Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

Discipline
Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 3391 - 3420 of 195898

Full-Text Articles in Engineering

Scenarioxp: A Complete Scenario–Based Testing Framework For The Exploration And Exploitation Of Autonomous Vehicle Validation Scenarios, Quentin Goss Mar 2026

Scenarioxp: A Complete Scenario–Based Testing Framework For The Exploration And Exploitation Of Autonomous Vehicle Validation Scenarios, Quentin Goss

Student Research Symposium (SRS)

Today is an age of exiting emerging technology where cutting-edge research in autonomous vehicles (AVs) reduces the active human participation in driving and extends awareness beyond human limitations of perception and reaction, improving driving safety and quality of the user experience as a result. The ever-increasing complexity of these autonomous systems poses many challenges towards the validation and verification (V\&V) of these complex systems under time and resource constraints, as the use of artificial intelligence and also the intricacy of the operating environment means that these systems are also black-box and non-deterministic. Scenario-based V\&V testing of such systems, which involves …

Go to article

A Data-Driven Framework For Modeling Car-Following Behavior Using Conditional Transfer Entropy And Dynamic Mode Decomposition, Poorendra Ramlall Mar 2026

A Data-Driven Framework For Modeling Car-Following Behavior Using Conditional Transfer Entropy And Dynamic Mode Decomposition, Poorendra Ramlall

Student Research Symposium (SRS)

Accurate modeling of car-following behavior is essential for understanding traffic dynamics and enabling predictive control in intelligent transportation systems. This study presents a novel data-driven framework that combines information-theoretic input selection via conditional transfer entropy (CTE) with dynamic mode decomposition with control (DMDc) for identifying and forecasting car-following dynamics. In the first step, CTE is employed to identify the specific vehicles that exert directional influence on a given subject vehicle, thereby systematically determining the relevant control inputs for modeling its behavior. In the second step, DMDc is applied to estimate and predict the dynamics by reconstructing the closed-form expression of …

Go to article

Best Practices For Electrical Safety At Home, Joshua Henderson, Derek Centrone Mar 2026

Best Practices For Electrical Safety At Home, Joshua Henderson, Derek Centrone

Student Research Symposium (SRS)

The household, although it’s a comfortable and relaxing environment, can in fact be riddled with everyday hazards that homeowners and residents overlook or are too complacent in acknowledging or even recognizing their presence. One such common oversight is electrical hazards. This may be due to the high usage of electricity in people’s day-to-day lives, especially since the perceived risk of electrical hazards by the public can be very low. In a household, there are many hazards present each and every day. One such hidden deadly hazard is electricity. While on the surface it doesn’t seem that dangerous, in reality, it …

Go to article

Artificial Intelligence In Aviation: Benefits, Concerns, And Regulations, Aarohi Srivastava Mar 2026

Artificial Intelligence In Aviation: Benefits, Concerns, And Regulations, Aarohi Srivastava

Student Research Symposium (SRS)

As artificial intelligence (AI) becomes increasingly integrated into aviation systems, understanding its implications for safety and regulation is critical. This research examines the current state of AI implementation in aviation, exploring both transformative benefits and significant concerns in this high-stakes environment. AI's strengths, including rapid large-scale data processing, predictive capabilities, and pattern recognition, offer substantial operational advantages. However, these benefits must be balanced against key concerns including liability issues, potential loss of pilot competency through over-reliance, the "black box" problem of AI explainability, emergent system behaviors, and training requirements.  This project analyzes current regulatory frameworks from major aviation authorities including …

Go to article

Enhancing Aviation Safety: A Framework For Predictive Maintenance Using Generative Data Augmentation And Uncertainty Quantification, Muhammad Najjar Mar 2026

Enhancing Aviation Safety: A Framework For Predictive Maintenance Using Generative Data Augmentation And Uncertainty Quantification, Muhammad Najjar

Student Research Symposium (SRS)

Predictive maintenance is a critical component of aviation safety, yet the development of accurate data-driven models is often hindered by the severe class imbalance inherent in real-world flight data; healthy flights are abundant, while flights preceding a failure are rare. This imbalance biases machine learning models, leading to poor detection of critical maintenance needs. This project addresses this challenge by leveraging the NGAFID aviation maintenance dataset to develop and validate an integrated predictive framework. We propose training a Time-series Generative Adversarial Network (TimeGAN) to synthesize high-fidelity, realistic "pre-maintenance" flight data. This synthetic data is used to create a balanced training …

