Digital Commons Network^™

Inverse Problem In The Large Momentum Effective Theory Framework, Herve Dutrieux, Joe Karpie, Christopher J. Monahan, Kostas Orginos, Anatoly Radyushkin, David Richards, Savvas Zafeiropoulos

Physics Faculty Publications

One proposal to compute parton distributions from first principles is the large momentum effective theory (LaMET), which requires the Fourier transform of matrix elements computed nonperturbatively. Lattice quantum chromodynamics (QCD) provides calculations of these matrix elements over a finite range of Fourier harmonics that are often noisy or unreliable in the largest computed harmonics. It has been suggested that enforcing an exponential decay of the missing harmonics helps alleviate this issue. Using nonperturbative data, we show that the uncertainty introduced by this inverse problem in a realistic setup remains significant without very restrictive assumptions, and that the importance of the …

Search For The Y(2175) In The Photoproduction Cross Section Measurement Of 𝛾p → 𝜙𝜋⁺𝜋⁻P At Gluex, F. Afzal, M. Albrecht, M. Amaryan, S. Arrigo, V. Arroyave, A. Asaturyan, A. Austregesilo, Z. Baldwin, F. Barbosa, J. Barlow, E. Barriga, R. Barsotti, D. Barton, V. Baturin, V. V. Berdnikov, A. Berger, W. Boeglin, M. Boer, W. J. Briscoe, T. Britton, R. Brunner, S. Cao, C. Chen, E. Chudakov, G. Chung, P. L. Cole, O. Cortes, V. Crede, M. M. Dalton, D. Darulis, A. Deur, S. Dobbs, A. Dolgolenko, M. Dugger, R. Dzhygadlo, D. Ebersole, M. Edo, H. Egiyan, P. Eugenio, A. Fabrizi, C. Fanelli, S. Fang, M. Fritsch, S. Furletov, L. Gan, H. Gao, A. Gardner, A. Gasparian, D. I. Glazier, C. Gleason, K. Goetzen, B. Grube, J. Guo, A. Hamdi, J. Hernandez, K. Hernandez, N. D. Hoffman, D. Hornidge, G. M. Huber, P. Hurck, W. Imoehl, D. G. Ireland, M. M. Ito, I. Jaegle, N. S. Jarvis, T. Jeske, M. Jing, R. T. Jones, V. Mateev, M. Mccaughan, M. Mccracken, C. A. Meyer, R. Miskimen, R. E. Mitchell, P. Moran, F. Nerling, L. Ng, E. Nissen, S. Orešić, A. I. Ostrovidov, Z. Papandeou, L. Pentchev, K. J. Peters, L. Puthiya Veetil, S. Rakshit, J. Reinhold, A. Remington, J. Ritman, G. Rodriguez, K. Saldana, S. Schadmand, A. M. Schertz, K. Scheuer, A. Schmidt, R. A. Schumacher, J. Schwiening, M. Scott, N. Septian, P. Sharp, V. J. Shen, X. Shen, M. R. Shepherd, J. Sikes, H. Singh, A. Smith, E. S. Smith, A. Somov, J. R. Stevens, I. I. Strakovsky, B. Sumner, K. Suresh, V. V. Tarasov, S. Taylor, Y. Teymurazyan, A. Thiel, M. Thomson, T. Viducic, T. Whitlatch, Y. Wunderlich, B. Yu, J. Zarling, Z. Zhang, X. Zhou, B. Zihlmann, The Glue X Collaboration

Physics Faculty Publications

Based on 334 pb-¹ of photoproduction data collected with the GlueX detector at Jefferson Lab, we have measured for the first time the cross section of the exclusive reaction 𝛾 + p → φ(1020)π⁺π⁻p by reconstructing the final state K⁺K⁻π⁺π⁻p produced with a photon beam of energies between 8.0 and 11.6 GeV. Based on the measured differential cross section, we have performed a search for the strangeoniumlike exotic candidate Y(2175), recently renamed to φ(2170). This state has been reported by different e⁺e⁻ annihilation experiments and it is addressed here for the first time in a photoproduction experiment. We do not …

Shock-Wave Structure In A Monatomic Gas Mixture With Rydberg Atoms, Anna Markhotok

