Physical Sciences and Mathematics Commons^™

Time-Marching Quantum Algorithm For Simulation Of Nonlinear Lorenz Dynamics, Efstratios Koukoutsis, George Vahala, Min Soe, Kyriakos Hizanidis, Linda Vahala, Abhay K. Ram

Electrical & Computer Engineering Faculty Publications

Simulating nonlinear classical dynamics on a quantum computer is an inherently challenging task due to the linear operator formulation of quantum mechanics. In this work, we provide a systematic approach to alleviate this difficulty by developing an explicit quantum algorithm that implements the time evolution of a second-order time-discretized version of the Lorenz model. The Lorenz model is a celebrated system of nonlinear ordinary differential equations that has been extensively studied in the contexts of climate science, fluid dynamics, and chaos theory. Our algorithm possesses a recursive structure and requires only a linear number of copies of the initial state …

A Spine-Specific Lexicon For The Sentiment Analysis Of Interviews With Adult Spinal Deformity Patients Correlate With Sf-36, Sf-36, And Odi Scores: A Pilot Study Of 25 Patients, Ross Gore, Michael M. Safaee, Christopher J. Lynch, Christopher P. Ames

VMASC Publications

Classic health-related quality of life (HRQOL) metrics are cumbersome, time-intensive, and subject to biases based on the patient’s native language, educational level, and cultural values. Natural language processing (NLP) converts text into quantitative metrics. Sentiment analysis enables subject matter experts to construct domain-specific lexicons that assign a value of either negative (−1) or positive (1) to certain words. The growth of telehealth provides opportunities to apply sentiment analysis to transcripts of adult spinal deformity patients’ visits to derive a novel and less biased HRQOL metric. In this study, we demonstrate the feasibility of constructing a spine-specific lexicon for sentiment analysis …

Are We Ready For Synchronous Conceptual Modeling In Augmented Reality? A Usability Study On Causal Maps With Hololens 2, Anish Shrestha, Philippe J. Giabbanelli

VMASC Publications

(1) Background: Participatory modeling requires combining individual views to create a shared conceptual model. While remote collaboration tools have enabled synchronous online modeling, they are limited to desktop settings. Augmented reality (AR) offers a new approach by potentially providing the sense of presence found in physical collaboration, which may better support participants in achieving the sense of presence found in physical locations, thus supporting them in negotiating meaning and building a shared model. (2) Methods: Building on prior works that developed technology, we performed a usability study with pairs of modelers to examine their ability at performing key conceptual modeling …

Integrated Valuation Of The Ecological, Social And Economic Benefits Provided By A Multifunctional Nature-Based Solution, Laura Costadone, Shan Zhang

ODU Articles

Nature-based Solutions (NbS) offer multifunctional approaches to address climate change and environmental challenges, providing a sustainable alternative to traditional gray infrastructure. Despite their promise, widespread adoption remains limited, in part due to an incomplete understanding of their full costs and benefits relative to conventional infrastructure. Traditional benefit–cost analyses often overlook non-monetized benefits and the interconnected ecosystem services provided by NbS. This study introduces a methodological approach to quantify both the physical and monetary value of ecosystem services and co-benefits delivered by an NbS project. We applied an integrated valuation framework to a case study in Virginia Beach, VA, USA, where …

Match Accuracy Of Burned Teeth: A Pilot Study Of Allied Dental Professionals, Brenda T. Bradshaw, Marsha A. Voelker, Samantha C. Vest, Sinjini Sikdar

Dental Hygiene Faculty Publications

Purpose: The purpose of this pilot study was to assess allied dental professionals' match accuracy of burned teeth; a skill required by disaster victim identification (DVI) team members.

Methods: This cross-sectional study used a convenience sample of registered dental hygienists (RDH) (n=15) and dental assistants (DA) (n=15) to assess their match accuracy of burned teeth with simulated antemortem (AM) and postmortem (PM) images. Fifteen human teeth were heated at 400°C for 15 minutes. Prior to and following heat alteration, each tooth was photographed and radiographed. Images were presented to participants in randomized order, and they were instructed to correctly match …

Clinician Perspectives On Virtual Reality Use In Physical Therapy Practice In The United States, Danielle T. Felsberg, Jared T. Mcguirt, Scott E. Ross, Louisa D. Raisbeck, Charlend K. Howard, Christopher K. Rhea