Go to article

Ergonomics Of A Pilot Workstation And Aircraft Interactions On A Cessna 172 Nav Iii, Nicole Beaulieu Mar 2026

Ergonomics Of A Pilot Workstation And Aircraft Interactions On A Cessna 172 Nav Iii, Nicole Beaulieu

Student Research Symposium (SRS)

This study analyzes the ergonomic aspects of the Cessna 172 Navigator III, a common flight training aircraft. The research investigated the interactions between pilots and the aircraft, focusing on pilot fatigue, workstation design, anthropometric data, and pilot interactions with controls. The study included surveys, interviews, and anthropometric measurements involving three pilots with varying experience levels, alongside physical measurements of the cockpit and a workstation ergonomic assessment.. Participants reported issues with limited physical space, particularly impactful to the pilot’s posture and ability to manipulate controls. Display visibility and interaction were areas of concern, often requiring pilots to lean in awkward postures. …

Go to article

Building Services Engineering January/February 2026 Mar 2026

Building Services Engineering January/February 2026

Building Services Engineering

No abstract provided.

Go to article

Layer-Wise Printing Parameter Optimization For Laser Powder Bed Fusion, Chaoran Dou, Rongxuan Wang, Raghav Gnanasambandam, Jianzhi Li, Zhenyu James Kong Mar 2026

Layer-Wise Printing Parameter Optimization For Laser Powder Bed Fusion, Chaoran Dou, Rongxuan Wang, Raghav Gnanasambandam, Jianzhi Li, Zhenyu James Kong

Manufacturing & Industrial Engineering Faculty Publications

Additive manufacturing (AM) is a transformative technology that enables the fabrication of complex geometries layer by layer. However, metal parts produced via AM processes such as laser powder bed fusion (LPBF) are prone to various defects, including porosity and deformation. These defects often result from suboptimal printing parameter settings. Traditional approaches typically aim to reduce defects by optimizing a fixed set of parameters for the entire part. However, such methods do not account for layer-wise variations in printing conditions caused by changes in geometry, heat transfer, and re-heating effects. While optimizing parameters for each layer could improve part quality, it …

Go to article

Enhanced Antenna Selection Techniques For Energy-Efficient Code Index Modulation Aided Spatial Modulated Wireless Communication Systems, Fati̇h Çögen, Burak Ahmet Özden, Erdoğan Aydin Mar 2026

Enhanced Antenna Selection Techniques For Energy-Efficient Code Index Modulation Aided Spatial Modulated Wireless Communication Systems, Fati̇h Çögen, Burak Ahmet Özden, Erdoğan Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes an integrated multiple-input multiple-output (MIMO) transceiver framework, termed CIM-HQAM-SM, which combines code index modulation (CIM) and spatial modulation (SM) with energy-efficient hexagonal quadrature amplitude modulation (HQAM). In the proposed bit mapping, the information bits jointly select (i) the active transmit-antenna index, (ii) the Walsh–Hadamard spreading-code indices for the in-phase and quadrature branches, and (iii) an HQAM symbol. Hence, the payload is conveyed through the constellation symbol as well as through antenna and code indices. For the considered Rayleigh-fading scenarios and matched spectral-efficiency settings, the proposed framework offers BER improvements over conventional SM and quadrature SM (QSM), while …

Go to article

An Ensembled Two-Phase Deep Learning Approach For A Psychiatric Disorder Detection, Prajna Paramita Debata, Midhun Chakkaravarthy, Brojo Kishore Mishra Mar 2026

An Ensembled Two-Phase Deep Learning Approach For A Psychiatric Disorder Detection, Prajna Paramita Debata, Midhun Chakkaravarthy, Brojo Kishore Mishra

Turkish Journal of Electrical Engineering and Computer Sciences

Computational Psychiatry represents a burgeoning realm within scientific inquiry, delving into the intricate interplay of neurobiology within the brain. The escalating prevalence of mental illness underscores the urgency to confront this challenge. Among the prevalent disorders, Schizophrenia and Bipolar Disorder loom large, affecting a significant portion of the population at some point in their lives. However, pinpointing psychiatric disorders poses a formidable challenge. Genetic predispositions significantly influence the development of mental illnesses, with intriguing overlaps observed among certain disorders. This convergence complicates accurate diagnosis. Here, a deep learning approach is considered for significant gene biomarker identification and classification of Schizophrenia …