Physics Faculty Publications

The effect of atom size on the shock-wave structure in a binary monatomic gas mixture with Rydberg atoms has been investigated. The problem was solved numerically using the system of hydrodynamic equations in argon gas for the atom-size ratios between 2 and 100, T = 1500 K, and the density between 10¹⁷ and 10²⁰ m−³. It was found that the presence of larger-sized atoms in the mixture results in shock front splitting that is on the order of the mean free path for this component. The results could be of interest in supersonic plasma dynamics and in astrophysics, studying shock …

Geometry Of Almost-Conserved Quantities In Symplectic Maps: Approximate Invariants In Nonlinear Accelerator Systems, T. Zolkin, S. Nagaitsev, I. Morozov, S. Kladov

Physics Faculty Publications

We present a perturbative method for constructing approximate invariants of motion directly from the equations of discrete-time symplectic systems. This framework offers a natural nonlinear extension of the classic Courant-Snyder (CS) theory for systems with 1 degree of freedom—a foundational cornerstone in accelerator physics now spanning seven decades and historically focused on linear phenomena. The original CS formalism emerged under conditions where nonlinearities were weak, design goals favored linear motion, and analytical tools—such as the Kolmogorov-Arnold-Moser theory—had not yet been fully developed. While various normal-form methods have been proposed to treat near-integrable dynamics, the approach introduced here stands out for …

Quasielastic ³H⃗E (E⃗ , E′) Asymmetry In The Threshold Region With A Longitudinally Polarized Target, M. Nycz, W. Armstrong, T. Averett, C. Ayerbe Gayoso, X. Bai, J. Bane, S. Barcus, J. Benesch, H. Bhatt, D. Bhetuwal, D. Biswas, A. Camsonne, G. D. Cates, J-P. Chen, J. Chen, M. Chen, C. Cotton, M. M. Dalton, A. Deltuva, A. Deur, B. Dhital, B. Duran, S. C. Dusa, I. Fernando, E. Fuchey, B. R. Gamage, H. Gao, D. Gaskell, T. Gautam, N. Gauthier, J. Golak, J. -O. Hansen, F. Hauenstein, W. Henry, D. W. Higinbotham, G. M. Huber, C. Jantzi, S. Jia, K. Jin, M. Jones, S. Joosten, A. Karki, B. Karki, S. Katugampola, S. Kay, C. Keppel, E. King, P. King, W. Korsch, V. Kumar, R. Li, S. Li, W. Li, D. Mack, S. Malace, P. Markowitz, J. Matter, M. Mccaughan, Z-E. Meziani, R. Michaels, A. Mkrtchyan, C. Morean, V. Nelyubin, H. Nguyen, G. Niculescu, M. Niculescu, C. Peng, S. Premathilake, A. Puckett, A. Rathnayake, M. Rehfuss, P. Reimer, G. Riley, Y. Roblin, J. Roche, M. Roy, P. U. Sauer, S. Scopeta, M. Satnik, B. Sawatzky, S. Seeds, S. Širca, R. Skibiński, G. Smith, N. Sparveris, H. Szumila-Vance, A. Tadepalli, V. Tadevosyan, Y. Tian, W. A. Tobias, A. Usman, H. Voskanyan, H. Witala, S. Wood, B. Yale, C. Yero, A. Yoon, J. Zhang, Z. Zhao, X. Zheng, J. Zhou

Physics Faculty Publications

We report on the measurements of the double-spin asymmetry from electron-³He scattering in the threshold region of two- and three-body breakup of ³He for 4-momentum transfer values of 0.1 and 0.2 (GeV/c)². The measurement was done at Jefferson Lab using a polarized ³He target with its spin aligned parallel to the beam direction. This asymmetry is sensitive to a combination of spin-dependent response functions not previously measured and may highlight differences in two body forces, meson-exchange currents and final-state interactions. The results of this measurement serve as a test of our understanding of few-body systems. When compared with …

Supercharging Simulation-Based Inference For Bayesian Optimal Experimental Design, Samuel Klein, Willie Neiswanger, Daniel Ratner, Michael Kagan, Sean Gasiorowski

