Digital Commons Network^™

Ai-Based Detection Of Optical Microscopic Images Of Pseudomonas Aeruginosa In Planktonic And Biofilm States, Bidisha Roy Sengupta, Esther Mallet, Angel Torres, Ravyn Solis

Faculty Publications

No abstract provided.

Assessing The Tax Communications Of E-Commerce Vendors, Part I, David Gamage

Faculty Publications

This article reports research results from a study analyzing the tax communication practices of top e-commerce retailers and marketplaces. The research found a spectrum of tax communication practices. Notably, many (but not all) e-commerce businesses that did not collect sales tax did still inform customers about potential use tax obligations, though the transparency of this information varied.

Displaced Decarbonization: Climate Necropolitics And The Contested Spatialities Of Green Hydrogen In Namibia, Meredith J. Deboom

Faculty Publications

Green hydrogen is often presented as a transformative solution to the dual challenges of decarbonization and economic development. This article applies the framework of climate necropolitics to interrogate the contested spatialities underlying such “win-win” narratives. It does so through an extended case study of Hyphen Hydrogen Energy, a $10 billion green hydrogen project planned for Lüderitz, Namibia. A remote town of 20,000 in a country with a $12 billion annual GDP, Lüderitz initially appears to be an unlikely host site for the “industrial fuel of the future.” To explain this outcome, I first illustrate how discordant socio-spatial projects—including European energy …

Explaining Youth Driver Licensing Determinants Using Xgboost And Shap, Kailai Wang, Jonas De Vos, Michael Smart, Sicheng Wang

Faculty Publications

This study explores the factors influencing driver's license acquisition among young individuals and examines its broader implications for mobility, safety, and sustainability. Leveraging nationally representative survey data on Millennials and Generation Z, we apply eXtreme Gradient Boosting (XGBoost) and SHapley Additive Explanations (SHAP) to identify key socioeconomic determinants of teenage driver's license attainment. Our findings reveal consistent predictors across both generations, including the percentage of licensed family members, household income per capita, educational attainment, and public transit ridership. We identify meaningful dose-response relationships, such as the increasing influence of licensed household members beyond a 0.75 threshold and the …

Two-Layer Formulation For Long-Runout Turbidity Currents: Theory And Bypass Flow Case, Hongbo Ma, Gary Parker, Matthieu Cartigny, Enrica Viparelli, S. Balachandar, Xudong Fu, Rossella Luchi

Faculty Publications

Turbidity currents, which are stratified, sediment-laden bottom flows in the ocean or lakes, can run out for hundreds or thousands of kilometres in submarine channels without losing their stratified structure. Here, we derive a layer-averaged, two-layer model for turbidity currents, specifically designed to capture long-runout. A number of previous models have captured runout of only tens of kilometres, beyond which thickening of the flows becomes excessive, and the models without a lateral overspill mechanism fail. In our framework, a lower layer containing nearly all the sediment is a faster, gravity-driven flow that propels an upper layer, where sediment concentration is …

A Psychometric Investigation Of The Biophilic Values Profile Indicator: A New Measure Of Environmental Values, W. Brad Faircloth, Jayson Seaman, Andrew J. Bobilya, Lauren A. Ferguson, Riley Whitney

Faculty Publications

Researchers studying outdoor experiences for educational or recreational purposes will benefit from better capturing the environmental values of the individuals and communities they serve, as both antecedent predictors and outcome measures. The Kellert-Shorb Biophilic Values Indicator (KSBVI) is an instrument that has shown promise as a tool for assessing environmental values. However, the length of the KSBVI makes it impractical to use, especially in field settings where brief measures are desirable. Therefore, this study’s purpose was to explore environmental values in a college student population relative to Kellert’s (2002) typology and to reduce the KSBVI to a more …

A Survey Of Sampling Methods For Hyperspectral Remote Sensing: Addressing Bias Induced By Random Sampling, Kevin T. Decker, Brett J. Borghetti

Faculty Publications

Identified as early as 2000, the challenges involved in developing and assessing remote sensing models with small datasets remain, with one key issue persisting: the misuse of random sampling to generate training and testing data. This practice often introduces a high degree of correlation between the sets, leading to an overestimation of model generalizability. Despite the early recognition of this problem, few researchers have investigated its nuances or developed effective sampling techniques to address it. Our survey highlights that mitigation strategies to reduce this bias remain underutilized in practice, distorting the interpretation and comparison of results across the field. In …