Go to article

Potential And Chloride Concentration As Thresholds For Crevice Corrosion Initiation In Ss 316l, Y Shorrab, R S. Lillard Mar 2026

Potential And Chloride Concentration As Thresholds For Crevice Corrosion Initiation In Ss 316l, Y Shorrab, R S. Lillard

University Research

This work investigated the relationship between crevice chloride concentration ([Cl−]) and the potential necessary for initiation in stainless steel 316L (SS 316L). Real-time fluorescence measurements were used to measure [Cl−] inside SS 316L crevice assemblies as a function of bulk [Cl−] and potential. Crevice initiation at potentials slightly less than or equal to the bulk repassivation potential was associated with chloride transport, owing to passive dissolution, and an increase in the crevice [Cl−]. Once the [Cl−] within the crevice increased to the concentration necessary to initiate SS 316L pitting at the applied potential, crevice corrosion was initiated. For example, in …

Go to article

Ionic Liquid Pilocarpine Serves As Therapeutic Cosolvent And Permeation Enhancer For Glaucoma Medication, Ashish Trital, Lei Xu, Burhan Ates, Tzu Chen Wang, Vimalin Mani, Hu Yang Mar 2026

Ionic Liquid Pilocarpine Serves As Therapeutic Cosolvent And Permeation Enhancer For Glaucoma Medication, Ashish Trital, Lei Xu, Burhan Ates, Tzu Chen Wang, Vimalin Mani, Hu Yang

Chemical and Biochemical Engineering Faculty Research & Creative Works

The efficacy of hydrophobic ocular drugs is significantly hindered by their low bioavailability, for which poor water solubility is a major contributing factor. In this work, we synthesized pilocarpine-derived ionic liquid [Pilo-OEG] Cl (PO) and evaluated its cosolvent properties for the codelivery of the hydrophobic antiglaucoma drug brimonidine (BM) for glaucoma therapy. Pilocarpine was quaternized with 2-[2-(2-chloroethoxy) ethoxy] ethanol in a one-pot reaction to yield PO, and its structure was confirmed using 1H NMR and FT-IR spectroscopy methods and further characterized for its rheological property and thermal stability. The HET-CAM assay and cell viability study showed that PO was …

Go to article

Cover And Contents Mar 2026

Cover And Contents

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

Go to article

Sentisec: Combining Keyword Heuristics And Sentiment Modeling For Ai-Powered Threat Detection, Ridho Surya Kusuma, Erum Ashraf, Selvakumar Manickam, Shankar Karuppayah Mar 2026

Sentisec: Combining Keyword Heuristics And Sentiment Modeling For Ai-Powered Threat Detection, Ridho Surya Kusuma, Erum Ashraf, Selvakumar Manickam, Shankar Karuppayah

Turkish Journal of Electrical Engineering and Computer Sciences

This work presents SENTISEC, a hybrid LLM-based threat detection framework designed to classify security logs by integrating keyword heuristics, domain-adapted sentiment scoring, and Retrieval-Augmented Generation (RAG). The system achieves an overall accuracy of 93.67%, with 91.46% macro recall, 89.07% macro F1, and 95.15% threat recall, while maintaining a low false-positive rate of 1.68%. Its methodology incorporates strict keyword and IOC matching, a domain-tuned DistilBERT sentiment module, hybrid BM25–MiniLM retrieval enhanced with BGE reranking, adaptive quantile-based threshold calibration, and SHAP-based explainability. Comparative evaluations against keyword-only, sentiment-only, classical machine-learning models, and DistilBERT-only baselines show that SENTISEC consistently improves both true-positive and true-negative …

Go to article

Sgsc-Kko-Lstm: A Deeplearning Classifier Model For Smart Grid, Dushmanta Kumar Das, Samaniba Imchen Mar 2026

Sgsc-Kko-Lstm: A Deeplearning Classifier Model For Smart Grid, Dushmanta Kumar Das, Samaniba Imchen

Turkish Journal of Electrical Engineering and Computer Sciences

Maintaining smart grid stability is crucial for the reliable operation of decentralized electricity networks, especially as the energy sector becomes more complex. The process of ensuring grid stability begins with collecting consumer data and comparing it to power supply requirements. Ultimately, consumers receive a report showing their energy use and pricing details. However, this process is time-consuming and can be improved by leveraging artificial intelligence to predict smart grid stability more efficiently. Specifically, an optimized Long Short-Term Memory (LSTM) network is proposed to predict smart grid stability, addressing the challenges associated with traditional data collection and evaluation methods. Simulations from …