Rehabilitation Sciences Faculty Publications

The primary goal of physical rehabilitation is to assess movement impairments and restore function to improve overall quality of life. Virtual reality (VR) may provide the optimal environment to promote these goals due to its motivating and modifiable nature which can be difficult to accomplish through traditional real-world therapeutic methods. Current research of VR for rehabilitation has demonstrated that VR interventions can produce clinically meaningful change in motor outcomes. Despite this, adoption and usage of VR by physical therapy professionals is unclear due to the limited research in this area. Thus, the purpose of this study was to identify the …

Exploring Research And Tools In Ai Security: A Systematic Mapping Study, Sidhant Narula, Mohammad Ghasemigol, Javier Carnerero-Cano, Amanda Minnich, Emil Lupu, Daniel Takabi

School of Cybersecurity Faculty Publications

With the pervasive integration of artificial intelligence (AI) in various facets of modern technology, the importance of AI security has been thrust into the spotlight. The field is rapidly evolving, with new challenges and solutions emerging at a swift pace. However, the breadth and depth of AI security research have not been comprehensively mapped in recent times, presenting a crucial need for an extensive review and synthesis of existing literature. Given the increasing reliance on AI in critical domains such as healthcare, finance, and national security, ensuring the resilience and trustworthiness of these systems is imperative. This survey fulfills the …

Artificial Intelligence And Digital Technologies In Finance: A Comprehensive Review, Soudeh Pazouki, Mohamad Jamshidi, Mirarmia Jalali, Arya Tafreshi

Finance Faculty Publications

This study explores the transformative impact of artificial intelligence (AI) and digital technologies on the financial technology (FinTech) industry, highlighting their role in fostering business growth, operational efficiency, and enhanced customer engagement. AI-driven strategies have unlocked new avenues for streamlining workflows, boosting productivity, and expanding financial inclusion by reaching underrepresented populations. However, these advancements also pose challenges, including navigating complex regulatory frameworks and adapting to the rapidly evolving technological landscape. This paper delves into the macroeconomic effects of AI, examining its influence on labor markets, consumer behavior, and organizational success. Furthermore, the paper discusses blockchain applications and their potential to …

Heterotrophy Of Particulate Organic Matter Subsidies Contributes To Divergent Bleaching Responses In Tropical Sclaractinian Corals, Connor R. Love, Kelly E. Speare, Michael D. Fox, Veronica Z. Radice, Kelton W. Mcmahon, Gretchen E. Hofmann,, David L. Valentine, Marie E. Strader

Biological Sciences Faculty Publications

Heterotrophic feeding on plankton and particulate organic matter (POM) by tropical Scleractinian corals is known to aid in the resistance and recovery from thermally induced bleaching. However, the relative importance of heterotrophy in promoting bleaching resistance and recovery is likely to vary based on ecological context and the severity of heat stress. In 2019, the Pacific Island of Mo'orea experienced mass coral mortality during a widespread marine heatwave. Many Acropora hyacinthus colonies on the shallow reef slope (5 m) were resistant to bleaching, while colonies on the deeper fore reef (14 m) often bleached and subsequently recovered, despite similar thermal …

Analyzing Microbial Communities In Porites Astreoides, Sanaa Caldwell, Katie Parker, Daniel Barshis

Biological Sciences Faculty Publications

Coral reefs are vital marine ecosystems that support many different species and ecosystem services through protecting coastlines from storms and erosion, providing raw materials for medication, and facilitating diversity amongst marine species. Anthropogenic climate change is causing ocean temperatures to exceed the range of coral thermal tolerance resulting in more coral bleaching events globally. However, some corals have the capacity to withstand high temperatures through different thermal tolerance strategies. A balanced microbial community plays a critical role in coral health and recent studies have indicated that a balanced microbiome is associated with temperature-stress tolerant corals. Yet, there is a severe …

A Blueprint To Greener Shorelines: Advancing The Effectiveness, Sustainability, And Widespread Adoption Of Coastal Nature-Based Solutions Through Transdisciplinary Research, Taylor M. Sloey, Sierra Hildebrandt, Rebecca L. Morris, Matthew V. Bilskie, Aaron Bland, David Bushek, Gabriella Dipetto, Daniel Elefant, Vincent Encomio, Ramin Familkhalili, Christine Hladik, Danielle Kreeger, Avery B. Paxton, Cindy M. Palinkas, Latina Steele, Andrew Scheld, Daisuke Taira, Jason D. Toft, Armando J. Ubeda, Christine Whitcraft, Donna Marie Bilkovic

