Digital Commons Network^™

Insight Into The Decalcification Mechanism Of Calcium Silicate Hydrate Under A Water–Heat–Salt Environment, Wei Zhang, Boya Zhang, Jia Sun, Juntao Dang, Xiangke Guo, Keliang Li, Bo Tao Huang, Biqin Dong, Hongyan Ma, Dongshuai Hou

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Understanding the decalcification mechanism of calcium silicate hydrate (C–S–H) under marine environments is crucial for concrete durability. In this study, the decalcification behavior of C–S–H under a water–heat–salt environment was systematically investigated through immersion experiments and reactive molecular dynamics simulations. Experimental results showed that elevated temperature and NaCl solution significantly accelerated Ca leaching and reduced the Ca/Si ratio of C–S–H. Simulation results further revealed that both high temperature and NaCl reduce the dissolution free energy of Ca, making its release more thermodynamically and kinetically favorable. Local structure analysis indicated that Cl^– disrupts Ca–Os (O atoms in silicate tetrahedra) connection …

Robust And High-Efficiency Demodulation Of Ultra-Weak Fbg Arrays In Ofdr-Based Distributed Sensing, Zhaopeng Zhang, Yuxuan Cao, Xu Liu, Dingcheng Wang, Bo Liu, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

A robust and high-efficiency demodulation scheme for optical frequency domain reflectometry (OFDR) based ultra-weak fiber Bragg grating (UWFBG) array detection system, originating from the Buneman frequency estimation (BFE) algorithm, is proposed and experimentally demonstrated. Due to the current limitations and imperfections of FBG inscription technology, the quasi-continuous inscription approach, along with its less-than-ideal outcomes, gives rise to problems of grating spectrum splitting and spectral distortion during the grating demodulation process. This renders the traditional approach of directly applying the BFE algorithm for grating demodulation ineffective, despite its significant enhancement of demodulation efficiency. To address this issue, we propose utilizing the …

Rogue Waves In Extended Gross-Pitaevskii Models With A Lee-Huang-Yang Correction, Sathyanarayanan Chandramouli, S. I. Mistakidis, G. C. Katsimiga, D. J. Ratliff, D. J. Frantzeskakis, P. G. Kevrekidis

Physics Faculty Research & Creative Works

We explore the existence and dynamical generation of rogue waves (RWs) within a one-dimensional quantum droplet-bearing environment. RWs are computed by deploying a space-time fixed point scheme to the relevant extended Gross-Pitaevskii equation (eGPE). Parametric regions where the ensuing RWs are different from their counterparts in the nonlinear Schrödinger equation are identified. To corroborate the controllable generation—relevant to ultracold atom experiments—of these rogue patterns, we exploit two different protocols. The first is based on interfering dam break flows emanating from Riemann initial conditions, and the second refers to the gradient catastrophe of a spatially localized waveform. A multitude of possible …

Pciafl: Personalized And Class Imbalance-Aware Federated Learning For Driver Behavior Classification, Osho Osho, Shubh Garg, Suchetana Chakraborty, Sajal K. Das

Computer Science Faculty Research & Creative Works

Automated understanding of driver behavior from vehicular kinematics is vital for safety-aware intelligent transportation systems. However, centralized cloud processing suffers from latency, scalability, and privacy issues. Federated Learning (FL) provides a decentralized alternative but faces two major challenges: (i) non-IID client data due to heterogeneous driving styles and sensors, and (ii) severe class imbalance, as risky behaviors are inherently rare. In this work, we propose a personalized FL framework that uses a shared CNN-LSTM backbone with client-adaptive classifiers and incorporates a cost-sensitive loss to address behavior skew. Evaluated on the UAH-DriveSet dataset, our method achieves 92.60% accuracy and 91.68% macro-F1, …

Datamut: Deterministic Algorithms For Time-Delay Attack Detection In Multi-Hop Uav Networks, Keiwan Soltani, Federico Corò, Punyasha Chatterjee, Sajal K. Das

Computer Science Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs), also known as drones, have gained popularity in various fields such as agriculture, emergency response, and search and rescue operations. UAV networks are susceptible to potential security threats, such as wormhole attacks, jamming, spoofing, and false data injection. Time-Delay Attack (TDA) is a unique attack in which malicious UAVs intentionally delay packet forwarding, posing significant threats, especially in time-sensitive applications. It is challenging to distinguish malicious delay from benign network delay due to the dynamic nature of UAV networks, intermittent wireless connectivity, or the Store-Carry-Forward (SCF) mechanism during multi-hop communication. Some existing works propose machine learning-based …