X-Ray Polarization Of The High-Synchrotron-Peak Bl Lacertae Object 1es 1959+650 During Intermediate And High X-Ray Flux States, Luigi Pacciani, Dawoon E. Kim, Riccardo Middei, Herman L. Marshall, Alan P. Marscher, Ioannis Liodakis, Iván Agudo, Svetlana G. Jorstad, Juri Poutanen, Manel Errando, Laura Di Gesu, Michela Negro, Fabrizio Tavecchio, Kinwah Wu, Chien Ting Chen, Fabio Muleri, Lucio Angelo Antonelli, Immacolata Donnarumma, Steven R. Ehlert, Francesco Massaro, Stephen L. O’Dell, Matteo Perri, Simonetta Puccetti, Francisco José Aceituno, Giacomo Bonnoli, Víctor Casanova, Juan Escudero, Beatriz Agís-González, César Husillos, Daniel Morcuende, Jorge Otero-Santos, Alfredo Sota, Pouya M. Kouch

Faculty Publications

We report the Imaging X-ray Polarimetry Explorer (IXPE) polarimetric and simultaneous multiwavelength observations of the high-energy-peaked BL Lacertae object (HBL) 1ES 1959+650, performed in 2022 October and 2023 August. In 2022 October, IXPE measured an average polarization degree ΠX = 9.4% ± 1.6% and an electric-vector position angle ψX = 53° ± 5°. The polarized X-ray emission can be decomposed into a constant component, plus a rotating component, with the rotation velocity ωEVPA = (−117 ± 12) deg day⁻¹. In 2023 August, during a period of pronounced activity of the source, IXPE measured an average ΠX = 12.4% …

A Brave New World Of Human Resources Research: Navigating Perils And Identifying Grand Challenges Of The Genai Revolution, Anthony Nyberg, Deidra J. Schleicher, Bradford S. Bell, Corine Boon, Peter Cappelli, David G. Collings, Joseph E. Dalle Molle, Stefan Feuerriegel, Berry Gerhart, Yoojin Jeong, M. Audrey Korsgaard, Dana Minbaeva, Robert E. Ployhart, Prasanna Tambe, Ingo Weller, Patrick M. Wright, Valery Yakubovich

Faculty Publications

This paper reviews the transformative role of Generative Artificial Intelligence (GenAI) in Human Resource (HR) management, from a practice perspective, highlighting both opportunities and challenges and laying out a use-inspired future research agenda. This scoping review is grounded in insights from a unique Summit held in Spring 2024, which brought together HR academic scholars with dozens of Fortune 500 Chief Human Resource Officers (CHROs) and their top technical leaders to discuss the workforce implications of GenAI. The paper identifies six key themes from the Summit practitioners: GenAI as disruptive and transformative, data as competitive advantage, adoption challenges, potential ethical abuses, …

Average Biomechanical Responses Of The Human Brain Grouped By Age And Sex, Ahmed A. Alshareef, Aaron Carass, Yaun-Chiao Lu, Joy Mojumder, Alexa M. Diano, Olivia M. Bailey, Ruth J. Okamoto, Dzung L. Pham, Jerry L. Prince, Philip V. Bayly, Curtis L. Johnson

Faculty Publications

Traumatic brain injuries (TBIs) occur from rapid head motion that results in brain deformation. Computational models are typically used to estimate brain deformation to predict risk of injury and evaluate the effectiveness of safety countermeasures. The accuracy of these models relies on validation to experimental brain deformation data. In this study, we create the first group-average biomechanical responses of the brain, including structure, material properties, and deformation response, by age and sex from 157 subjects. Subjects were sorted intro three age groups—young, mid-age, and older—and by sex to create group-average neuroanatomy, material properties, and brain deformation response to non-injurious loading …

Examining Physiological Responses To Misophonic Triggers, Christian O'Reilly, Xuan Yang, Sewon Oh, Doug Wedell, Svetlana Shinkareva

Faculty Publications

We collected and analyzed an array of biosignals (face electromyogram, skin electrodermal activity, peripheral temperature, and electrocardiogram) in 60 participants with and without misophonia, a condition characterized by decreased tolerance to innocuous sounds. Our goal was to objectively characterize the physiological response to misophonia triggering sounds. We found that misophonic responses can be objectively identified in some cases through atypical physiological reactions to triggering stimuli, though not all participants exhibited this response. Our analyses suggest a large interindividual variability in response to misophonic triggers and highlights the need for methodological adjustments in future experiments to increase the detectability of misophonic …

Removing Eog Artifacts From Eeg Recordings Using Deep Learning, Christian O'Reilly, Scott Huberty

