Engineering Commons^™

Robustness Of Ai-Driven Histopathology Under Real-World Adversarial Examples, Ruchik N. Yajnik

Theses

This robustness of histopathology classification models under adversarial and real-world perturbations resembling clinical artifacts is being investigated.

Using whole-slide images from the CAMELYON17 cohort, four representative architectures—ResNet-18, ResNet-50, HIPT-2MLP, and ViT-B/16 —are benchmarked across controlled pixel-level distortions and artifact-like transformations. Adversarial methods include iterative Fast Gradient Sign, Projected Gradient Descent, Salt-and-Pepper noise, and the Adversarial Watermark—Stain Shift (AWSS). Three defense strategies—Randomized Smoothing, Adversarial Training, and an Artifact Detector—are evaluated for their ability to preserve diagnostic accuracy and model reliability. Structured perturbations consistently degrade performance, with transformer-based models showing the greatest sensitivity. The benchmark developed here offers a reproducible framework for …

Machine Learning-Driven Prediction And Mechanistic Insight Into Co2 Adsorption On Biomass-Derived Activated Carbons Using Explainable Ai (Xai), Dalia A. Ali Dr.

Chemical Engineering

To improve CO2 uptake in Biomass-Derived Activated Carbon (BDAC), this study develops a multiscale hybrid digital twin framework. By integrating microscopic descriptors from Density Functional Theory and Molecular Dynamics (DFT/MD) with experimental data from 63 chemically diverse biomass precursors, a Gaussian Process Regression (GPR) model was developed using the Materń 5/2 Automatic Relevance Determination (ARD) kernel. The framework achieved high internal training accuracy (R2 = 0.968) and Root Mean Square Error (RMSE = 0.2552), while providing a realistic generalization baseline across heterogeneous precursors with a 5-fold Cross Validated (CV) R2 of 0.1567 and CV RMSE of 0.283. Explainable Artificial Intelligence …

Ai-Augmented Financial Advisors: Comparing Ai And Human Analyst Investment Recommendations In Agreement, Performance, And Firm Size Effects, Crystal Chen

Honors College Theses

This study examines the level of agreement and performance between artificial intelligence (AI) generated investment recommendations and human analyst recommendations across U.S. publicly traded firms. Using a sample of twelve companies categorized by firm size (large, mid, and small), the study collects buy, hold, or sell recommendations from generative AI systems and human analysts. Agreement between AI-to-AI and AI-to-human recommendations is measured using Cohen’s Kappa agreement. Portfolio performance is evaluated by constructing equal-weighted portfolios for each recommendation source and size category. Risk-adjusted returns are measured using the Sharpe ratio over 1-, 2-, and 3-month periods. Furthermore, the study tests whether …

Omama-Db: The Oregon-Massachusetts Mammography Database, Avanih Kanamarlapudi

Graduate Masters Theses

Public datasets for training AI models in breast cancer screening are limited in size and quality, making it difficult to develop reliable systems. We introduce OMAMA-DB, an extensive publicly available collection of 2D mammograms and 3D tomosynthesis volumes. Starting from 967,991 images, we created a curated set of 231,080 images us ing a multi-stage filtering process that removes missing labels, uncommon dimensions, rare scanner types, duplicate studies, and invalid DICOM files. All 2D images then undergo additional outlier detection using histogram filtering and a variational autoen coder to remove low-quality outliers. OMAMA-DB includes pathology-based cancer labels and automated lesion annotations …

Drilling Fluid Enhancement Via Addition Of Sustainably Synthesized Nanoparticles, Hasan A. Abbood, Sarmad Al-Anssari

Research outputs 2022 to 2026

The addition of nanoparticles to the drilling fluids for geological projects is a promising application for enhancing the stability, rheological properties, and overall performance of the mud. This study aims to thoroughly analyze and compare the effects of silica and alumina nanoparticles on the properties and effectiveness of polymer drilling mud. Silica and alpha-alumina nanoparticles were synthesized using the sol-gel process and characterized through several techniques, including X-ray diffraction, Fourier-transform infrared spectroscopy, field-emission scanning electron microscopy, and atomic force microscopy. The effects of silica and alumina nanoparticles on various properties of drilling mud were then measured using a permeable plugging …