Rescue: Routing Under Evolving Stochastic Congestion And Uncertain Spread In Wildfire Emergencies, Sowjanya Tammali, Arindam Khanda, Anurag Satpathy, S. M. Shovan, Sajal K. Das

Computer Science Faculty Research & Creative Works

Wildfires cause unpredictable spread and panic-driven congestion, posing severe challenges to evacuation planning. We present RESCUE (Routing under Evolving Stochastic Congestion and Uncertain Spread in Wildfire Emergencies), a dynamic, risk-aware framework that models the road network as a time-varying weighted graph. RESCUE operates in two stages: (i) a preprocessing phase integrating fire forecasts, traffic density, and distance to assign edge weights, and (ii) a real-time routing phase that adaptively updates paths using a multi-granular strategy distinguishing macro-level disruptions (e.g., rapid spread) from micro-level changes (e.g., local congestion). Two stochastic edge-cost functions are introduced: the Edge-Fire Risk Function (EFRF), estimating road …

Enhanced Superconductivity And Vortex Dynamics In Quasi-1d Tas2 Nanowires, Mathew Pollard, Visakha Ho, Clarissa Wisner, Eric W. Bohannan, Yew San Hor

Chemistry Faculty Research & Creative Works

We report the synthesis of high-quality 2H-TaS₂ nanowires via a controlled two-step conversion process from TaS₃ precursors, achieving robust superconductivity with a transition temperature T c ≈ 3.6K, which is significantly higher than bulk 2H-TaS₂ (T c ≈ 0.8K). Structural and compositional analyses confirm phase purity and preserved one-dimensional morphology, while magneto transport measurements reveal an enhanced upper critical field μ 0 H c2 (2K)≈5 T, far exceeding the bulk value (_μ0H_c2 (0)≈1.17T), attributed to dimensional confinement and suppression of charge-density wave order. Magnetic characterization demonstrates complex vortex dynamics, including flux jumps and a …

Work-In-Progress: Evaluating Feasibility Of Band Matrix Solvers For Scaling Up Extreme Learning Machine Method, Anton Akusok, Kaj Mikael Björk, Amaury Lendasse, Leonardo Espinosa Leal

Engineering Management and Systems Engineering Faculty Research & Creative Works

This work presents the results of the potential of band linear system solvers for improving the scalability of the Extreme Learning Machine (ELM) method at large model sizes. The model is tested on the standard MNIST dataset with a range of solvers provided by the SciPy Python library. The results are analyzed taking into consideration the overall performance and the performance impact of band solvers across different matrix bandwidths, as well as the performance versus runtime analysis. The findings show potential in applying the proposed method to very large ELM models with narrow band matrices.

Consumer Responses To Ethical And Privacy Concerns In Ai Chatbots: Evidence From Offensive Language, Gender Bias, And Digital Privacy, Jikhan Jeong

Economics Faculty Research & Creative Works

Due to the rapid innovation of artificial intelligence (AI) and big data, AI chatbots have become increasingly influential computational social systems (CSS) in everyday life. However, the expansion of interactions between AI chatbots and consumers has raised significant ethical and privacy concerns. Using data from an online survey, this study empirically examines how consumer concerns about AI ethics and privacy influence their intention to use AI chatbots. These concerns are categorized into three types: 1) offensive language (generated by AI chatbots or users); 2) gender-biased language (from either source); and 3) digital privacy violations. The findings suggest that prior experience …

Explaining The Unseen: Multimodal Vision-Language Reasoning For Situational Awareness In Underground Mining Disasters, Mizanur Rahman Jewel, Mohamed Elmahallawy, Sanjay Kumar Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

Underground mining disasters produce pervasive darkness, dust, and collapses that obscure vision and make situational awareness difficult for humans and conventional systems. To address this, we propose MDSE, Multimodal Disaster Situation Explainer, a novel vision-language framework that automatically generates detailed textual explanations of post-disaster underground scenes. MDSE has three-fold innovations: (i) Context-Aware Cross-Attention for robust alignment of visual and textual features even under severe degradation; (ii) Segmentation-aware dual pathway visual encoding that fuses global and region-specific embeddings; and (iii) Resource-Efficient Transformer-Based Language Model for expressive caption generation with minimal compute cost. To support this task, we present the Underground Mine …

Sadqn-Based Residual Energy-Aware Beamforming For Lora-Enabled Rf Energy Harvesting For Disaster-Tolerant Underground Mining Networks, Hilary Kelechi Anabi, Samuel Frimpong, Sanjay Madria