Biological Sciences Faculty Publications

Coastal nature-based solutions (NbS) have emerged as powerful tools to enhance sustainable development and ecological restoration goals. As a rapidly growing field spanning across social, political, ecological, economic, and engineering disciplines, it is critical that researchers working in coastal NbS regularly attempt to identify emerging focal areas for scientific inquiry. Following the 27th Biennial meeting of the Coastal and Estuarine Research Federation, we provide a transdisciplinary perspective (including biologists, engineers, oceanographers, geoscientists, economists, and facilitators of workforce training programs) of pertinent research questions that, if answered, will advance the effectiveness, sustainability, and widespread adoption of coastal NbS. These suggestions for …

High Temporal Resolution Gene Expression Analysis Of Acute Heat Stress Response In Acropora Cervicornis And Porites Astreoides, Katherine Parker, Nicolas Evensen, Iliana Baums, Daniel Barshis

Biological Sciences Faculty Publications

Widespread coral bleaching and mortality events are becoming increasingly frequent due to rising ocean temperatures, though certain coral species and populations have displayed higher tolerance to elevated emperatures than others. As such, it is of high research priority to identify thermally tolerant coral populations for research and conservation and assess the biological mechanisms allowing these populations to survive exposure to higher temperatures. This research utilized the Coral Bleaching Automated Stress System (CBASS), a portable experimental aquaria system with precise temperature manipulation, to assess the thermal thresholds and heat stress response of two coral species from Summerland Key, FL, USA. Seven …

The Pluralistic Natural Capital Values Of A Tropical City, Adrienne Grêt-Regamey, Justine Saunders, Peter Edwards, Daniel Richards, Jahson I. Alemu, Natasha Bhatia, Roman Carrasco, Zuzana Drillet, Tze Kwan Fung, Yan Feng Leon Gaw, Wanggi Jaung, Andrea Law, Rachel Ai Ting Leong, Aikeen Youu Ming Lim, Mahyar Masoudi, Yudhishthra Nathan, Rachel Rui Ying Oh, Wen Ting Ooi, Fairul Edros Ahmad Shaikh Shaikh, Xiao Ping Song, Claudia L.Y. Tan, Puay Yok Tan, Sergio Wicki, Lynn-Wei Wong, Yanyun Yan, Erik Yando, Alex Thiam Koon Yee, Jingyuan Zhang, Daniel A. Friess

Biological Sciences Faculty Publications

Nature in cities is essential for human well-being. Quantifying and valuing the goods and services provided by nature to city dwellers is missing in tropical contexts. Yet, as cities worldwide face similar challenges, understanding the services provided by tropical urban ecosystems becomes imperative for effective management. Here, we present the first Natural Capital Assessment of a tropical city, unveiling three critical insights. Firstly, we demonstrate the vital reliance of a developed tropical city on nature, particularly for climate change mitigation through regulating services. Secondly, we identify intact natural areas as Singapore’s most valuable assets, stressing the significance of the quality …

Low Salinities Impair Heat Tolerance And Alter Reproductive Traits With No Implications For Survival In A Marine Annelid From Coastal Habitats, Gabrielle Newton, Gloria Massamba-N'Siala

Biological Sciences Faculty Publications

Climate change is expected to intensify salinity and temperature fluctuations in estuarine and coastal habitats. However, the impact of salinity variation on ectotherms’ thermal tolerance remains underexplored, limiting our understanding of the interplay between these stressors. This study investigated salinity-dependent changes in life history traits (survival, growth rate, fecundity, and egg size) over a 33-day exposure to a salinity gradient (12, 17, 22, 27, 32, 35, 40, 45, 50) in the marine annelid Ophryotrocha labronica. Individuals that survived the salinity treatments were assessed for their upper and lower thermal tolerance limits. Female individuals, the target of the study, exhibited …

Investigations Of Conjugate Heat Transfer And Fluid Flow In Partitioned Porous Cavity Using Darcy-Forchheimer Model: Finite Element-Based Computations, Nasir Yasin, Shafee Ahmad, Muhammad Umair, Zahir Shah, Narcisa Vrinceanu, Ghadah Alhawael

