine environments, characterized by high biodiversity, offer an underutilized source of natural resources with enormous potential for creating novel materials for dressings. This review highlights the revolutionary nature of polymeric biomaterials of marine origin, with a focus on polysaccharides, like alginate, chitosan, and carrageenan; proteins, such as collagen and gelatin. These biopolymers are outstanding in their physicochemical properties, such as biodegradability, bioactivity, and modifiable mechanical strength, which enable their use in wound-healing systems. Besides, these biomaterials may be easily chemically and …

Pin-Plane Electrical Discharge Driven By A Mosfet Dc Current Source, Myles Perry, Sidmar Holoman, Daniel Wozniak, Shirshak Kumar Dhali

Electrical & Computer Engineering Faculty Publications

The generation of atmospheric pressure nonequilibrium plasma using electrical discharges is an active area of research due to its significance in a wide spectrum of applications including medicine, combustion, and manufacturing. In our attempt to create a helium plasma jet in a pin-plane discharge with a constant current source, we observed self-pulsating behavior. We present the results of the electrical, optical, and spectroscopic measurements carried out to characterize the discharge. The duration of the discharge is a few tens of nanoseconds, and the repetition rate is in the few tens of kHz. The effect of the gap distance and gas …