Digital Commons Network^™

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 …

The Role Of Tgf-Beta Superfamily Members In Immune Homeostasis And Disease, Natalie Eva Nieuwenhuizen, Ioannis Eleftherianos, Piotr Jan Kraj, Maria Semitekolou

Biological Sciences Faculty Publications

[Introduction] The Transforming Growth Factor beta (TGF-beta) superfamily, encompassing molecules such as TGFs, activins, Bone Morphogenetic Proteins (BMPs), Growth/Differentiation Factor (GDFs) and Nodals, represents the largest family of growth and differentiation factors, playing crucial roles in developmental and physiological processes across animal species (1). These molecules are integral to tissue homeostasis and cell fate determination. Among them, TGF-beta is particularly noted for its regulatory influence on immune responses and tissue fibrosis (2, 3). Recent research has expanded our understanding of the immune functions of other superfamily members, including activin A and BMPs (4). These molecules signal through receptor complexes composed …

Squid Paralarvae Turn With High Agility Using Jets Near The Reynolds Number Threshold For Viscous Domination, Ian K. Bartol, Alissa M. Ganley, Paul S. Krueger, Joseph T. Thompson

Biological Sciences Faculty Publications

Turning is critical for survival in the ocean, as marine animals need to maneuver to capture prey, elude predators, and navigate complex environments. While prior research has focused on turning performance of adult swimmers, less is known about early ontogenetic stages that locomote within lower Reynolds number (Re) regimes, especially young jetters. To evaluate squid paralarval turning proficiency and the role of the pulsed jet in maneuvers, recently hatched longfin squid Doryteuthis pealeii swimming in a viewing chamber were studied using digital particle image velocimetry and kinematic motion analyses. Paralarvae exhibited a wide repertoire of turning behaviors, including those performed …

Part 4: The Economic Impact Of Norfolk International Airport, Dragas Center For Economic Analysis And Policy, Old Dominion University

State of the Region Reports: Hampton Roads

Airports such as Norfolk International Airport (ORF) serve as economic engines connecting cities and regions to other localities and generate economic activity that would not otherwise occur in their absence. ORF set a record for commercial service passengers in 2019 before witnessing a dramatic fall in traffic in 2020 due to the COVID-19 pandemic. Arrivals and departures quickly recovered, and ORF set a new passenger traffic record in 2024. This chapter explores the economic impact of ORF on the economy of Virginia.

The State Of The Region: Hampton Roads 2025, Dragas Center For Economic Analysis And Policy, Old Dominion University, Vinod Agarwal, Josh Andrews, Andrea Barcenas, Leora Friedman, James V. Koch, Feng Lian, Anna Makhorkina, Melody Nguyen, Terry Parker, Mohamed Rahoui, Kara Sullivan, Jay Walker, Liam Ward, Robert Mcnab

State of the Region Reports: Hampton Roads

This is Old Dominion University’s 26th annual State of the Region: Hampton Roads report. While it represents the work of many people connected in various ways to the university, the report does not constitute an official viewpoint of Old Dominion University, its president, Brian Hemphill, Ph.D., the Board of Visitors, the Strome College of Business, or the generous donors who support the activities of the Dragas Center for Economic Analysis and Policy.

This year’s report provides an opportunity to reflect on the region’s economic performance since the COVID-19 pandemic and ask how changes in federal trade, immigration, civilian employment, and …

Empirical Vulnerability Function Development Based On The Damage Caused By The 2014 Chiang Rai Earthquake, Thailand, Patcharavadee Hong, Masashi Matsuoka

Institute for Innovation & Entrepreneurship Publications

Seismic hazards in Thailand are frequently overlooked in disaster management planning, leading to insufficient research and significant economic losses during earthquake events. The 2014 Chiang Rai earthquake exposed critical vulnerabilities in Thailand's building practices due to widespread non-compliance with building codes and limited preparedness. This exposure prompted the development of empirical vulnerability functions using loss data from 15,031 damaged residences. The study analyzed government compensation records, which were standardized using replacement cost metrics. Three distinct models were developed through probabilistic and possibilistic modeling approaches. Residual analysis demonstrated the superior performance of the possibilistic approach, with the Possibilistic-based Vulnerability Function achieving …

Restored Wetlands Show Rapid Vegetation Recovery And Substantial Surface-Water Expansion, Thilina D. Surasinghe, Yin-Hsuen Chen, Kunwar K. Singh