Mining Engineering Faculty Research & Creative Works

The end-to-end efficiency of radio-frequency (RF)-powered wireless communication networks (WPCNs) in post-disaster underground mine environments can be enhanced through adaptive beamforming. The primary challenges in such scenarios include (i) identifying the most energy-constrained nodes, i.e., nodes with the lowest residual energy to prevent the loss of tracking and localization functionality; (ii) avoiding reliance on the computationally intensive channel state information (CSI) acquisition process; and (iii) ensuring long-range RF wireless power transfer (LoRa-RFWPT). To address these issues, this paper introduces an adaptive and safety-aware deep reinforcement learning (DRL) framework for energy beamforming in LoRa-enabled underground disaster networks. Specifically, we develop a …

A Literature Review And Conceptual Framework For Sustainability In Open-Pit Mine Planning, Raymond Kudzawu-D'Pherdd, Kwame Awuah-Offei, Esteban Koberg De La Cruz, Marcos Goycoolea, Andrea Brickey, Alexandra M. Newman

Mining Engineering Faculty Research & Creative Works

This paper presents a comprehensive literature review and a conceptual framework for integrating environmental sustainability into strategic mine planning, focusing on open pits. Despite growing interest, easily discernible sustainability metrics remain elusive in early mine-planning stages, and are included as a post-processing step, if at all, rather than integrated a priori into a mine plan via, e.g., optimization. Through a literature review, we identify efforts regarding how environmental dimensions, such as emissions, water use, and land rehabilitation, are addressed across mine planning phases. We propose the Environmental Stewardship and Sustainability Framework for Mine Planning, which: (i) embeds sustainability into decision …

Meshless Collocation Methods For Time-Dependent Nonlocal Problems Based On Radial Basis Functions, Qiao Zhuang, Yanzhi Zhang, Zhongqiang Zhang

Mathematics and Statistics Faculty Research & Creative Works

We present radial basis function (RBF) collocation methods for time-dependent space fractional problems on general bounded domains. Building on a recently developed approach for accurately computing the integral fractional Laplacian of any RBF, we design collocation schemes for fractional heat and Stokes equations using extended-domain techniques. In particular, we propose a numerical Leray projection method for fractional Stokes problems, where both the discrete projection operator and the collocation scheme are formulated on extended domains to handle complex domains. Numerical results demonstrate the effectiveness of the proposed methods in solving time-dependent nonlocal problems on complex domains.

January 2026 Cafe Newsletter - Special Events Edition, Missouri University Of Science And Technology

CAFE Faculty Newsletters

No abstract provided.

January 2026 Cafe Newsletter - Special Edition, Missouri University Of Science And Technology

CAFE Faculty Newsletters

Center for Advancing Faculty Excellence (CAFE) newsletter January 2026.

Safety Aware Continual Reinforcement Learning-Based Output Tracking Control Of Nonlinear Continuous-Time Systems, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

An output feedback (OF)-based control scheme utilizing both a scalable multilayer neural network (MNN) observer and actor–critic MNN via integral reinforcement learning (IRL)/adaptive dynamics programming (ADP) approach for a class of nonlinear systems with output constraints is introduced. The proposed observer, critic, and actor MNN weight updates are derived using a singular value decomposition (SVD) of MNN activation function gradient along with output error, Bellman and control input errors, respectively. Next, the approach incorporates continual learning (CL), utilizing a penalty function in the weight update laws for both actor–critic MNNs to consolidate knowledge from previous tasks and enhance learning in …

A Coupled Thermo-Hydraulic Transfer Model For Soil Freezing, Antai Dong, Xiong Zhang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Frost heave is a common challenge in cold regions, threatening infrastructure stability. Despite decades of research, numerical simulation remains difficult due to the complex nature of coupled processes. This study presents a coupled thermo-hydraulic model for soil freezing, developed within the framework of unsaturated soil mechanics. The model uses suction and temperature as primary variables and incorporates a method to estimate ice content. It employs a soil freezing characteristic surface (SFCS), previously developed in related work, to calculate unfrozen water content as a function of both suction and temperature in partially frozen soils. The model is implemented in COMSOL for …

The Effect Of Reviewer Heterogeneity Between One-Time And Multi-Review Reviewers, Price Sentiment, And Pre-Purchase Information On Star Ratings For Amazon Subscription Boxes, Jikhan Jeong