Faculty Publications

The electroencephalogram (EEG) directly measures the electrical activity generated by the brain. Unfortunately, it is often contaminated by various artifacts, notably those caused by eye movements and blinks (EOG artifacts). Such artifacts are usually removed using an independent component analysis (ICA) or other blind source separation techniques. However, it is difficult to assess whether subtracting EOG components estimated through ICA removes some neurogenic activity. It is crucial to address this question to avoid biasing EEG analyses. Toward that objective, we developed a deep learning model for EOG artifact removal that exploits information about eye movements available through eye-tracking (ET). Using …

A Reliable And Efficient Detection Pipeline For Rodent Ultrasonic Vocalizations, Sabah Shahnoor Anis, Devin Mark Kellis, Kris Ford Kaigler, Marlene A. Wilson, Christian O'Reilly

Faculty Publications

Analyzing ultrasonic vocalizations (USVs) is crucial for understanding rodents' affective states and social behaviors, but the manual analysis is time-consuming and prone to errors. Automated USV detection systems have been developed to address these challenges. Yet, these systems often rely on machine learning and fail to generalize effectively to new datasets. To tackle these shortcomings, we introduce ContourUSV, an efficient automated system for detecting USVs from audio recordings. Our pipeline includes spectrogram generation, cleaning, pre-processing, contour detection, post-processing, and evaluation against manual annotations. To ensure robustness and reliability, we compared ContourUSV with three state-of-the-art systems using an existing open-access USV …

Deep Jansen-Rit Parameter Inference For Model-Driven Analysis Of Brain Activity, Deepa Tilwani, Christian O'Reilly

Faculty Publications

Accurately modeling effective connectivity (EC) is critical for understanding how the brain processes and integrates sensory information. Yet, it remains a formidable challenge due to complex neural dynamics and noisy measurements such as those obtained from the electroencephalogram (EEG). Model-driven EC infers local (within a brain region) and global (between brain regions) EC parameters by fitting a generative model of neural activity onto experimental data. This approach offers a promising route for various applications, including investigating neurodevel- opmental disorders. However, current approaches fail to scale to whole-brain analyses and are highly noise-sensitive. In this work, we employ three deep-learning architectures—a …

Re-Framing The Master Narratives Of Learning Dis/Abilities Through An Emotion And Intersectional Lens, David I. Hernández-Saca

Faculty Publications

In this conceptual framework paper, I critically chronicle the historiography, policy, and scientific literatures of learning disabilities (ld) and provide a conceptual framework for reframing these as master narratives. I defined master narratives as the pre-existent sociocultural forms of interpretation. I interrogated the a) cultural-historical; b) the federal definition of ld within idea, c) the educational-professional academic and focused on, the d) social and emotional literature of ld. The master narratives from these literatures included: a) ld as a boy who struggles with reading, ld as a symbolic complex, and the legacy of the term "feebleminded", d) assumptions about learning, …

Open Accessarticle Crystal Plasticity Modeling Of Dislocation Density Evolution In Cellular Dislocation Structures, Md Mahabubur Rohoman, Caizhi Zhou

Faculty Publications

The complex thermal cycles during the solidification process in metal additive manufacturing (AM) lead to the formation of high-density dislocation networks, organizing into submicron-scale cellular structures. These ultrafine structures are recognized as crucial for enhancing the mechanical properties of AM metals. In this study, we investigate the evolution of dislocation density within these cellular structures under plastic deformation and its impact on mechanical response using dislocation density-based crystal plasticity finite element (CPFE) modeling. The model incorporates the evolution of both statistically stored dislocation (SSD) and geometrically necessary dislocation (GND). Our simulations reveal that the yield and flow stresses of dislocation …

Actor–Partner Model Of Parenting And Co-Parenting Practices And Youth Resilience During The Covid-19 Pandemic, Olivia Aspiras, Jaimie O'Gara, Justine Radunzel

Faculty Publications

The present research examined parents' perspectives of co-parenting and supportive and hostile parenting as predictors of youth resilience during the COVID-19 pandemic. Participants were 47 mother/father dyads who had at least one K-12 child (Mage = 11.40, SD = 3.92). Mothers and fathers each completed an online survey that measured parenting, co-parenting, and youth resilience during the pandemic. Data were analyzed using the actor–partner interdependence model. Results revealed a positive relationship between mother supportiveness and perceived youth resilience; in contrast, increased father supportiveness was associated with lower perceived youth resilience. For both mothers and fathers, increases in their own hostility …