Towards Interpretable Transfer Learning With Limited Data, Youxiang Zhu

Graduate Doctoral Dissertations

Modern foundation models are typically trained with large-scale data to ensure good performance. However, certain tasks cannot scale with large amounts of data due to cost and practical constraints, resulting in limited performance. To address this, in this dissertation, I introduce model-task alignment, a general methodology for making a foundation model work well with tasks with limited data. The methodology comprises two parts: aligning downstream tasks with foundation models and aligning foundation models with downstream tasks. To study and validate this methodology, I first focus on speech-based dementia detection, a representative task with limited data, and then extend to general …

Electrospun Nanofiber Scaffolds For In Vitro 3d Tissue Engineering, Victoria E. Santillan, Samerender Nagam Hanumantharao, Stephanie Bule, Ronish M. Shrestha, Carter Rodzik, Alan Mendoza Estrada, Stephen L. Farias, Marina Tanasova, Smitha Rao

Michigan Tech Publications

Tissue engineering is widely used in research for investigating cellular proliferation, behavior, and responses to various stimuli. However, the predictive value of preclinical studies using cell culture plates is limited by the inability to recapitulate the complexity of the physiological microenvironment. Synthetic three-dimensional (3D) scaffolds can be engineered to mimic the complex morphology of the extracellular matrix of native tissues and can serve as physiologically relevant platforms for preclinical studies. In this study, 3D electrospun scaffolds were characterized to aid in breast cancer research. Unlike previous studies that focused primarily on scaffold fabrication or cell viability, this work systematically evaluates …

Software Engineering: Ai-Enhanced Full Stack Development, Huixin Wu, Haiying Xiao

Open Educational Resources

This course provides instruction in full‑stack web application development using modern JavaScript technologies. Students design, implement, and deploy web‑based solutions while applying AI‑assisted development tools in an ethical and effective manner. The curriculum emphasizes problem‑solving, system design, teamwork, and industry‑standard best practices, with dedicated focus on cloud‑native development—including containerization, distributed services, and modern deployment pipelines—as well as API‑first architecture, enabling students to build scalable, maintainable, and interoperable applications aligned with current industry expectations.

Hydrodynamic Analysis And Cfd Modeling Of Pawec Interacted With Regularwaves Using Cfx, Ahmed Elbaz

Mechanical Engineering

The multiplicity of renewable energy sources represents the biggest challenge for environmental scientists and engineers. This research presents a mathematical model and a numerical study using the high-performance ANSYS-CFX software to analyze the dynamic behavior of the point absorberwave energy converter (PAWEC). Two different models were constructed to predict the hydrodynamic response of the wave energy converter in both free and forced oscillations under the action of incident regular waves and external mechanical damping. The differential equations are solved analytically using RKFOM. CFX multiphase model is constructed to solve the 3D Unsteady Reynolds Averaged Navier–Stokes Equation (URANS) using the two-way …

Debatrix, Vivienne Lu, Huy Ngo, Luke Ponssen, Jonathan Preiss, Ryan Rani

Computer Science and Engineering Senior Theses

Developing public-speaking skills remains a persistent challenge in formal education, constrained by limited instructional time and the lack of scalable, individualized feedback. Existing automated tools address only narrow aspects of this problem, offering text-based coaching against rigid rubrics that fail to capture argument quality, evidence use, or real-time rebuttal skill. This thesis presents Debatrix, an AI-powered platform that enables K-12 students, university learners, and independent self-studiers to debate an intelligent opponent. The system combines automatic speech recognition, large language model-driven rebuttal generation, and a multi-dimensional rhetorical analysis engine that evaluates argument structure, evidence integration, and persuasive technique. Users receive explainable …

Developing A Framework For Mooc Dropout: The Role Of Utilitarian And Hedonic Values In Student Retention, Bipllab Roy, Mave D'Souza, Madhura Laghane

Northeast Journal of Complex Systems (NEJCS)