Go to article

A Joint Optimization-Based Novel Attack For Genomic Beacon Reconstruction, Kousar Saleem, Si̇nem Sav Mar 2026

A Joint Optimization-Based Novel Attack For Genomic Beacon Reconstruction, Kousar Saleem, Si̇nem Sav

Turkish Journal of Electrical Engineering and Computer Sciences

Genomic data sharing has become an essential component of biomedical research, enabling large-scale collaborations and accelerating discoveries in human genetics. To balance the need for accessibility with privacy concerns, several controlled-access mechanisms have been proposed, including genomic beacons. Genomic beacons answer simple presence/absence queries about specific genetic variants. However, prior work has demonstrated that beacons remain vulnerable to genome reconstruction attacks, where an adversary can recover large portions of participants’ genomes using summary statistics. Building on insights from prior reconstruction attacks, we introduce an approach that unifies SNP correlation and allele frequency alignment objectives within a single-stage joint optimization framework. …

Go to article

Automated Software Size Measurement Using Multilingual Domain-Adapted Language Models, Samet Tenekeci̇, Hüseyi̇n Ünlü, Burak Keçeci̇, Muhammed Efe İnci̇r, Onur Demi̇rörs Mar 2026

Automated Software Size Measurement Using Multilingual Domain-Adapted Language Models, Samet Tenekeci̇, Hüseyi̇n Ünlü, Burak Keçeci̇, Muhammed Efe İnci̇r, Onur Demi̇rörs

Turkish Journal of Electrical Engineering and Computer Sciences

Software Size Measurement (SSM) is crucial for estimating required project effort as well as budget and schedule. However, many small and medium-sized companies struggle to apply objective SSM due to limited resources and lack of expertise. This often leads to inaccurate estimates and project overruns. There is a need for practical, low-resource solutions that support these tasks without requiring expert involvement. Motivated by this challenge, this study proposes an automated software size measurement approach that formulates the measurement task as supervised regression over natural language requirements, using domain-adapted transformer models. We construct large-scale Turkish and English software engineering corpora to …

Go to article

Reducing Complexity In Versatile Video Coding Intra-Coding Through Machine Learning-Based Optimization Of Partitioning And Prediction, Amina Kessentini, Amna Maraoui, Imen Werda, Fatma Ezahra Sayadi Mar 2026

Reducing Complexity In Versatile Video Coding Intra-Coding Through Machine Learning-Based Optimization Of Partitioning And Prediction, Amina Kessentini, Amna Maraoui, Imen Werda, Fatma Ezahra Sayadi

Turkish Journal of Electrical Engineering and Computer Sciences

The escalating demand for high-resolution multimedia content has necessitated more efficient video compression solutions. The Versatile Video Coding (VVC) standard, despite achieving remarkable compression gains, introduces significant computational complexity, primarily due to its exhaustive Rate-Distortion Optimization (RDO) process. To address this, we propose an intelligent approach leveraging supervised machine learning techniques to streamline the VVC encoding process. Specifically, we introduce a Lightweight Neural Network (LNN) for efficient coding unit partitioning decisions and a Decision Tree (DT) classifier for optimizing the intra prediction process. This dual-method framework, tailored for All Intra coding configuration, significantly reduces encoder complexity while maintaining compression performance …

Go to article

Designing Risk-Aware Mixed-Mode Evacuation Strategies For Tsunamis: Insights From İstanbul, Vedat Bayram, Doruk Ergez, Ada Arikanoğlu Mar 2026

Designing Risk-Aware Mixed-Mode Evacuation Strategies For Tsunamis: Insights From İstanbul, Vedat Bayram, Doruk Ergez, Ada Arikanoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

​Tsunamis pose severe and time-critical risks to densely populated coastal cities, where limited warning times and infrastructure constraints demand carefully coordinated evacuation strategies. This study develops an integrated, risk-aware optimization framework that jointly considers vertical and horizontal sheltering options together with mixed pedestrian-vehicular evacuation dynamics. The proposed mixed-integer second-order cone programming (MISOCP) model simultaneously determines vertical shelter location, evacuee assignment, road-use designation for pedestrians and vehicles, and route selection under congestion, capacity, and budget constraints. Vehicle travel times incorporate congestion effects through a convex flow-dependent function, while pedestrian routing ensures convergent and conflict free evacuation paths. A risk-minimization objective accounts …