Center for Geospatial Science, Education & Analytics Faculty Publications

Ecological restoration is essential for improving the ecological integrity of degraded ecosystems to enhance ecosystem services and biodiversity. In this study, we assessed the effectiveness of wetland restoration on retired cranberry farms by analyzing vegetation recovery and surface-water dynamics using the enhanced vegetation index (EVI) and normalized difference water index (NDWI) derived from Sentinel-2 satellite imagery. To quantify temporal dynamics of both vegetation recovery and surface-water cover, we identified the spectral distinctions among restored wetland plant communities. Our results indicated the emergence of distinct plant communities upon restoration. Restored wetlands in general showed significant and progressive vegetation recovery and expanding …

Landslide At River's Edge: Alum Bluff, Apalachicola River, Florida, Joann Mossa, Yin-Hsuen Chen

Center for Geospatial Science, Education & Analytics Faculty Publications

When rivers impinge on the steep bluffs of valley walls, dynamic changes stem from a combination of fluvial and mass wasting processes. This study identifies the geomorphic changes, drivers, and timing of a landslide adjacent to the Apalachicola River at Alum Bluff, the tallest natural geological exposure in Florida at similar to 40 m, comprising horizontal sediments of mixed lithology. We used hydrographic surveys from 1960 and 2010, two sets of LiDAR from 2007 and 2018, historical aerial, drone, and ground photography, and satellite imagery to interpret changes at this bluff and river bottom. Evidence of slope failure includes a …

Preparing The Built Environment In Grenada For Future Sea Level Rise And Extreme Precipitation Events, Rocco D. Boyd, Meagan P. Duncan, Alivia D. Markham, Adelle K. Novak, Blaizen B. Bloom, Ashawne Edwards, Jai S. Lewis, Hans-Peter Plag

CCPO Publications

[Introduction] Communities across the globe are being affected by climate change in numerous ways. However, those most often affected, especially by sea level rise, are those small island nations that are pressed for space already; this includes the island of Grenada. Grenada is located in the southern portion of the Caribbean and is bordered by the Caribbean Sea (West) and the Atlantic Ocean (East). The planning and development authority (PDA) has been identified as the main stakeholder involved in this case study, but recommendations will be made to all parties involved to best accomplish our mission.

Key stakeholders were initially …

Multi-Model Estimate Of Antarctic Ice-Shelf Basal Mass Budget And Ocean Drivers, Benjamin K. Galton-Fenzi, Richard Porter-Smith, Sue Cook, Eva Cougnon, David E. Gwyther, Wilma G. C. Huneke, Madelaine G. Rosevear, Xylar Asay-Davis, Fabio Boeira Dias, Michael S. Dinniman, David Holland, Kazuya Kusahara, Kaitlin A. Naughten, Keith W. Nicholls, Charles Pelletier, Ole Richter, Hélène Seroussi, Ralph Timmerman

CCPO Publications

Societal adaptation to rising sea levels requires robust projections of the Antarctic Ice Sheet's retreat, particularly due to ocean-driven basal melting of its fringing ice shelves. Recent advances in ocean models that simulate ice-shelf melting offer an opportunity to reduce uncertainties in ice–ocean interactions. Here, we compare several community-contributed, circum-Antarctic ocean simulations to highlight inter-model differences, evaluate agreement with satellite-derived melt rates, and examine underlying physical processes. All but one simulation use a melting formulation depending on both thermal driving (T^⋆) and friction velocity (u^⋆), which together represent the thermal and ocean current forcings at the …

Improving Understanding And Connections For Preparedness, Mitigation, Response, And Recovery For Tornado And Straight-Line Wind Events In Virginia: Summary Of The Inaugural Virginia Tornado And Straight-Line Wind Summit, Wie Yusuf, Monica Arul, Joshua Behr, Kaleen Lawsure, An Huy Pham, Henry Attivor

School of Public Service Faculty Publications

Background

The Virginia Tornado and Straight-Line Wind Summit, the first of its kind in the Commonwealth, was held on October 15, 2025 in Isle of Wight County, Virginia. The Summit had several goals, including:

• Understanding Virginia’s wind risk and learning the science behind it.
• Hearing lessons learned from emergency managers who have experienced extreme wind events.
• Learning about practical steps to prepare, mitigate, and respond to severe wind events.
• Learning best practices for timely and actionable communication with the public before and after events.
• Strengthening interagency coordination and connecting with others to share resources, align priorities, and coordinate resilience planning. …

Ai-Generated Messaging For Life Events Using Structured Prompts: A Comparative Study Of Gpt With Human Experts And Machine Learning, Christopher Lynch, Erik Jensen, Ross Gore, Virginia Zamponi, Kevin O'Brien, Brandon Feldhaus, Katherine Smith, Joseph Martínez, Madison H. Munro, Timur E. Ozkose, Tugce B. Gundogdu, Ann Marie Reinhold, Hamdi Kavak, Barry Ezell