Massive Open Online Courses (MOOCs) have expanded access to higher education but continue to face persistently high dropout rates, raising concerns about their long‑term effectiveness and sustainability. This study develops and empirically tests a structural framework that links utilitarian values (perceived usefulness, certificate value, time flexibility), hedonic values (enjoyment, variety and novelty, personal interest alignment), and individual characteristics (goal orientation, self‑efficacy, motivation type) to MOOC student retention. Data were collected through a structured questionnaire administered to 200 MOOC learners from Christ University, Lavasa Campus, and analyzed using Structural Equation Modelling (SEM) in AMOS. The results show that goal orientation, self‑efficacy …

Engineering: What Are We Doing?, Matthew Kuperus Heun

University Faculty Publications and Creative Works

Keynote speech at 2026 Christian Engineering Society Conference and 2026 Association for Christians in Mathematical Sciences Conference

Coupled Ferroelectricity And Phonon Chirality, Xiang-Bin Han, Cong Yang, Rui Sun, Xiaotong Zhang, Thuc Mai, Zhengze Xu, Aryan Jouneghaninaseri, Xiaoning Jiang, Rahul Rao, Yi Xia, Multople Additional Authors

Mechanical and Materials Engineering Faculty Publications and Presentations

Recognizing the coupling between ferroelectricity and chirality in optically active ferroelectrics opens a route for manipulating chirality via ferroelectricity under an external electric field, enabling control over chirality-dependent quantum states. Here, we report the experimental demonstration of the coupling between ferroelectricity and phonon chirality in the molecular ferroelectric triglycine sulfate. By electrically switching the crystal chirality, we achieve reversible and device-compatible control of phonon chirality, as revealed by in situ time-resolved magneto-optical Kerr effect measurements. The Kerr rotation reverses with electric-field switching, while phonon chirality vanishes in the paraelectric phase and is tunable in the racemic ferroelectric state. Furthermore, density …

Experimental Evaluation Of Walking Stability Of Bilateral Transtibial Prosthetic User: A Case Study, Mustafa Sharaf Jaian, Mahmud Rasheed Ismail

AUIQ Technical Engineering Science

Bilateral transtibial amputation presents a complex biomechanical condition in which the loss of biological ankle function and reduced sensory feedback can compromise walking stability. This case study aimed to experimentally evaluate gait stability in a bilateral transtibial prosthesis user under controlled sensory and mechanical walking conditions using a portable G-Walk inertial measurement system. The novelty of this study lies in the use of a structured three-factor experimental protocol that systematically combined visual input, arm posture, and surface type across twelve walking conditions to assess walk quality, propulsion, propulsion symmetry, and pelvic symmetry indices. The participant was a 31-year-old bilateral transtibial …

Are Single-Pilot Operations An Advantage Or A Disadvantage?, Ezgi Berte Erme

International Journal of Aviation, Aeronautics, and Aerospace

This study aims to investigate the potential benefits and drawbacks of Single-Pilot Operations (SPO) and to provide actionable insights for commercial airlines. A qualitative research design was employed, with data collected via online interviews and analyzed thematically and descriptively using MAXQDA 24. The findings indicate that pilots perceive several advantages of SPO, including the power of automation, learning artificial intelligence, minimizing human error, cockpit systems designed for artificial intelligence, more effective decision-making/speed-up in response time, reduced labor costs, reduced pilot fatigue, and reduced need for human factor/performance. Conversely, the perceived disadvantages include diminished lack of situational awareness, lack of communication …