Mathematics & Statistics Faculty Publications

The conjugate heat transfer and fluid flow has vast applications in thermal engineering, particularly for cooling in thermal devices, and automobile engines. This study investigates conjugate heat transfer in 2D enclosures, featuring thin solid fins attached to a porous bottom wall. The porous medium is considered isotropic and homogeneous by the Darcy-Forchheimer model, with fluid phases in local thermal equilibrium. The boundary conditions at the porous fluid interface ensure continuity of the velocities, stresses, temperature, and heat flux. The phenomenon is mathematically modelled by obtaining a set of partial differential equations. The finite element method (FEM) is used to perform …

Editorial: Ai's Impact On Higher Education: Transforming Research, Teaching, And Learning, Alyse Jordan, Ashley L. Dockens, Natalia Anastasia Pierson, Xinyue Ren

STEMPS Faculty Publications

[Introduction] This Research Topic provides a comprehensive examination of how artificial intelligence (AI) is transforming higher education. The collected studies reveal several interconnected themes that illuminate both the opportunities and challenges of AI integration in academic settings. This editorial summarizes these themes and articulates their significance for the future of higher education.

Integrating Satellite-Based Precipitation Analysis: A Case Study In Norfolk, Virginia, Imiya M. Chathuranika, Dalya Ismael

Engineering Technology Faculty Publications

In many developing cities, the scarcity of adequate observed precipitation stations, due to constraints such as limited space, urban growth, and maintenance challenges, compromises data reliability. This study explores the use of satellite-based precipitation products (SbPPs) as a solution to supplement missing data over the long term, thereby enabling more accurate environmental analysis and decision-making. Specifically, the effectiveness of SbPPs in Norfolk, Virginia, is assessed by comparing them with observed precipitation data from Norfolk International Airport (NIA) using common bias adjustment methods. The study applies three different methods to correct biases caused by sensor limitations and calibration discrepancies and then …

A Comprehensive Academic And Industrial Survey Of Blockchain Technology For The Energy Sector Using Fuzzy Einstein Decision-Making, Umit Cali, Annabelle Lee, Barry Hayes, Claudio Lima, D. Jonathan Sebastian-Cardenas, David Flynn, Emre Kantar, Farrokh Rahimi, Kaung Si Thu, Marco Pasetti, Marthe Fogstad Dynge, Merlinda Andoni, Muhammet Deveci, Murat Kuzlu, Raquel Alanso, Kim-Kwang Raymond Choo, Sambeet Mishra, Shammya Shananda Saha, Sonam Norbu, Srinikhil Gourisetti, Ugur Halden, Vahid Hosseinezhad, Valentin Robu

Engineering Technology Faculty Publications

The global energy sector is undergoing a significant transformation driven by decarbonization and digitalization, leading to the emergence of Distributed Ledger Technology (DLT) — particularly blockchain — as a promising tool for enhancing transparency, security, and efficiency in modern power systems. This study aims to provide a comprehensive academic and industrial survey of blockchain applications in the energy sector and develop a robust decision-making framework to identify and prioritize the most promising real-world use cases based on multidisciplinary criteria. A three-stage methodology was adopted: (i) a literature and market review encompassing over 300 academic publications and commercial blockchain initiatives in …

Integrating Sustainable Practices Into Lean Engineering: Applying The Engineering For One Planet Framework In Manufacturing Engineering Technology Education, Dalya Ismael, Vukica M. Jovanovic, Murat Kuzlu, Charles Lowe, Lisa Bosman

Engineering Technology Faculty Publications

A growing number of manufacturers are recognizing significant financial and environmental benefits from adopting sustainable business practices. Sustainable manufacturing refers to the production of goods through processes that are economically sound, minimize environmental impact, and conserve energy and natural resources. Lean engineering, a comprehensive approach to decision-making and leadership within manufacturing organizations, has proven effective in driving sustainable practices. Key strategies include waste elimination, value identification, value stream mapping, flow creation, pull system establishment, and continuous improvement. Both lean manufacturing and sustainability share a common focus on minimizing waste. Lean principles address seven types of waste: transport, inventory, motion, waiting, …

Using Quanser Platform To Introduce Engineering Technology Students To Autonomous Vehicles, Otilia Popescu, Logan Beaver, Murat Kuzlu, Krishnanand Kaipa