Economics Faculty Research & Creative Works

This study examines the presence, prevalence, and negative polarity of one-time reviewers compared to those who have left multiple reviews across all categories, based on an analysis of 571,544,746 Amazon product reviews. Since sellers and consumers may be interested in specific products relevant to their business or purchasing interests within a category rather than across all categories, this research focuses on the Subscription Boxes category for econometric analysis. This category exhibits an unusual rating distribution, likely presents fewer incentives for promotional reviews, and faces fewer constraints. However, price data is unavailable in this category. Therefore, this study develops price sentiment …

Reflections On Linear B (Part 13): Sign 21 May Derive From The Ancient Egyptian 'Wedjat Eye’ (‘Eye Of Horus’ But Also Associated With Ra), Gerald Leonard Cohen

Arts, Languages and Philosophy Faculty Research & Creative Works

This article suggests that Linear B sign 21 (of unknown origin)

may derive ultimately from the Ancient Egyptian ‘wedjat eye’

(Eye of Horus). A point of special interest here is the possibility

that the pronunciation of Linear B sign 21 (designated as ‘qi’)

derives in abbreviated form from the Proto-Indo-European dual

of ‘eye’ and would therefore be the oldest Greek attestation of

that reconstructed PIE form.

Effect Of Ionic Strength On Gelation Time And Strength Of Amps-Based Polymer Gels, Maryam Sharifi Paroushi, Xuyang Tian, Baojun Bai, Thomas P. Schuman, Yin Zhang, Mingzhen Wei

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Polymer gel treatment has been widely applied for improving sweep efficiency and controlling excessive water and gas production. Their performance depends on gelation time and final gel strength. In most studies, brine salinity is used to describe the effect of formation water on gel behavior. However, changing salinity also changes ionic strength and ion composition at the same time. Because of this coupling, it is difficult to identify the mechanisms controlling gelation, which has led to inconsistent trends in the literature. Increasing salinity has been reported to either slow or accelerate gelation and to weaken or strengthen gels depending on …

Soil Freezing Characteristic Surface For Partially Frozen Soils, Antai Dong, Xiong Zhang, Ming Xiao

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The soil freezing characteristic curve (SFCC), which relates unfrozen water content to temperature, is a fundamental constitutive relationship in frost heave simulations. However, the influence of soil suction, another critical state variable, is often neglected. This study highlights how the SFCC is significantly affected by suction conditions, with unfrozen water content varying markedly between saturated (suction = 0) and completely dried (suction = ∞) conditions at the same subfreezing temperature. Recognizing this limitation, the concept of the soil freezing characteristic surface (SFCS) is proposed to incorporate the impacts of both temperature and suction on unfrozen water content. After that a …

Managing And Accelerating The Circular Economy Transitions Within The Construction Value Chain Using Network Governance And Game Theory Systems Perspectives, Radwa Eissa, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The fragmented nature of the construction industry has hindered its transition toward circular economy (CE) practices. While game theory (GT) has been successfully applied to support the strategic decisions of CE transitions in other sectors, CE-GT models in the construction domain remain extremely limited. This paper addresses two research questions: (1) how are CE network governance activities currently modeled using GT across domains? (2) How can such models be transferred and adapted to solve strategic interactions within the construction value chain in a manner that enables CE practices to emerge as equilibrium outcomes? These questions are driven by the need …

Carbonated Blast-Furnace Slag As Supplementary Cementitious Material: Phase Transition And Effect On Cement Hydration, Gao Deng, Nannan Zhang, Wenyu Liao, Yongjia He, Linnu Lu, Lingyu Chi, Hongyan Ma

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Blast-furnace slag, which contains high levels of CaO (and MgO), holds potential as a feedstock for CO₂ capture and storage. This study investigates the phase transitions occurring during the wet carbonation of ground granulated blast-furnace slag (GGBFS), characterizes the physical and chemical properties of carbonated GGBFS (CS), evaluates its pozzolanic reactivity, and examines the microstructure and performance of cement pastes blended with GGBFS or CS. The findings reveal that aragonite and calcite, the primary carbonation products, precipitate on the surface of GGBFS, hindering its dissolution and thereby reducing both the pozzolanic reactivity and the early strength of cement pastes. …

Optimal Error Estimates For A Semi-Discrete Finite Element Scheme Of Cahn-Hilliard-Navier-Stokes-Darcy Model, Yanyun Wu, Yali Gao, Xiaoming He, Yanping Lin

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we present a rigorous optimal error analysis for a semi-discrete finite element method of the coupled Cahn-Hilliard-Navier-Stokes-Darcy model. The optimal convergence order for the phase variable in the L^∞(0,T;H¹) norm and the velocity in the L^∞(0,T;L²) norm are proved with two key techniques. One key technique is establishing the discrete L²(0,T;H²)∩L²(0,T;L^∞) boundedness of the numerical solution for the phase variable to handle the nonlinear regional coupling terms. Another key technique adopts the inverse inequality and Ritz projection to bound the L …