Physics Faculty Publications

Bayesian optimal experimental design (BOED) seeks to maximize the expected information gain (EIG) of experiments. This requires a likelihood estimate, which in many settings is intractable. Simulation-based inference (SBI) provides powerful tools for this regime. However, existing work explicitly connecting SBI and BOED is restricted to a single contrastive EIG bound. We show that the EIG admits multiple formulations which can directly leverage modern SBI density estimators, encompassing neural posterior, likelihood, and ratio estimation. Building on this perspective, we define a novel EIG estimator using neural likelihood estimation. Further, we identify optimization as a key bottleneck of gradient based EIG …

Exploring Causes Of Beam Loss At Cebaf, C. Matthews, J. Benesch, R. M. Bodenstein, B. Freeman, D. Moser, D. Turner, K. Price, J. Samari, B. Terzić

Physics Faculty Publications

At Jefferson Lab, the Continuous Electron Beam Accelerator (CEBAF) features a unique design with two linear accelerators and two arc sections allowing for multiple turns of the electron beam, as well as four experimental end stations. This topology leads to increased beam losses, especially in the spreader and recombiner regions connecting the arcs to the LINACs and in the extraction regions connecting the experimental end stations to the accelerator. These losses result in equipment activation and operational interruptions. Recent upgrades to the facility’s diagnostic systems, including the addition of xenon ion chambers, have provided higher-resolution data regarding these loss events. …

Real-Space Imaging Of The Electron-Pair Density Hole In Molecular Auger-Meitner Decay, Mats Simmermacher, Nathan Goff, Andres Moreno Carrascosa, Elke Fasshauer, Thomas Northey, Lingyu Ma, Haiwang Yong, Brian Stankus, Asami Odate, Xuan Xu, Wenpeng Du, Kyle Acheson, Joseph C. Cooper, Daniel Ratner, Mengning Liang, Ruaridh Forbes, Michael P. Minitti, Adam Kirrander, Peter M. Weber

Physics Faculty Publications

Electrons in matter can rearrange extremely quickly under external perturbations, underpinning subsequent structural and chemical transformations. Coulomb interactions between neighbouring electrons often shape this response, giving rise to correlated motion and strongly affecting the distribution of electrons in the system. Here we show that non-resonant hard X-ray scattering can directly access changes in the radial electron-pair density during the rapid rearrangement of core and valence electrons. We do this by studying sulfur hexafluoride molecules undergoing Auger–Meitner decay. We exploit a second-order interaction between the X-ray photons and the molecules to trigger and probe the decay dynamics with a single pulse, …

Reaching The Intrinsic Performance Limits Of Superconducting Nanowire Single-Photon Detectors Up To 0.1 Mm Wide, Kristen M. Parzuchowski, Eli Mueller, Bakhrom G. Oripov, Benedikt Hampel, Ravin A. Chowdhury, Sahil R. Patel, Daniel Kuznesof, Emma K. Batson, Ryan Morgenstern, Robert H. Hadfield, Varun B. Verma, Matthew D. Shaw, Jason P. Allmaras, Martina J. Stevens, Alex Gurevich, Adam N. Mccaughan

Physics Faculty Publications

Superconducting nanowire single-photon detectors combine high detection efficiency, low noise, and excellent timing resolution, making them a leading platform for photon-counting applications. However, despite decades of materials and fabrication research, detector performance has never been shown to match theoretical performance expectations. Here, we demonstrate in situ tuning of a detector from its typical, suboptimal operation, to a regime limited only by material quality, allowing the device to reach its intrinsic performance limit. Our approach is based on current-biased superconducting “rails” placed on either side of the detector that redistribute current across its width to achieve peak performance. This technique reduces …

Rf Design Progress Of The 197 Mhz Crab Cavity For Eic, B. Xiao, J. C. Brutus, A. Blednykh, Z. Conway, J. Cox, J. R. Delayen, S. U. De Silva, R. Fernandes, J. Guo, D. Holmes, N. Huque, G. Li, Z. Li, J. B. Mandel, S. Verdú-Andrés, G. Wang, Q. Wu, W. Xu

Physics Faculty Publications

The interaction region (IR) crab cavity system is a special RF system designed to compensate for the luminosity loss caused by the 25 mrad crossing angle at the interaction point (IP) of the Electron-Ion collider (EIC). The configuration includes six crab cavities in the Hadron (proton or ion) Storage Ring (HSR) - four operating at 197 MHz and two at 394 MHz - installed on each side of the IP, along with one 394 MHz crab cavity on each side of the IP in the Electron Storage Ring (ESR). This paper presents the recent progress in the RF design of …