Go to article

Optimal Network Reconfiguration Based On Discrete Metaheuristic Techniques For Reduction Of Power Loss And Carbon Emission In Distribution Networks, Asad Ali, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hussain Shareef, Hasmaini Mohamad, Munir Azam Muhammad Mar 2026

Optimal Network Reconfiguration Based On Discrete Metaheuristic Techniques For Reduction Of Power Loss And Carbon Emission In Distribution Networks, Asad Ali, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hussain Shareef, Hasmaini Mohamad, Munir Azam Muhammad

Turkish Journal of Electrical Engineering and Computer Sciences

Power distribution systems play a crucial role in transmitting electrical power from generation sources to end users. During transmission, significant power losses occur in the form of heat as the current flowing along the lines/cables has resistance. To minimize power losses, distribution network reconfiguration (DNR) has been widely adopted. This paper proposes optimal DNR based on metaheuristic techniques with discrete mutation feature targeting active power loss reduction, which subsequently lowers carbon emissions and operational costs. Through the discrete mutation feature, computational time to find optimal solution has been reduced significantly with fewer iterations compared to conventional mutation techniques. The proposed …

Go to article

Impact Of Glass Powder As A Sustainable Material On The Workability, Strength, And Durability Properties In High-Performance Basalt Fiber Reinforced Concrete: A Statistical Analysis, Ahmed Fathi Mohamed Salih Mar 2026

Impact Of Glass Powder As A Sustainable Material On The Workability, Strength, And Durability Properties In High-Performance Basalt Fiber Reinforced Concrete: A Statistical Analysis, Ahmed Fathi Mohamed Salih

Journal of Sustainable Construction Materials and Technologies

The global construction sector is increasingly challenged to balance environmental sustainability with the growing demand for durable, high-performance materials. As cement production continues to be a major source of anthropogenic CO2 emissions, the incorporation of alternative, low-impact binders has become a key strategy for reducing the environmental footprint of concrete. In this context, glass powder (GP)—a finely ground industrial by-product rich in amorphous silica—has emerged as a promising partial replacement for Portland cement. Its pozzolanic reactivity contributes to improved hydration and matrix densification, while its use also supports circular economy principles by diverting waste glass from landfills. At the same …

Go to article

Developing And Delphi-Validating A Phase-Based Sustainable Bsc Framework For Contractors' Sustainable Productivity Management In Developing Countries, Truong Van Luu, Le Minh Long Nguyen Mar 2026

Developing And Delphi-Validating A Phase-Based Sustainable Bsc Framework For Contractors' Sustainable Productivity Management In Developing Countries, Truong Van Luu, Le Minh Long Nguyen

HBRC Journal

This study develops and validates, using the Delphi method, a conceptual decision-support framework for construction contractors' sustainable productivity management (CSPM) in developing-country settings. Guided by KAMET rules, semi-structured interviews were conducted with 15 experts to elicit, refine, and reach consensus on a set of productivity management attributes that construction contractors can realistically apply. The outcome is 29 feasible productivity management attributes, organized under the four Sustainable Balanced Scorecard (SBSC) perspectives and mapped onto five management phases (planning, organizing, staffing, leading/coordination, and controlling). Rather than predicting or demonstrating productivity gains, the framework provides a practical roadmap for diagnosing capability gaps, prioritizing …

Go to article

Heuristic Particle Swarm Optimization Method For The Stability Analysis Of Geosynthetics-Reinforced Slopes, Hoda Mostafa, Ibrahim Mashhour Mar 2026

Heuristic Particle Swarm Optimization Method For The Stability Analysis Of Geosynthetics-Reinforced Slopes, Hoda Mostafa, Ibrahim Mashhour

HBRC Journal

Slope stability is considered one of the crucial topics in geotechnical engineering. Accurate soil slopes stability analyses are essential as slope failures could cause catastrophic environmental and human disasters. Geosynthetics are widely used as stabilizing elements in slope stability analyses. Incorporating geosynthetic reinforcement generally improves the global factor of safety against slope failure. However, in practice, analyses must not only focus on the global slope stability but should also account for any sliding along geosynthetic interfaces, since geosynthetics are considered as week layers within the reinforced soil mass and act as potential slip interfaces that should be checked for stability. …