VMASC Publications

Large Language Models (LLMs) play an increasingly integrated and pivotal role in generating diverse types of texts, such as social media messages, emails, narratives, and technical reports, among other textual communication forms. As AI-generated messaging filters into human communication, a systematic exploration of their effectiveness for mimicking human-like communication of life events is needed. In this study, we employ a zero-shot structured narrative prompt to generate 24,000 life event messages for birth, death, hiring, and firing events using OpenAI's GPT-4. From this dataset, we manually classify 2880 messages and evaluate their validity in conveying these life events through the form …

Advances In Bacterial Cellulose-Based Scaffolds For Tissue Engineering: Review, Rewati Raman Ujjwal, Gymama Slaughter

Center for Bioelectronics Publications

Bacterial cellulose (BC) has emerged as a highly versatile and promising biomaterial in tissue engineering, with potential applications across skin, bone, cartilage, and vascular regeneration. Its exceptional properties like high mechanical strength, superior biocompatibility, excellent moisture retention, and inherent ability to support cell adhesion and proliferation, make BC particularly effective for wound healing and skin regeneration. These attributes accelerate tissue repair and foster new tissue formation, highlighting its value in skin-related applications. Additionally, BC's capacity to support osteogenic differentiation, combined with its mechanical robustness, positions it as a strong candidate for bone tissue engineering, facilitating regeneration and repair. Recent advancements …

Electrochemical And Nanomaterial Based Strategies For Nonenzymatic Glucose Detection: A Review, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Electrochemical glucose sensing technologies have undergone significant evolution, with continual advancements aimed at improving sensitivity, selectivity, and user convenience. This review systematically explores the development of emerging nonenzymatic glucose sensor designs. Nonenzymatic sensors are critically evaluated for their ability to overcome enzymatic limitations, leveraging novel materials and catalytic mechanisms. Additionally, the emergence of smartphone-integrated glucose monitoring systems is highlighted as the fifth generation, representing a paradigm shift toward personalized, real-time healthcare management. Emphasis is placed on the strategies employed to reduce the working electrode potential and enhance analytical performance. Key analytical metrics and real-sample applicability are evaluated, and persistent challenges …

Gold Nanoparticle-Enhanced Molecularly Imprinted Polymer Electrode For Non-Enzymatic Lactate Sensing, Christopher Animashaun, Abdellatif Ait Lahcen, Gymama Slaughter

Center for Bioelectronics Publications

We are reporting the development of a high-performance, non-enzymatic electrochemical biosensor for selective lactate detection, integrating laser-induced graphene (LIG), gold nanoparticles (AuNPs), and a molecularly imprinted polymer (MIP) synthesized from poly(3,4-ethylenedioxythiophene) (PEDOT). The LIG electrode offers a highly porous, conductive scaffold, while electrodeposited AuNPs enhance catalytic activity and signal amplification. The PEDOT-based MIP layer, electropolymerized via cyclic voltammetry, imparts molecular specificity by creating lactate-specific binding sites. Cyclic voltammetry confirmed successful molecular imprinting and enhanced interfacial electron transfer. The resulting LIG/AuNPs/MIP biosensor demonstrated a wide linear detection range from 0.1 µM to 2500 µM, with a sensitivity of 22.42 µA/log(µM) and …

Evaluating The Long-Term Effectiveness Of Marsh Terracing For Conservation With Integrated Geospatial And Wetland Simulation Modeling, Nick Carpenter, Laura Costadone, Thomas R. Allen

ODU Articles

Coastal marshes provide essential ecosystem services, yet they are vulnerable to anthropogenic stressors and climate change, particularly sea level rise (SLR). Restoration approaches like marsh terracing have emerged as nature-based strategies to enhance resilience and reduce habitat loss. This study applies the Sea Level Affecting Marshes Model (SLAMM) to assess the potential of marsh terraces to mitigate future losses, while also examining the model’s limitations, including its assumptions and capacity to reflect complex marsh processes. A geospatial approach was used to generate 3D representations of terraces through morphostatic modeling within digital elevation models (DEMs). Under a no-restoration scenario, SLAMM projections …

From Wind To Whales: Potential Hydrodynamic Impacts Of Offshore Wind Energy On Nantucket Shoals Regional Ecology, Eileen E. Hofmann, Jeffrey R. Carpenter, Qin J. Chen, Josh T. Kohut, Richard L. Merrick, Erin L. Meyer-Gutbrod, Douglas P. Nowacek, Kaustubha Raghukumar, Nicholas R. Record, Kelly Oskvig