Du Undergraduate Showcase Abstracts: Research, Scholarship, And Creative Works, Sophia Wismar, Henry Staats, Allison Metzler, Chloe Puckett, Rachel Levine, Christa Kilpatrick, Scott Wolf, Joe Walsh, Grace Doolittle, John Engebreston, Zoe Lopez, Christopher Aaby, Audrey Duff, Timothy Sisk, Katelyn Lamberton, Angela Narayan, Gilkah Argueta, Habiba Samir, Girena Tesfazghi, Genet Kenore, Sinit Tesfamariam, Effley Brooks, Abi Newell, Megan Doherty, Natalie Baer, Lexi Blood, Talya Riciputi, Jessica Jimenez, Devin Hernandez, Lynn Clark, Taj Kumar, Sunil Kumar, Allen Rutman, Mira Pronobis, Tess Carson, Anna Sher, Frankie Stroud, Tamra Pearson D'Estree, Alyssa Wilson, Emily Melnick, Jenalee Doom, Yihang Gao, Gwendolyn Geiger, Noah Gettle, Scott Nichols, Clare Ayoub, Cara Dienno, Sunny Walker, Zoe Hansen, Maya Wheeler, Addison Rice, Patrick Martin, Sanjana Acharya, Daniel Mcintosh, Amanda Mckellips, Calli Cain, Justin Blake, Peter Sokol-Hessner, Natalie Miller, Max Weisbuch, Sophia Dellota, John Macikas, Charlotte Snow, Mark Siemens, Zoe Lynch, Alex Huffman, Prachi Shah, Jason Roney, Halcyon Levi, Nicole Herzog, Andrea Koly, Daniel Linseman, Annie London, Xi Yang, Avery Zwisler, Jane Smith, Chaz Contag, Michael Kerwin, Lucy Rand, Grace Schroeder, Michelle Rozenman, Nissa Tapper, Guiming Zhang, Mateo Mazariego-Halpern, Keith Meyer, Julie Do, Dakota Park-Ozee, Travis Herink, Kara Neu, Jonathan Plomin, Eve-Odine Duchaufour, Debbie Gale Mitchell, Tennyson Anderson-Stricklin, Lily Treitz, Samantha Rosenberger, Sierra Griffith, Finley Joseph, Daniel Sampson, Emmy Davis, Skyler Kasnoff, Evon Lopez, Vivian Nguyen, Cassy Young, Franklin Sellner, Martin Tobon, Ila Graham, Zach Billings, Holden Hedit, Decatur Boland, Paul Kosempel, Cory Chandler, Jay Mahoney, Sam Dragan, Susan Dagget, Yarrow Ator, Heidi Vuletich, Owen Weber, Andrew Kloeppel, Petersen Gray, Mandi Schaeffer-Fry, Razleen Bassra, Bryanna Rodriguez, Christina Blue, Taubie Sanders, Rachel Epstein, Luke Milburn, Camryn Evans, Ezra Martinez, Mary Westwood, Gabri Notov, Robin Tinghitella, Lilou Cabrol, Eli Barbour, Juliet Mendik, Selma Myers, Zac Wise, Noah Fahlin, Michelle Knowles, Abigail Hopper, Michael Greenberger, Romi Laclair, Sarah Watamura, Sabrina Efroymson, Casey Barker, Sydney Seltzer, Bryn Yehle, Jennifer Hoffman, Sara Garcia, Ryuka Nagamine, Trevor Briggs, Remy Le Boeuf, Elena Krone, Eileen Farrell, Regan O'Rourke, Elena Roel, Greg Mortimer, Ali Ayoub, Stefani Langehennig, Caitlin Turk, Logan Scmid, Stefan Chavez-Norgaard, Karen Kim, Tatiana Peccedi, Courtney Cassidy, John Sebesta, Rhianna Lewis, Janice Bening-Lacek, Vivian Lawless, Mckenna Hanson, Jeffrey Amidon, Riya Joshi, Ram Ambre, Brady Worrell, Perrin Schneider, Ali Azadani, Brooke Agulnek, Lyndsie Salvagio, Elise Siemanowki, Yan Qin, Andre Allen, Melodie Nguyen, Megan Livengood, Abby Reams, Saffron Hartreeve, Bri Wylie, Sarah Brookman, Mariah Loiacono, Green Russo, Abhia Lodhi, Gabrielle Welsh, Nika Spehar, Shahked Levin, Evrim Baykal, Kimberly Chiew, Jocelyn Torres, Kailey Hicks, Mykaela Tanino-Springsteen, Audrey Bellows, Akam Chahal, Madeline Tepper, Shannon Murphy, Alexa Fonseca, Deborah Han, Cassandra Perez, Oluwatoyin Alaba, Julia Roncoroni, Vy Nguyen, Nana Burn, Sarah Sasse, Rubin Tuder, Anthony Gerber, Nancy Lorenzon, Christine Vohwinkel, Camryn Gunter, Tristan Weber, Sam Rommel, Brian Michel, Muskan Fatima, Alannah Oleson, Kira Frey, Edward Garrido, Beckett Morris, Kerstin Haring, Drew Middleton, Abigail Walpert, Liam Dee, Gabby Ishaw, Cole Carnes, Maddie Weiser, Claire Fox, Valeriia Vlasenko, Kateri Mcrae, Riley Smith, Abigail Templin, Kushani Rajapaksha

DU Undergraduate Research Journal Archive

Abstracts from the DU Undergraduate Research Showcase.