First Measurement Of Polarized Spin-Density Matrix Elements And Differential Cross Sections Dσ/Dt In Ω Photoproduction Off The Proton For 2.7 < E𝛾 < 5.2 Gev Using Clas At Jefferson Lab, T. Hu, Z. Akbar, V. Crede, J. M. Laget, V. Mathieu, M. J. Amaryan, W. R. Armstrong, H. Atac, N. A. Baltzell, L. Barion, M. Battaglieri, I. Bedlinskiy, B. Benkel, F. Benmokhtar, A. Bianconi, L. Biondo, A. Biselli, M. Bondi, F. Bossu, S. Boiarinov, W. J. Briscoe, S. Bueltmann, D. Bulumulla, V. D. Burkert, R. Capobianco, D. S. Carman, J. C. Carvajal, A. Celentano, T. Chetry, G. Ciullo, G. Clash, P. L. Cole, M. Contalbrigo, G. Costantini, A. D'Angelo, N. Dashyan, R. De Vita, M. Defurne, A. Deur, S. Diehl, C. Djalali, R. Dupre, H. Egiyan, A. El Alaoui, L. El Fassi, L. Elouadrhiri, P. Eugenio, S. Fegan, A. Filippi, G. Gavalian, Y. Ghandilyan, G. P. Gilfoyle, F. X. Girod, A. A. Golubenko, G. Gosta, R. W. Gothe, K. A. Griffioen, M. Guidal, K. Hafidi, H. Hakobyan, M. Hattawy, T. B. Hayward, D. Heddle, A. Hobart, M. Holtrop, Y. Ilieva, D. G. Ireland, E. L. Isupov, D. Jenkins, H. S. Jo, K. Joo, S. Joosten, D. Keller, A. Khanal, M. Khandaker, A. Kim, W. Kim, F. J. Klein, V. Klimenko, A. Kripko, V. Kubarovsky, V. Lagerquist, L. Lanza, M. Leali, P. Lenisa, K. Livingston, I.J.D. Macgregor, D. Marchand, L. Marsicano, V. Mascagna, M. E. Mccracken, B. Mckinnon, Z. E. Meziani, S. Migliorati, R. G. Milner, T. Mineeva, M. Mirazita, V. Mokeev, C. Munoz Camacho, P. Nadel-Turonski, K. Neupane, J. Newton, S. Niccoai, M. Nicol, G. Niculescu, M. Osipenko, A. I. Ostrovidov, P. Pandey, M. Paolone, L. L. Pappalardo, R. Paremuzyan, E. Pasyuk, S. J. Paul, W. Phelps, N. Pilleux, O. Pogorelko, J. W. Price, Y. Prok, B. A. Raue, T. Reed, M. Ripani, J. Ritman, A. Rizzo, G. Rosner, F. Sabatié, C. Salgado, S. Schadmand, A. Schmidt, R. A. Schumacher, E. V. Shirokov, U. Shrestha, P. Simmerling, D. Sokhan, N. Sparveris, S. Stepanyan, I. I. Strakovsky, S. Strauch, R. Tyson, M. Ungaro, L. Venturelli, H. Voskanyan, A. Vossen, E. Voutier, D. P. Watts, X. Wei, M. H. Wood, B. Yale, M. Yurov, N. Zachariou, J. Zhang, The Clas Collaboration At Jefferson Laboratory

Physics Faculty Publications

We report on the differential cross sections dσ/dt, the unpolarized spin-density matrix elements ρ⁰₀₀, ρ⁰₁₋₁, Re ρ⁰₁₀, and the first extraction of the polarized elements Im ρ³₁₀, Im ρ³₁₋₁ for the reaction γp → pω using the CLAS spectrometer at Jefferson Laboratory. The ω mesons were detected in their dominant charged decay mode, ω→π+π−π⁰, and all t-dependent results are presented in a fine binning for incident photon energies between 2.73 and 5.16 GeV (corresponding to the center-of-mass energy range W ∈ [ 2.45, 3.25 ] GeV). All matrix elements are first measurements for −t>0.6 GeV². …