Engineering Technology Faculty Publications

The area of autonomous vehicles is not new, but the latest advances in various technologies gave it a new boost in the last decade and it keeps growing in interest. However, undergraduate curricula rarely include courses specific to this area, which is considered mostly an interdisciplinary graduate field. While various programs introduce students to the background needed to understand and approach the field, specific work on autonomous vehicle projects is left for extra curriculum activities or student clubs, and eventually for senior (capstone) projects. This paper presents the work of a team of electrical engineering technology students on an autonomous …

5g-Enabled Iot Gateway For Educational Purposes, Murat Kuzlu

Engineering Technology Faculty Publications

The project aims to develop and implement a 5G-IoT gateway for efficient management and interconnection of IoT devices through advanced sensing and communication technologies. Sensing technologies encompass modern approaches for detecting and measuring physical properties with high accuracy across manufacturing, smart grids, healthcare, smart cities, and other domains. Communication technologies represent the latest developments in high-speed data transmission, offering enhanced reliability and network capacity. This 5G-IoT gateway functions as an educational platform, providing students and educators with hands-on experience in emerging technologies. The system creates opportunities for practical learning and research in telecommunication technologies by enabling direct engagement with 5G …

Maximum Trimmed Likelihood Estimation For Discrete Multivariate Vasicek Processes, Thomas M. Fullerton Jr., Michael Pokojovy, Andrews T. Anum, Ebenezer Nkum

Mathematics & Statistics Faculty Publications

The multivariate Vasicek model is commonly used to capture mean-reverting dynamics typical for short rates, asset price stochastic log-volatilities, etc. Reparametrizing the discretized problem as a VAR(1) model, the parameters are oftentimes estimated using the multivariate least squares (MLS) method, which can be susceptible to outliers. To account for potential model violations, a maximum trimmed likelihood estimation (MTLE) approach is utilized to derive a system of nonlinear estimating equations, and an iterative procedure is developed to solve the latter. In addition to robustness, our new technique allows for reliable recovery of the long-term mean, unlike existing methodologies. A set of …

Is It Getting Better? An Evaluation Of Two Successive Generations Of Chatgpt In Answering Specialized Vascular Surgery Questions, Dongjin Suh, Quang Le, Leana Dogbe, Kedar Lavingia, Michael Amendola

Department Surgery Faculty Publications

Purpose: Large language models (LLMs) can generate clinically relevant text; however, their performance in highly specialized medical domains remains uncertain. This study evaluated ChatGPT-3.5 and ChatGPT-4 (OpenAI) using vascular surgery board–style questions from the Vascular Education and Self-Assessment Program, version 4 (VESAP4) and compared the two public model versions (June and November 2023).

Materials and Methods: All non-image VESAP4 questions (n=384) were presented independently three times to each model version (ChatGPT-3.5 June/November; ChatGPT-4, June/November). Outcomes included accuracy (proportion correct), consistency (same option letter across all three attempts and “consistently correct”), explanation length (word count), and modes of failure classified for …

A Comprehensive Exploration Of 6g Wireless Communication Technologies, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Md. Shahriar Uzzal, H. M. Dipu Kabir

Electrical & Computer Engineering Faculty Publications

As the telecommunications landscape braces for the post-5G era, this paper embarks on delineating the foundational pillars and pioneering visions that define the trajectory toward 6G wireless communication systems. Recognizing the insatiable demand for higher data rates, enhanced connectivity, and broader network coverage, we unravel the evolution from the existing 5G infrastructure to the nascent 6G framework, setting the stage for transformative advancements anticipated in the 2030s. Our discourse navigates through the intricate architecture of 6G, highlighting the paradigm shifts toward superconvergence, non-IP-based networking protocols, and information-centric networks, all underpinned by a robust 360-degree cybersecurity and privacy-by-engineering design. Delving into …

Differentiating Opioid Use Disorder From Healthy Controls Via Ml Analysis Of Rs-Fmri Networks, Ahmed Temtam, Megan A. Witherow, Liangsuo Ma, M. Shibly Sadique, F. Gerard Moeller, C. Kenneth, Dianne Wright, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Objectives/Goals: This work aims to identify functional brain networks that differentiate opioid use disorder (OUD) subjects from healthy controls (HC) using machine learning (ML) analysis of resting-state fMRI (rs-fMRI). We investigate the default mode network (DMN), salience network (SN), and executive control network (ECN), as well as demographic features. Methods/Study Population: This work uses high-resolution rs-fMRI data from a National Institute on Drug Abuse study (IRB #HM20023630) with 31 OUD and 45 HC subjects. We extract rs-fMRI blood oxygenation level-dependent (BOLD) features from the DMN, SN, and ECN. The Boruta ML algorithm identifies statistically significant features and brain activity mapping …