OES Faculty Publications

The National Academy of Sciences, Engineering, and Medicine convened a committee in June 2023 to assess the potential hydrodynamic and ecological impacts from offshore wind energy development in the Nantucket Shoals region, with particular attention to impacts on the critically endangered North Atlantic right whale (Eubalaena glacialis) that forages on zooplankton aggregations in the region. The assessment suggested that the effects of offshore wind energy development will be difficult to distinguish from the effects of natural variability and climate change in this region. The Consensus Study Report recommendations highlight observational and modeling studies that will advance understanding of …

Qos-Aware Link Adaptation For Beyond 5g Networks: A Deep Reinforcement Learning Approach, Ali Parsa, Neda Moghim, Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Modern wireless communication systems face increasingly complex challenges due to rapidly changing channel conditions and the growing diversity of application-specific Quality of Service (QoS) requirements. Traditional link adaptation mechanisms primarily aim to maximize throughput and often lack the flexibility to support emerging applications, such as Extended Reality (XR) and Virtual Reality (VR), which demand simultaneous guarantees for high data rates, ultra low latency, and high reliability. These stringent and multidimensional QoS needs call for more intelligent and adaptive solutions. In this paper, we propose QDRLLA (QoS-aware Deep Reinforcement Learning-based Link Adaptation), a novel framework that employs deep reinforcement learning to …

A Trust-By-Learning Framework For Secure 6g Wireless Networks Under Native Generative Ai Attacks, Md Shirajum Munir, Sravanthi Proddatoori, Manjushree Muralidhara, Trinidad Mario Dena, Walid Saad, Zhu Han, Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Sixth-generation (6G) wireless networks will become vulnerable due to native generative AI (GenAI)-driven intelligent poisoning attacks in both the radio unit and the core network. In particular, network parameters and metrics in cross-layer design pose fundamentally uncertain conditions and can be compromised through the native GenAI mechanism, which leverages data augmentation and reconstruction capabilities. This work investigates the capabilities of native GenAI to create novel poisoning attacks in wireless networks, while investigating their impact through uncertainty-informed root analysis. Then, detected attacks are mitigated by developing a trustworthy service aggregation in the wireless network. First, a joint decision problem is formulated …

Leveraging Custom Gpts For Formative Assessment And Feedback, Nari Kim, Jason Vickers, Shaimaa Alyehaibi, Chikezie Ozuzu, Xinyue Ren, Suhasini Kotcherlakota

STEMPS Faculty Publications

As artificial intelligence (AI) advances, the use of custom generative pre-trained transformers (Custom GPTs) in formative assessments opens new opportunities for improving student learning and engagement. Custom GPTs increase cognitive and emotional engagement by providing timely, context-sensitive, and tailored responses based on unique learner profiles. This paper aims to investigate how custom GPT-driven formative feedback can enhance individualized learning experiences and improve student performance. This paper will discuss the promise of this AI tool, the challenges associated with its application, and recommendations for educators and academics looking to use these technologies for formative assessments.

Technology Integration In Online Feminist Pedagogy, Xinyue Ren

STEMPS Faculty Publications

Feminist pedagogy refers to a liberatory way of teaching to develop democratic and transformative learning experiences in which students can be empowered to make a social change (Grissom-Broughton, 2020). Previous research showed that feminist pedagogy was often used to guide course design and development in various disciplines, such as music, art, language, and environmental education (Cannizzo, 2021; Grissom-Broughton, 2020; Jespersen, 2014; Springgay & Zaliwska, 2017). For example, in music education, instructors increased the representations of multicultural voices in course materials and applied in-depth discussions and essays as learning assessments to develop critical and reflective thinking among students. In a feminist-oriented …

The Integration Of Artificial Intelligence And Ontologies: Transformations In Knowledge Representation And Application, Grazia Serratore, Julaine Clunis

STEMPS Faculty Publications

Artificial Intelligence (AI) is reshaping the landscape of knowledge representation. There is an increasingly strong bidirectional relationship, between AI techniques and ontologies. AI techniques revolutionized traditional, manual ontology development and contribute to automated ontology construction, while ontologies enhance the performance of AI systems and their semantic accuracy. Through a comprehensive review of current literature, this paper aims to examine: i) how Machine Learning (ML) techniques contribute to the automated construction, refinement, and validation of ontologies; ii) the most widely used and effective ML approaches for ontology construction; iii) how domain-specific requirements influence the selection and adaptation of AI techniques for …

Part 3: Virginia's Workforce: Understanding Apprentices, Dragas Center For Economic Analysis And Policy, Old Dominion University

State of the Commonwealth Reports

This chapter examines the state of apprenticeship programs in the United States and Virginia, assessing their role in the labor market. We begin with an overview of national apprenticeship policy, tracing major laws and initiatives that have influenced the system’s evolution and expansion. We then review trends in apprenticeship participation, highlighting the states that lead in registrations and program growth. The discussion pivots to Virginia, where we analyze current occupation, wage and demographic data, and regional apprenticeship examples that connect education and industry. Finally, we consider whether apprenticeships represent a sustainable and scalable solution to the Commonwealth’s workforce challenges.