Efficient Dynamic And Momentum Aperture Optimization For Lattice Design Using Multipoint Bayesian Algorithm Execution, Z. Zhang, I. Agapov, S. Gasiorowski, T. Hellert, W. Neiswanger, X. Huang, D. Ratner

Physics Faculty Publications

We demonstrate that multipoint Bayesian algorithm execution (multipointBAX) can overcome fundamental computational challenges in storage ring design optimization. Dynamic aperture and momentum aperture optimization is a multipoint, multiobjective design task for storage rings, ultimately informing the flux of x-ray sources and luminosity of colliders. Current production black-box optimization methods require extensive particle-tracking simulations for each trial configuration; the high computational cost restricts the extent of the search to ~ 10³ configurations and therefore limits the quality of the final design. We remove this bottleneck using multipointBAX, which selects, simulates, and models each trial configuration at the single-particle level. We demonstrate …

Interpolation Between Sudakov And Bfkl Rapidity Evolutions For Tmd Factorization At Small X, Ian Balitsky

Physics Faculty Publications

Within the framework of rapidity-only small-x TMD factorization, the evolution with respect to the rapidity cutoff is initially governed by Sudakov double logarithms and subsequently by BFKL/BK single logarithms. The evolution equation proposed in this paper correctly reproduces both the Sudakov and BFKL limits, while providing a consistent interpolation between these two regimes.

Adaptive Electric Vehicle Routing And Charging With Deep Reinforcement Learning, Mandana Farhang Ghahfarokhi, Hyoshin Park, Venktesh Pandey, Gyugeun Yoon

Engineering Management & Systems Engineering Faculty Publications

As electric vehicles (EVs) gain popularity, efficient routing and charging solutions remain challenging due to time-dependent travel variability, sparse charging infrastructure, and heterogeneous user preferences. To address these challenges, this paper introduces a decision-support system that integrates three complementary methods: Temporal Multimodal Multivariate Learning (TMML) for real-time characterization of travel time uncertainty, Time-Dependent Shortest Path (TDSP) for reliability-aware route choice, and Deep Q-Network (DQN) reinforcement learning for adaptive charging decisions in sparse infrastructure environments. TMML updates link-level travel time distributions in real-time through Bayesian inference with cluster-based propagation, reducing uncertainties across the network. TDSP leverages these updated distributions to estimate …

A Hybrid Response Surface Methodology And Machine Learning Framework For Quantifying Effects Of Physicochemical Parameters On Pfas Distribution, Harsh V. Patel, Jazmin Green, Hyoshin Park, Stephanie Luster-Teasley Pass, Renzun Zhao

Engineering Management & Systems Engineering Faculty Publications

Predicting PFAS adsorption across diverse adsorbents and environmental matrices remains challenging because adsorbent physicochemical properties, PFAS molecular descriptors, and operational conditions simultaneously influence adsorption. This study develops and evaluates a unified hybrid modeling framework that integrates Response Surface Model (RSM) with machine-learning algorithms to quantify how six key variables, surface area, Log K_ow, pH_pzc, pK_a, log dose, and log-initial concentration, affect PFAS distribution coefficients (Log K_d). A data set of more than 1000 adsorption observations spanning 15 PFAS compounds, multiple adsorbent types, and a broad operational range was compiled and preprocessed using …

A. Vs. I In Ai: Is There A Threshold To "Engineered" Intelligence?, Joshit Mohanty

Engineering Management & Systems Engineering Faculty Publications

Despite artificial intelligence reshaping the world, its development generates uncertainties regarding future capabilities. AI simultaneously exists as an artifact of engineering design and as autonomous intelligence, creating an observer-participant feedback loop. This paper proposes that embodied AI faces a bandwidth-limited intelligence threshold T_h that it arises from B = min(C_sens,C_Act). However, Shannon capacity measures bits while intelligence operates on concepts, necessitating a dual-channel model separating physical bandwidth B_io from representational capacity B_rep. Intelligence emerges as multi-dimensional rather than scalar, with components exhibiting different bandwidth dependencies. Surpassing T_h requires either new sensing methods expanding B, enhanced representational frameworks, or reconceptualization within …

Technological Interventions For Reducing Climate Change Impacts On Health: An Overview Of Future Possibilities, Sujatha Alla, Vijay Kumar Chattu, Bawa Singh

Engineering Management & Systems Engineering Faculty Publications

Globally, over five million deaths annually are attributed to extreme weather events exacerbated by climate change, such as heatwaves, hurricanes, wildfires, droughts, and floods, which create health crises and economic losses. The 2015 Paris Declaration emphasized climate technology mechanisms, including research and development, to enhance resilience and reduce greenhouse gas emissions. Biotechnological advancements have mitigated about 20% of economic losses since the 1960s, highlighting technology’s potential to address climate-induced health risks.