Modulating Electronic Structure With Linearly Fused Pyrazine Units For High-Voltage And Stable Zinc-Organic Batteries Cathode, Min-Jian Zhao, Li-Bin Zhang, Jin-Tao Wang, Kun Ding, Hai-Mei Liu, Yong-Gang Wang

Journal of Electrochemistry

High-voltage n-type organic cathode materials are critical for constructing zinc-organic batteries (ZOBs) with high energy density and long cycle life. However, the intrinsically unfavorable electronic structures and relatively high LUMO energy levels of most n-type materials often lead to sluggish kinetics, high solubility, and suboptimal discharge voltages (< 0.8 V). Here, we design a small molecule, quinoxalino[2’,3’:5,6]pyrazino[2,3-f][1,10]phenanthroline (DPQP), as a ZOB cathode by introducing locally electron-deficient motifs into the conjugated backbone of aromatic compounds. The linearly fused pyrazine units extending the pyrazine–benzene framework effectively optimize the electronic structure, thereby significantly enhancing the discharge voltage. Meanwhile, the expanded π-conjugated plane suppresses dissolution and accelerates charge-transfer kinetics. Benefiting from these features, the DPQP electrode exhibits an exceptional increase in average operating voltage from 0.61 V to 1.07 V (vs. Zn²⁺/Zn) at 0.1 A·g^–1, with an overpotential of only 140 mV. Notably, no discernible voltage decay occurs as the current density increases, indicating rapid and highly reversible redox kinetics. Furthermore, the DPQP cathode delivers outstanding cycling stability, maintaining over 2000 h of continuous operation at 0.1 A·g^{–1 …}

(Co,Ni,Mn,Cu,Zn)O High-Entropy Oxide Nanotubes As Efficient Bifunctional Electrocatalyst For Oxygen Evolution And Hydrazine Oxidation Reactions, Pan-Yan Chen, Wan-Wan Wu, Heng Bian, Wei-Wei Li, Xin-Sheng Zhao, Lu Wei

Journal of Electrochemistry

High-entropy oxides (HEOs) present significant scientific challenges in both design and synthesis due to their multielement and high-entropy nature, which involves complex combinations of multiple metal cations and oxygen anions, typically arranged in equimolar ratios to achieve structural stability. Herein, one-dimensional (Co,Ni,Mn,Cu,Zn)O high-entropy oxide nanotubes (HEO-NTs) are fabricated by means of a gradient electrospinning strategy with a tailored polyvinyl alcohol (PVA) molecular weight distribution and controlled pyrolysis. Benefiting from the HEO features and the synergistic effect of multicomponent sites, the as-synthesized (Co,Ni,Mn,Cu,Zn)O HEO-NTs exhibit exceptional bifunctional electrocatalytic activity for the oxygen evolution and hydrazine oxidation reactions (OER/HzOR). This study offers …

From Theory To Practice: Investigating Process Safety Skills Acquisition And Bridging The Industry Readiness Gap, Brittany Butler-Morton

Theses and Dissertations

Process safety management is vital to companies operating highly hazardous materials or processes, and it is of interest to the engineering community as poor process safety judgments can have catastrophic results. Process safety judgments consider more than the prioritization of safety, as they are often influenced by elements like production, spending, reputation, and time. As such, it’s important to prepare engineering students nearing graduation for the complexity of these judgments and narrow the Theory-to-Practice gap for students entering industry. This work sought to identify 1) how the Theory-to-Practice gap is manifesting in process safety judgments, and 2) how the application …

An Ai-Integrated Methodology For Secure Software And System Development, Ian Matthew Campbell Coston

Electronic Theses and Dissertations

Securing interconnected software systems requires more than layering existing frameworks on top of each other. Most current Secure Software and System Development Lifecycle (S-SDLC) models treat security as a phase rather than a design condition, leaving real gaps in governance, access control, and automated enforcement that become critical failure points in Internet of Things (IoT) environments where devices are resource-constrained, long-lived, and frequently insecure by default.