Check Your Data Before You Wreck Your Model: The Impact Of Careless Responding On Substance Use Data Quality, Abby L. Braitman, Anna M. Petrey, Jennifer L. Shipley, Rachel Ayala Guzman, Emily Renzoni, Alison Looby, Adrian J. Bravo

Psychology Faculty Publications

Background: The accuracy of survey responses is a concern in research data quality, especially in college student samples. However, examination of the impact of removing participants from analyses who respond inaccurately or carelessly is warranted given the potential for loss of information or sample diversity. This study aimed to understand if careless responding varies across a number of demographic indices, substance use behaviors, and the timing of survey completion.

Method: College students (N = 5809; 70.7% female; 75.7% White, non-Hispanic) enrolled in psychology classes from six universities completed an online survey assessing a variety of demographic and substance use-related information, …

Human Perception Of Ai Capabilities At Classifying Perturbed Roadway Signs, Katherine R. Garcia, Jing Chen, Yanru Xiao, Scott Mishler, Cong Wang, Bin Hu

Psychology Faculty Publications

Artificial Intelligence (AI) is crucial to numerous functions required for driving automation systems, including the computer vision techniques used to detect the roadway environment and make real-time decisions. However, the images used as inputs to the AI system may be maliciously perturbed, or manipulated, causing the AI system to make an incorrect classification. In this study, we examined humans’ perception of the AI’s computer vision capability of classifying various road sign images, including the original images, images with two different types of malicious attacks, and images that are scrambled randomly at the pixel level. Our results showed that participants rated …

Am I As Effective At Identifying Emotions As Artificial Intelligence? A Comparative Study Of Emotional Recognition, Traci R. Grove, Alexandra T. Lucas, Maryann Martin, Cathleen M. Deckers, Lulu Sherif Mahmood, Nicole Danaher-Garcia, Mark W. Scerbo, Suzan Kardong-Edgren, Janice C. Palaganas

Psychology Faculty Publications

Background

Learning conversations, or dialogues aimed at deepening understanding and reflection, are deeply influenced by emotions. Effective communication is influenced by emotional intelligence - the ability to recognize, understand, and manage both one’s own and others’ emotions. While advances in artificial intelligence (AI) offer new tools for emotion recognition, these technologies still struggle with accurately interpreting subtle and culturally diverse emotional expressions, sparking debate about their reliability and effectiveness. This article provides a comparative analysis of human versus AI recognition of emotions during an end-of-course reflective learning conversation.

Methods

Emotions during a structured post-conference debriefing were analyzed and coded by …

The Interacting Roles Of Attention Allocation And Trust In Highly Automated Aam Environments, Yusuke Yamani

Psychology Faculty Publications

[First slide]

Mechanisms of attentive visual processing

• Attention control
• Visual search
• Eye movement
• Aging and individual differences

Limits of human performance in applied environment

• Complex displays
• Machine operation
• Surface transportation
• Advanced air mobility
• Nuclear operation

Methods to ameliorate human cognitive performance

• Human-machine interface
• Human autonomy/AI teaming
• Human-systems integration
• Training

Trustworthiness And Trust: Identifying Factors That Drive Successful Human-Ai Interaction In Nuclear Power Plant Applications, Yusuke Yamani, Austin Jackson, Casey Kovesdi, Jeffrey Joe, Jeremy Mohon

Psychology Faculty Publications

Emerging technologies such as artificial intelligence (AI) and machine learning are rapidly evolving and promising tools for efficient and continued safe operations of the U.S. nuclear power plants (NPPs). Emerging AI techniques like large language models (LLMs) are one such technology that may help personnel at existing NPPs perform work more efficiently. For example, operators may query the current operational status of a power plant via a chat interface, leveraging LLMs to access plant-related information in an interactive manner rather than manually collecting various sensor data for surveillance or work order tasks. This is a fundamental shift in the way …