Information-Theoretic Path Planning For Safe And Adaptive Nanobot Drug Delivery, Nagesh Bheesetty, John H. Park, Sujatha Alla, Winifred M. Lo, Aditya Nimmagadda, Mohamadmahdi Samandari, Jae H. Lee

Engineering Management & Systems Engineering Faculty Publications

We present a safe and efficient path planning framework for nanobot navigation in complex vascular networks, enabling precise drug delivery to hard-to-reach tumor regions such as those found in the lungs. The proposed method introduces a safe and efficient path planning strategy that integrates a utility-based function to balance two key goals: exploring uncertain areas to gather valuable information and avoiding hazardous regions to ensure safe and reliable delivery. We evaluate a simplified swarm-based nanobot navigation scenario using synthetic vascular maps that mimic the structural complexity of lung tumor blood vessels. Environmental uncertainty is modeled from vessel topology, blockage density, …

Winning Without War In Africa: The Will To Fight, Strategic Openness, And Great Power Rivalry, Chick Edmond

Political Science & Geography Faculty Publications

This research assesses how “will to fight” impacts the ability of African nations to achieve strategic success during periods of increased competition between powerful nations (great powers) and increasing global and transnational threat. Unlike most studies on strategy which focus on the physical assets (material capacity), institutions (governance), and the support received from other nations (external assistance) a new study provides evidence that the will to fight of an African nation has a significant impact on its ability to sustain its deterrent capability, remain strategically open, and resist coercion. Using case studies of four regions (the Sahel, Mali, Cameroon, and …

The Evolving Beijing Consensus: Chinese Communist Party Political Control And Economic Trade Offs, Ian Murphy

Political Science & Geography Faculty Publications

China’s rapid economic rise and unique development trajectory have long been the subject of scholarly debate, often framed through the concept of the “Beijing Consensus” as an alternative to the Washington Consensus. While initial conceptualizations highlight innovation, sustainability, and national sovereignty, later analyses highlighted elements like state capitalism and authoritarianism, particularly in the wake of the 2008 Global Financial Crisis. This paper argues that the Beijing Consensus is undergoing a significant evolution under Chairman Xi Jinping, increasingly prioritizing the Chinese Communist Party’s political security, regime stability, and ideological control at the expense of economic growth. This marks a notable departure …

Integrating Self-Organizing Maps And Explainable Artificial Intelligence To Unravel Surface Water-Groundwater Hydrochemical Evolution And Drinking-Water Suitability Controls In A Data-Limited Arid Basin, Hui Tong, Ruizhong Gao, Yinlong Wang, Xixi Wang, Limin Duan, Guoqiang Wang

Civil & Environmental Engineering Faculty Publications

Study region

The Dahei River Basin, located in the semi-arid northern region of China's Great Bend of the Yellow River.

Study focus

This study integrates hydrochemical characterization, stable hydrogen-oxygen isotopes, Self-Organizing Maps (SOM), the entropy-weighted water quality index (EWQI), and explainable ensemble learning (XGBoost-TreeSHAP) to investigate surface water-groundwater evolutionary patterns and identify key hydrochemical contributors to drinking-water suitability in the Dahei River Basin.

New hydrological insights for the region

Waters in the basin are predominantly weakly alkaline and are characterized by HCO₃^--Ca-Mg and HCO₃^--Na facies, indicating the combined effects of carbonate weathering and cation exchange, 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 …

Markov Chain Wave Generative Adversarial Network For Bee Bioacoustic Signal Synthesis, Kumudu Samarappuli, Iman Ardekani, Mahsa Mohaghegh, Abdolhossein Sarrafzadeh