This dissertation introduces the Automated Zero Trust Risk Management with DevSecOps Integration (AZTRM-D) methodology, a novel approach that unifies DevSecOps automation, the National Institute of Standards and Technology (NIST) Risk Management Framework (RMF), and …

Zirconium Metal-Organic Cages: Synthetic Development Of Chromium-Functionalized Ligands, Jim P. Heller, Jonathan E. Pines, Miguel I. Gonzalez

Wetterhahn Science Symposium Posters

Metal-organic cages (MOCs) are a class of highly porous molecules composed of inorganic clusters bridged by highly tunable organic ligands. The synthesis and development of various ligands could allow for more selective and efficient catalysts. Specifically, Chromium-based homogeneous catalysts have recently been commercialized due to their high selectivity in the production of 1-hexene and 1-octene. This project aims to synthesize reusable heterogeneous catalysts composed of chromium-functionalized zirconium MOCs deposited on mesoporous supports.

The current focus of this project is to synthesize and purify the "SNS Ligand." This ligand can coordinate to chromium via its S—N—S moiety. This project specifically focuses …

The Effects Of Solutes On The Growth Of Crystals In Polycrystalline Ice ​, Roberto Nieto Jr, Chinazom Onubogu, Ian Baker

Wetterhahn Science Symposium Posters

The structure of sea ice (NaCl-doped water) differs from freshwater ice. In this project, we will be investigating how ice grows when doped with various solutes such as sodium chloride and sulfuric acid. There are two projects that were investigated. The first project consisted of finding the velocity of the ice growth of deionized water, saltwater, and water doped with sulfuric acid. The second project consisted of observing how the polycrystalline structure of ice differs between deionized water, saltwater, and water doped with sulfuric acid.

A Faith And Technology Resource Hub: Building The Christian Engineer’S Bookshelf, Gayle Ermer, Derek Schuurman

University Faculty Publications and Creative Works

A wealth of material related to the interactions between faith and technology has been generated over time to help Christian engineers reflect on and evaluate their work and technology development more generally. However, there is currently no central location where this large variety of resources can easily be accessed. This paper will describe the process of developing a faith and technology resource hub. The vision for the hub is that it will include a comprehensive searchable directory of resources addressing faith and technology, as well as a browsable, organized, curated, and annotated set of webpages containing links to particularly important …

Evaluating Soil Health And Crop Yield In Louisiana Agricultural Systems: Impacts Of Best Management Practices And Prediction Models, Hector J. Mendoza Lagos

LSU Doctoral Dissertations

The adoption of conservation management practices is critical for improving soil health, enhancing nutrient use efficiency, and sustaining crop productivity in row crop systems in Louisiana. This study evaluated the role of conservation agronomic practices, soil biochemical indicators, and machine learning predictive models to improve soil nutrient dynamics, soil health indicators, microbial communities (MC), and crop productivity on a corn (Zea mays L.) research plot scale and in a commercial forty-hectare cotton (Gassypium hirsutum L.)-corn-soybean (Glycine max L.) rotation system in northeast Louisiana. The objectives of the study were to evaluate soil nutrient dynamics and MCs under …

Measuring Stock Market Inefficiency Using A Multilayer Composite Efficiency Index: A Case Of The Egyptian Exchange, Patrick K. Owido, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

Financial markets play a critical role in resource allocation. Their performance depends on the decisions of millions of independent investors constantly reacting to one another. Their informational efficiency remains a subject of debate across economic systems. When informational efficiency is present at the weak form, historical price information should not consistently predict future returns. Several empirical tests of this hypothesis often focus on the behavior of aggregate market indices, and use individual efficiency proxies such as autocorrelation, GARCH-type volatility, or entropy-based measures to measure efficiency. This has often yielded mixed results, particularly in emerging markets. Here we show that testing …