“They Are Fat And Want Special Treatment For Being Fat”: Backlash To And Lay Theories Of Fat Activism, Flora Blanchette-Oswald, Minh Duc Pham, R. J. Harr, Alexandra Garr-Schultz, Kimberly E. Chaney

Faculty Publications

Fat activism is a movement that seeks to acknowledge and eliminate the oppression of fat people. The movement and those who participate face significant backlash, yet fat activism is understudied. We sought to understand lay theories about fat activism; that is, how everyday people think about the goals and motivations of fat activism, and people who engage in fat activism, to understand how these perceptions shape support for and backlash toward fat activism. In Study 1 (N = 294), we qualitatively elucidated lay theories of fat activism in a US nationally representative sample. We identified lay theories that both …

Wind-Resilient Solar: Harnessing Cfd For Enhanced Load Estimation, Aly Mousaad Aly

Faculty Publications

Solar panels are a cornerstone of renewable energy infrastructure, playing a pivotal role in global sustainability efforts. To ensure their resilience and long-term viability, accurate wind load estimations are essential for designing supporting structures, which account for nearly 50% of their total cost. However, traditional building codes lack comprehensive guidance for solar panels, resulting in inconsistent estimations due to discrepancies in scaled wall-bounded wind tunnel testing methodologies. These inaccuracies pose safety risks, increase costs, and hinder adoption. Emerging technologies like computational fluid dynamics (CFD) simulations offer a promising alternative by enabling full-scale analysis under realistic conditions of complete turbulence. This …

Advancing Solar Farm Resilience: Cfd-Driven Wind Load Optimization, Aly Mousaad Aly

Faculty Publications

This study investigates wind load design methods for ground-mounted solar panels and arrays by comparing Computational Fluid Dynamics (CFD) simulations with design standards. A case study of a solar farm impacted by Hurricane Maria examines the effects of elevation height, tilt angle, and variations in the American Society of Civil Engineers (ASCE) standards on wind loads and structural failure. Turbulence models, including Reynolds Stress Model, k–ε Model, and Large Eddy Simulation (LES), are used to analyze wind pressures, lift, drag, and peak pressures. Results show Phase 1 experienced higher wind loads than Phase 2 due to design differences. A cost-benefit …

Impact Of Exercise Video-Guided Bodyweight Interval Training On Psychophysiological Outcomes In Inactive Adults With Obesity, Gabriella F. Bellissimo, Alyssa Bailly, Kelsey Bourbeau, Christine Mermier, Anthony Campitelli, Quint Berkemeier, Jonathan Specht, Jessica Smith, Jeremy Ducharme, Matthew J. Stork, Jonathan P. Little, Len Kravitz

Faculty Publications

Purpose: Determine the impact of a 6-week YouTube-instructed bodyweight interval training (BW-IT) program on cardiometabolic health, muscular strength, and factors related to exercise adherence in adults with obesity. Methods: Fourteen adults (30.7 ± 10.3 yrs, BMI 35.5 ± 5.4 kg/m²) participated in this study. The BW-IT program progressed bi-weekly from a 1:3 to 1:1 work-to-rest ratio, using maximum effort intervals of high knees, squat jumps, scissor jacks, jumping lunges, and burpees. Pre- and post-intervention measures included peak oxygen consumption ( (Formula presented.) O2peak), relative quadriceps isometric muscular strength, waist circumference (WC), body composition via bioelectrical impedance, and cardiometabolic …

Hedging Energy Transition: Green Hydrogen, Oil, And Low-Carbon Resilience As State Strategy In Namibia, Meredith J. Deboom

Faculty Publications

Policy frameworks increasingly portray energy transition as a mechanism for achieving a range of resilience- related goals, including socio-economic development and energy security. Energy transition is often character ized as a particularly important resilience strategy for lower-income states in the Global South, which face the simultaneous challenges of decarbonization and development. Yet these states, many of which have fossil fuel resources, face distinct constraints and risks in navigating energy transition, including the possibility that promised funding for low-carbon energy projects will never come to fruition or that global decarbonization will be deferred or abandoned completely. This article uses the case …

Geology Of Nacogdoches, Texas : Geogulf 2025, R. Larell Nielson

Faculty Publications

Nacogdoches and East Texas are geologically interesting places to live and work. This field trip will visit the locations indicated on the maps below (Figures 1 and 2). Our location is on the Sabine Uplift and is east of the East Texas Salt Dome Basin (Figure 3 and 4). The first producing oil well in Texas was drilled near Woden by Taliaferro Barret in 1866 at a depth of 106 feet, producing about 10 barrels a day from the Sparta Sand (Figures 5 and 6). Stratigraphic units that we will see are: Sparta Sand, Weches Formation, Queen City Sand, Reklaw …

Learning From Indigenous Knowledge And Research, Rob Morrison

Faculty Publications

The goal of this sabbatical research is to learn more about non-Western ways of knowing and learning (epistemologies) and to become a more effective culturally responsive teacher. I investigated how Indigenous Knowledge and research practices can enrich current definitions and practices of Information Literacy and integrate them into the research process. Information Literacy is part of a larger and more complex research process that involves connecting researchers’ questions and purpose with literature reviews and the resulting new knowledge.