Multisociety Guidance For Infection Prevention And Control In Nursing Homes, Lona Mody, Sonali D. Advani, Muhammad Salman Ashraf, Allison H. Bartlett, Suzanne F. Bradley, Deborah P. Burdsall, Jennifer A. Hanrahan, Susan S. Huang, Robert L.P. Jump, Lindsay Nicolle, Mary-Claire Roghmann, Patricia Stone, Rekha K. Murthy

Department of Medicine Faculty Publications

This multisociety guidance was endorsed by SHEA, APIC, IDSA, PALTmed, and AGS. It provides recommendations for infection prevention and control (IPC) in the context of the complexity of nursing home care in the United States: increased medical acuity of residents, the spread of multidrug-resistant organisms, and the threat of emerging pathogens. Recommendations and implementation suggestions address IPC leadership, staffing, and resources, healthcare personnel and residents‘ adherence to precautions and effective hand hygiene, outbreak preparedness, training, occupational health, cleaning and disinfection in the care environment, and the involvement of IPC in the facility. The guidance also addresses the challenges of maintaining …

Influence Of Time Pressure And Flood Information Type On Flood Alert Effectiveness In Driving, Katherine R. Garcia, Scott Mishler, Jing Chen

Psychology Faculty Publications

Flood alerts are a means of risk communication that alerts the public to potential floods. The purpose of this research was to investigate factors that affected drivers' understanding and actions given a flood presented through a mobile navigation application. Two experiments were conducted to examine the effects of time pressure and type of flood information on drivers' planned actions when faced with potential flooding. Participants were asked about their planned actions given one type of flood information in a driving scenario either with or without time pressure. Our results indicated significant differences in participants' behaviors across the different flood information …

Automation To Autonomy: Temporal Dynamics Of Trust And Visual Attention Allocation Did Not Evolve, Tetsuya Sato, Eric Chancey, Yusuke Yamani

Psychology Faculty Publications

Emerging work environments are expected to implement autonomy that performs various functions without human input. Previous works has shown that trust in automation is negatively correlated with visual attention allocation, indicating that trust is a dynamic construct. Moreover, trust in automation and trust in autonomy appears to evolve in similar ways. However, recent work has demonstrated differences between trust in automation and trust in autonomy within Kaber’s (2018) theoretical framework (Sato et al., 2023b). Yet, it is uncertain whether the development of trust and visual attention allocation differs between automation and autonomy. The present study examined the temporal dynamics of …

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

Similarity May Be Safer: The Effect Of Similarity Between Speech-Based Takeover Request Style And Driver Personality On Self-Driving Takeover Performance, Keer Ma, Jianfeng Wu, Yanxi Lin, Zihan Li, Songyang Guo, Dongfang Jiao, Shihan Yu

Psychology Faculty Publications

In Level 3 automated driving, it is critical that drivers can rapidly and effectively shift from non-driving related tasks (NDRT) back to the driving task. While previous research has examined the modality, timing, and vocal characteristics of takeover requests (TORs), little is known about how the style of speech-based TORs interacts with drivers’ personality traits. This study conducted a driving simulator experiment with 49 participants using a 2 × 2 within-subjects design. Drawing on the dominant-submissive dimension of personality, we examined the similarity of personality tendencies between speech-based TORs and drivers under takeover scenarios of varying urgency (low: road construction; …

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 …

Exploring Institutional Stratification: Minority-Serving Institutional Pathways To Medical School Acceptance In The United States, Amanda K. Burbage, Eushekia Y. Hewitt

EVMS School of Health Professions Faculty Publications

Introduction

Recruiting and training a diverse pool of physicians from historically excluded groups is vital to solving complex scientific problems and increasing access to patient care. Disparate educational and health outcomes of COVID-19 amplified this need. In stratified higher education systems, underfunded institutions that serve greater numbers of underrepresented in medicine (URM) students face unique barriers to entering physician training. However, pathways from historically underfunded minority-serving institutions (MSIs) in the United States to medical school (MD) are not well understood.

Method

A hierarchical logistic regression analysis of 328 488 de-identified applicants to US MD-granting medical schools for academic years 2017-2018 …