Go to article

Symmetry And Scale: The Precise Engineering Of Chitosan-Based Polyhedral For The Delivery Of Therapeutic Materials At The Nanoscale, Ahmed. J. Jasim, Noor Malik Saadoon Mar 2026

Symmetry And Scale: The Precise Engineering Of Chitosan-Based Polyhedral For The Delivery Of Therapeutic Materials At The Nanoscale, Ahmed. J. Jasim, Noor Malik Saadoon

AUIQ Technical Engineering Science

Preparation of chitosan-based drug delivery carriers requires converting linear polysaccharide chains into individual 3D objects. By building on the natural structural properties of chitin-based polymers, in addition to control the geometry of organically derived raw material from feedstock to submicron polyhedral or spherical dimensions. This geometric change is governed by a surface area-to-volume ratio that maximizes the exposure of the therapeutic payload to the external environment. The approach centres on the development of such carriers using ion-complexation and emulsification methodologies, which involve electrostatic cross-linking of ion-binding pairs to define an impenetrable boundary separating a liquid from a solid phase. Critical …

Go to article

Roadmap: Integrating Artificial Intelligence In Structural Health Monitoring Systems, Simon Laflamme, Erik Blasch, Flippo Ubertini, Zheng Liu, John Wertz, Christine Knott, Matthew Cherry, Eric Lindgren, Fu-Kuo Chang, Amrita Kumar, Jack Poole, Keith Worden, Austin Downey, Jie Wei, Patrick F. Musgrave, Adrian S. Wong, Guiseppe Quaranta, Marco Martino Rosso, Giuseppe Carlo Marano, Yu Chen, Et. Al. Mar 2026

Roadmap: Integrating Artificial Intelligence In Structural Health Monitoring Systems, Simon Laflamme, Erik Blasch, Flippo Ubertini, Zheng Liu, John Wertz, Christine Knott, Matthew Cherry, Eric Lindgren, Fu-Kuo Chang, Amrita Kumar, Jack Poole, Keith Worden, Austin Downey, Jie Wei, Patrick F. Musgrave, Adrian S. Wong, Guiseppe Quaranta, Marco Martino Rosso, Giuseppe Carlo Marano, Yu Chen, Et. Al.

Faculty Publications

Advances in computing and machine learning (ML) methods have led to a rapid rise in artificial intelligence (AI) research and applications in many fields. AI research benefitted from advances in computation hardware, collection and distribution of large data sets, and proliferation of software techniques. AI techniques include ML for provable results, deep learning for data exploration, reinforcement learning for control, and active learning for adaptive systems. Likewise, AI algorithms can handle large amounts of data, construct unknown representations, and provide a direct link between data and classification for decision making. These unmatched capabilities have been seen as a path to …

Go to article

Etv2 Mediated Differentiation Of Human Pluripotent Stem Cells Results In Functional Endothelial Cells For Engineering Advanced Vascularized Microphysiological Models, Shun Zhang, Zhengpeng Wan, Lei Wang, Caihong Wu, Junkai Zhang, Sarah Spitz, Xun Wang, Marie A. Floryan, Mark F. Coughlin, Francesca M. Pramotton, Liling Xu, Ron Weiss, Roger D. Kamm Mar 2026

Etv2 Mediated Differentiation Of Human Pluripotent Stem Cells Results In Functional Endothelial Cells For Engineering Advanced Vascularized Microphysiological Models, Shun Zhang, Zhengpeng Wan, Lei Wang, Caihong Wu, Junkai Zhang, Sarah Spitz, Xun Wang, Marie A. Floryan, Mark F. Coughlin, Francesca M. Pramotton, Liling Xu, Ron Weiss, Roger D. Kamm

Michigan Tech Publications

Patient-specific microphysiological models have become a valuable tool for broad applications, revolutionizing biomedical research. However, limitations persist, with functional vasculature being a significant challenge. With the discovery of ETV2's determinant role in specifying EC lineages during differentiation, researchers have adopted techniques involving ETV2 overexpression to produce h-iECs more efficiently and consistently. Here, we generated multiple h-iPSC lines with inducible ETV2 expression, and subsequently differentiated them into h-iECs, which were validated functionally and by key endothelial markers and RNA-seq analysis. These cells are capable of reproducibly self-organizing into stable microvascular networks (MVNs) in a microfluidic chip, forming lumenized and functional vessels …