I am continuing my research journey that started with my dissertation work on Culturally Relevant Information Literacy and Critical Information Literacy (CIL). …

Beyond Traditional Analytics: Ai's Transformative Role In Marketing Intelligence And Customer Experience Optimization, Anindita Sengupta, Prathima Shivakumar Pattada, Anasuya Sengupta

Faculty Publications

No abstract provided.

A Skill Assessment Framework For The Fisheries And Marine Ecosystem Model Intercomparison Project, Nina Rynne, Camilla Novaglio, Julia Blanchard, Daniele Bianchi, Villy Christensen, Marta Coll, Jerome Guiet, Jeroen Steenbeek, Andrea Bryndum-Buchholz, Tyler D. Eddy, Cheryl Harrison, Olivier Maury, Kelly Ortega-Cisneros, Colleen M. Petrik, Derek P. Tittensor, Ryan F. Heneghan

Faculty Publications

Understanding climate change impacts on global marine ecosystems and fisheries requires complex marine ecosystem models, forced by global climate projections, that can robustly detect and project changes. The Fisheries and Marine Ecosystems Model Intercomparison Project (FishMIP) uses an ensemble modeling approach to fill this crucial gap. Yet FishMIP does not have a standardised skill assessment framework to quantify the ability of member models to reproduce past observations and to guide model improvement. In this study, we apply a comprehensive model skill assessment framework to a subset of global FishMIP models that produce historical fisheries catches. We consider a suite of …

Rps Coach Project: A Growing Library About A Valuable Ai Tool, John Lande

Faculty Publications

This document collects a growing library of publications, videos, and podcasts about the RPS Negotiation and Mediation Coach (RPS Coach), an AI tool grounded in Real Practice Systems (RPS) Theory. RPS Coach is designed to support mediators, lawyers, parties, educators, students, and scholars by promoting good decision-making and reflective practice in negotiation and mediation. This piece summarizes articles and blog posts that present the theory, knowledge base, and functions of RPS Coach, along with practical guidance for its use in dispute resolution, writing, and legal education. It includes links to each publication and will be updated as new work is …

Rps Coach Is Biased - And Proud Of It, John Lande

Faculty Publications

This short essay explores the concept of bias in artificial intelligence tools used in dispute resolution. Biases are not necessarily flaws to be avoided, but inevitable and potentially constructive features of these tools. They reflect values and design choices that AI developers should disclose.

There are both market and ethical imperatives for AI tools to disclose their features and embedded values. As developers compete for users, people will want to know what they’re getting. Disclosure helps users understand the effects of assumptions, priorities, and frameworks built into a tool’s design, and thus should be treated as a core ethical principle. …

Government-Backed Insurance For Artificial Intelligence Technologies, Renee Henson

Faculty Publications

Artificial intelligence (AI) is an unpredictable technology that has the capacity to both help and harm people. Although insurance plays a key role in compensating for harms in other contexts, AI-produced damages evade traditional principles of risk pricing which limits viable commercial insurance coverage. AI requires modified insurance systems that can compensate diverse and unpredictable losses. Just like AI, at one time nuclear energy was viewed as a new and profitable, yet wholly unpredictable, technology that had the capacity to cause devastating harm. AI poses similar threats to society in certain domains, including, for example, health care (e.g., risk management …

Technology And Me And You: Getting Comfortable With Ai, John Lande

Faculty Publications

This short essay reflects on the author’s surprising dive into artificial intelligence (AI) despite his longstanding caution about adopting new technology. As a self-described tech-wary curmudgeon who avoids unnecessary upgrades and stays off social media, the author explores how AI – specifically, a custom-built RPS (Real Practice Systems) Negotiation and Mediation Coach – nonetheless has proved to be unexpectedly valuable.

Drawing from personal experience, the essay suggests how people can become comfortable using AI, suggesting how they can overcome hesitation and use AI productively. Rather than treating AI as a black box or magic solution, it emphasizes the importance of …