High-Throughput Robotic Ethanol Inhibition Assays For Engineered Thermophilic Biofuel Strains, Kevin He, Daniel Olson, Marybeth Maloney, Anthony Lanahan

Wetterhahn Science Symposium Posters

Ethanol stress assays are commonly used to evaluate microbial tolerance, metabolic adaptation, and fermentation performance. However, manual liquid handling introduces variability across replicate wells and small-volume pipetting steps, limiting reproducibility and throughput. This study developed an automated OT-2 robotic workflow to generate replicated ethanol concentration gradients for high-throughput inhibition assays in engineered thermophilic biofuel strains. Kinetic plate-reader measurements were used to quantify ethanol-dependent growth responses under anaerobic fermentation conditions. The reasearch question is: How do engineered thermophilic biofuel strains differ in ethanol-dependent growth inhibition under anaerobic fermentation conditions, and can automated robotic assays improve the reproducibility of these measurements? Can …

Electropulse Annealing: Phase Composition Of Tial6v4, Vaughn Eckhardt, Ethan Croke, Ian Baker, Russ Taylor

Wetterhahn Science Symposium Posters

Titanium alloy TiAl6V4 is the most ubiquitous titanium alloy used for dental care, aerospace manufacturing, and for high performance vehicles. The material typically undergoes a thermal heat  treatment, but electropulse annealing is another process that involves sending current through the material to heat it up at a quicker rate. The rate of post-annealing cooling is high, and around the material's critical point, its two components, alpha and beta phase, change in relative concentration. After testing multiple current densities and temperatures, in general, as the current density that the sample received during electropulse annealing decreased, both the alpha and beta phases …

Enhanced Population Mean Estimation Using An Exponential Estimator With Known Medians Of Dual Auxiliary Variables Within A Neutrosophic Approach: Applications In Agricultural Yield Prediction, Anchal Yadav, Mukesh Kumar

Neutrosophic Systems with Applications

In classical statistical theory, estimation of population parameters is generally carried out under the assumption that all observed data are precise, complete, and free from ambiguity. However, in many practical and real-world situations, data often deviate from these ideal conditions and instead appear in vague, uncertain, or interval-valued forms. Such imperfections reduce the effectiveness of traditional estimation techniques and motivate the development of more flexible and robust methodologies. To address these challenges, several improved estimators, particularly neutrosophic ratio-type estimators and their advanced extensions, have been proposed in recent literature. In this study, a new estimator known as the two auxiliary …

On Some Properties Of Generalised Regular Anti-Topological Space, Bhimraj Basumatary, Gugu Narzary, Jeevan Krishna Khaklary

Neutrosophic Systems with Applications

This article studies Regular Anti-open sets and Generalised Regular Anti-open sets within a topological framework, addressing the limited development of anti-open structures in generalised topology. We introduce Regular Anti-open sets and establish their fundamental properties. The study is extended by defining Generalised Regular Anti-open sets, providing a broader and more flexible class of sets. Furthermore, the notions of GR-interior and GR-closure are introduced and analyzed, and their essential properties are obtained. The results contribute to a clearer understanding of generalized anti-open structures and provide a basis for further research in topology.

Optimization Of A Multi-Item Supply Chain Model With Shortages Under Parametric Type-2 Interval Environments, Sourav Kumar Kumar Giri, Totan Garai, Sahidul Islam, Haridas Mondal, Shariful Alam

Neutrosophic Systems with Applications

Modern supply chain systems frequently operate in environments where demand, costs and inventory-related parameters are uncertain and difficult to estimate accurately. These uncertainties become more critical in multi-objective decision-making situations, where decision makers must simultaneously balance several conflicting goals. Conventional optimization techniques often fail to represent the ambiguity and vagueness present in practical decision environments. To overcome these limitations, this study develops a multi-item supply chain model for a single supplier and a single buyer by incorporating Type-2 interval representations into the modelling framework. The proposed approach introduces a structured set of arithmetic operations for Type-2 intervals to manage uncertain …