Go to article

Electrochemical Deactivation Of High-Strength, Catechol-Based Adhesives Incorporated With Anhydrous Proton And Electron Conducting Elements, Han Peng, Zhongtian Zhang, Vedika Khare, Abhilash Arjan Das, Fatemeh Razaviamri, Kan Wang, Bruce P Lee Mar 2026

Electrochemical Deactivation Of High-Strength, Catechol-Based Adhesives Incorporated With Anhydrous Proton And Electron Conducting Elements, Han Peng, Zhongtian Zhang, Vedika Khare, Abhilash Arjan Das, Fatemeh Razaviamri, Kan Wang, Bruce P Lee

Michigan Tech Publications

Catechol offers switchable adhesion in response to electrochemical redox reaction. However, electrochemistry requires water for effective proton transport, but water weakens adhesive performance. Here, we incorporate proton and electron conducting elements (sulfonic acid-containing monomer and multiwalled carbon nanotube, respectively) into a water-free catechol-based adhesive to create a high-strength adhesive that is also susceptible to electrochemical control. These additions increase the proton and electrical conductivity by over 100-fold. The adhesive also exhibits elevated lap shear adhesion strength (4.6 MPa) to metal substrates and outperforms a commercial epoxy glue. Under mild electrical stimulation (9 V), the adhesive strength decreases by over 90%. …

Go to article

An Exploration Of Aviation Safety And Security Culture In Nigeria And The United Arab Emirates (Uae), Nicholas Degarmo, Kathrine Lopez, Hana Marz, Cedric Leon, Michael Chrisman Mar 2026

An Exploration Of Aviation Safety And Security Culture In Nigeria And The United Arab Emirates (Uae), Nicholas Degarmo, Kathrine Lopez, Hana Marz, Cedric Leon, Michael Chrisman

Student Research Symposium (SRS)

Aviation safety and security standards are fundamental for enabling the reliability and sustainability of aviation operations. Aviation safety and security are influenced by organizational and institutional standards, as well as the application of human factors principles. This paper aims to explore the regional variances of aviation safety and security culture within Nigeria and the United Arab Emirates (UAE). Both regions have taken great steps to align with international aviation standards, offering insight into how different regions shape their regulatory environments, organizational culture, and how cultural factors affect safety and security practices. While Nigeria continues to face challenges such as inconsistent …

Go to article

Comparison Of The Impact Of Probabilistic Versus Deterministic Ground Motions On Structural Responses Of A Steel Moment Building In Salt Lake City, Utah, O. Murphy, M. Zaker Esteghamati, B. R. Cox Mar 2026

Comparison Of The Impact Of Probabilistic Versus Deterministic Ground Motions On Structural Responses Of A Steel Moment Building In Salt Lake City, Utah, O. Murphy, M. Zaker Esteghamati, B. R. Cox

Civil and Environmental Engineering Student Research

Earthquakes on the Wasatch Fault pose a significant hazard to Utah’s people and built environment. Code-based seismic design of civil infrastructure in Utah is governed by ground motions determined from regional probabilistic seismic hazard analysis (PSHA). However, with a large earthquake overdue along several segments of the Wasatch Fault, there is growing concern among Utah engineers that PSHA-based ground motions are significantly lower than those from a deterministic scenario. This study compares the structural responses of a four-story steel moment frame in Salt Lake City, Utah, under two ground-motion sets derived from risk-targeted probabilistic and deterministic seismic-hazard analyses. The preliminary …

Go to article

An Ambient Acoustic Ice-Fracturing Dataset Taken In Shallow Freshwater, John Case, Andrew Barnard, Daniel Brown Mar 2026

An Ambient Acoustic Ice-Fracturing Dataset Taken In Shallow Freshwater, John Case, Andrew Barnard, Daniel Brown

Michigan Tech Publications

This paper describes an acoustic dataset collected on a frozen shallow freshwater lake between February and March of 2024. This collection took place over one full week on Portage Lake in the Upper Peninsula of Michigan, USA. The first sub-dataset consists of ambient ice and environmental noises collected by an array of hydrophones, microphones and geophones placed below, above and on the ice respectively. The second sub-dataset consists of instrumented force hammer impacts at a series of locations on the the ice with the corresponding response at each acoustic sensor. All acoustic data were recorded at a sample rate f …

Go to article

First Prev Next Last