Fourier Pseudospectral Methods For The Variable-Order Space Fractional Wave Equations, Yanzhi Zhang, Xiaofei Zhao, Shiping Zhou

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we propose Fourier pseudospectral methods to solve the variable-order space fractional wave equation and develop an accelerated matrix-free approach for its effective implementation. In constant-order cases, fast algorithms can be designed via the fast Fourier transforms (FFTs), and the computational cost at each time step is O(Nlog⁡N) with N the total number of spatial points. In variable-order cases, however, the spatial dependence in the power s(x) leads to the failure of inverse FFTs. While the direct matrix-vector multiplication approach becomes impractical due to excessive memory requirements. Hence, we propose an accelerated matrix-free approach for effective implementation in …

Wattage- And Composition-Dependent Ocular Surface Toxicity: An In Vitro Study On E-Cigarette Aerosol Exposure In Human Corneal Epithelial Cells, Tzu-Ling Lin

Masters Theses

As electronic cigarette consumption continues to escalate globally, its impact on non-respiratory mucosal surfaces, particularly the ocular surface, remains largely understudied. This study investigated the toxicological effects of e-cigarette aerosols using a human corneal epithelial cell (HCE-2) model. Our findings reveal that aerosol exposure induces a significant, dose-dependent reduction in cell viability, exacerbated by higher device wattage and specific flavor agents such as watermelon. Exposure was found to trigger intracellular oxidative stress and the activation of apoptotic pathways, leading to programmed cell death. Furthermore, the upregulation of proinflammatory cytokines suggests that vaping may predispose users to chronic inflammatory conditions of …

Investigating The Dynamic Rating Method: Effects Of Flood Wave Geometry On Discharge Estimation, Daniel James Read

Masters Theses

Rating curves are a vital tool to convert from observed stage to discharge in streamflow monitoring. Most gaging sites utilize a simple rating curve, which assumes a monotonic relationship between stage and discharge. In most cases, this assumption is valid; however, dynamic effects of flood waves often cause significant error in discharge estimation for mildly sloped streams. The dynamic rating method utilizes a numerical solution of the St. Venant Equations applied to time series stage data to compute discharge. Within this method, there is a flood wave parameter called the flood wave factor. The researchers designed a formal computational model …

Optimal Slotting In Hybrid Warehousing For Industry 4.0, Teng Yang

Masters Theses

In the era of Industry 4.0, the warehouse management system (WMS) employed by many firms prescribes hybrid storage, i.e., products with high turnover, called fast movers, are kept in random storage for a short time duration before being shifted to a dedicated storage area, while products with low turnover, called slow movers, remain in random storage. From dedicated storage, the products are dispatched to the customer. The challenge for managers is selecting the slot in dedicated storage to assign to each product while demand data change because of fluctuating market conditions; this problem is referred to as slotting in the …

Developing Discharge Estimation Algorithm Using Low-Cost Velocity Sensor And Machine Learning, Barkha Gautam

Masters Theses

Accurate river discharge estimation is essential for flood forecasting, water resources management, and hydraulic decision-making; however, continuous discharge records are unavailable at many river locations. Traditional stage-discharge rating curves are widely used but their reliability may decrease when channel conditions change or flow conditions vary rapidly. This study develops and evaluates Long Short-Term Memory (LSTM) models for discharge prediction using 15-minute time-series data from river monitoring stations in Missouri. Two model configurations, a baseline stage-only model and an enhanced stage-plus-velocity model, are developed and evaluated independently at two river sites to determine whether the inclusion of surface velocity improves discharge …

Calcium Based Carbon Negative Fillers And Additives: Effects On Hydration And Performance Of Low-Carbon Cement Systems, Smita Bhowmick Shithi

Masters Theses

Cement production is a major source of global CO₂ emissions creating an urgent need for carbon-negative fillers and functional additives that lower clinker use while maintaining cement performance. This thesis investigates the effects of organic mineral salts as fillers and additives on cement hydration, fresh properties, compressive strength and pore structure. In the first study, ordinary Portland cement (OPC) was partially replaced with calcium carbonate or calcium oxalate to enable a direct comparison under controlled particle size distribution (PSD). Rheology, flowability, hydration kinetics, phase evolution, mechanical performance and water absorption were evaluated. Calcium carbonate promoted early hydration through nucleation and …