Electrical & Computer Engineering Faculty Publications

This paper presents a framework for synthesizing bee bioacoustic signals associated with hive events. While existing approaches like WaveGAN have shown promise in audio generation, they often fail to preserve the subtle temporal and spectral features of bioacoustic signals critical for event-specific classification. The proposed method, MCWaveGAN, extends WaveGAN with a Markov Chain refinement stage, producing synthetic signals that more closely match the distribution of real bioacoustic data. Experimental results show that this method captures signal characteristics more effectively than WaveGAN alone. Furthermore, when integrated into a classifier, synthesized signals improved hive status prediction accuracy. These results highlight the potential …

Microfluidic Encapsulation Of Sorafenib-Loaded Zif-8 Nanoparticles In Ph-Responsive Alginate Microparticles For Oral Chemotherapy Of Hepatocellular Carcinoma, Mojdeh Mirshafiei, Zahra Mahmoudi, Mehdi Mehrpouya, Mahdi Mahmoudi, Masoud Rezaeian, Mona Navaei-Nigjeh, Zahra Katoli, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related mortality. Sorafenib is the current first-line oral therapy; however, its therapeutic efficacy is limited by poor aqueous solubility, low bioavailability, and gastrointestinal instability. This study aimed to develop a pH-responsive nano-in-microparticle delivery system using a single-step droplet-based microfluidic process to protect sorafenib in the gastric environment and achieve controlled release for enhanced oral chemotherapy. Sorafenib-loaded ZIF-8 nanoparticles (SZ NPs) were synthesized and characterized by scanning electron microscopy (SEM), Fourier-transform infrared (FTIR) spectroscopy, Energy-dispersive X-ray (EDX) spectroscopy, and X-ray diffraction (XRD), exhibiting a mean diameter of about 72 nm and …

Mtl_Tx: A Multi-Task Transformer Model For Improved Radiation Time-Series Estimation, Hongfang Zhang, Adam Stavola, Hal Ferguson, Bence Budavari, Hongyi Wu, Chiman Kwan, Jiang Li

Electrical & Computer Engineering Faculty Publications

Controlling radiation doses at potential radioactive facilities is critical to ensuring the safety of both personnel and the public. At the Thomas Jefferson National Accelerator Facility (JLab), multiple sensors are deployed around the three experimental halls to monitor key parameters, including single-beam current, energy levels, current leakage, and radiation values during accelerator operations. In this study, we developed a Multi-task Transformer model, MTL_TX, to accurately estimate radiation doses at sensor locations based on historical data, with the aim of enhancing safety in accelerator facilities and surrounding public areas. To improve estimation accuracy, we integrated two innovative components into the proposed …

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 …

Qubit Lattice Algorithm Simulations Of The Scattering Of A Bounded Two Dimensional Electromagnetic Pulse From The Infinite Planar Dielectric Interface, Min Soe, George Vahala, Linda Vahala, Efstratios Koukoutsis, Abhay K. Ram, Kyriakos Hizanidis

Electrical & Computer Engineering Faculty Publications

Qubit lattice algorithm (QLA) simulations are performed for a two-dimensional spatially bounded pulse propagating onto a plane interface between two dielectric slabs. QLA is an initial value scheme that consists of a sequence of unitary collision and streaming operators, with appropriate potential operators, that recover Maxwell equations in inhomogeneous dielectric media to the second order in the lattice discreteness. For the case of total internal reflection, there is transient energy transfer into the second medium due to the evanescent fields as the Poynting unit vector of the pulse is rotated from its incident to reflected direction. Because of the finite …

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 …

Healthcare Digital Twins: A Methodological Literature Review On Integrating Iot And Ai For Personalized Medicine And Predictive Care, Sara Shahnazinia, Mahsa Tavasoli, Abdolhossein Sarrafzadeh, Ali Karimoddini

Electrical & Computer Engineering Faculty Publications

Digital Twin (DT) technology has the potential to revolutionize healthcare delivery and enhance patient outcomes through personalized and precision medicine, simulation models for operations and interventions, and drug discovery. However, successful implementation of DTs in Internet of Things (IoT) and artificial intelligence (AI) healthcare is contingent upon addressing key challenges such as privacy, ethics, and robust data security. This paper presents a methodological literature review of DT applications in healthcare, systematically analyzing the current state of research, key enabling technologies, and implementation challenges. The review summarizes DT categorization approaches (application-based, technology-based, and real-time function-based); delineates core DT components such as …