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Aquatic Interrelations In Malika Mokeddem’S Novel N’Zid (2001), Laura C. Klein

Green Humanities: A Journal of Ecological Thought in Literature, Philosophy & the Arts

This article offers an ecological analysis of Malika Mokeddem's novel N'Zid (2001), moving beyond postcolonial and anthropocentric interpretations. It centers on the protagonist Nora's individuation, arguing this process is intrinsically linked to her evolving relationship with the aquatic environment from which she emerges. The article aims to situate N'Zid within an ecological perspective, particularly relevant in the Anthropocene, an era compelling a reassessment of humanity's place. Echoing Bruno Latour, addressing inter-relationality is essential as the stable physical framework of the Moderns becomes unstable. This view necessitates rethinking environmental issues and encourages a scientific interpretation of the novel, drawing on neurosciences, …

Volume 5 - Water (Full)

Green Humanities: A Journal of Ecological Thought in Literature, Philosophy & the Arts

No abstract provided.

Critical Design And The Robotic Imaginary: Design Criticism And Critical Robots, Jörgen Behrendtz

The Journal of Sociotechnical Critique

This paper brings critical design and design criticism to critical robot studies. Critical design can be described as an umbrella term for approaches making use of speculative designs to highlight and challenge narrow assumptions, preconceptions or even taken-for-granted truths about the role products play (in a wide sense) in everyday life. Design criticism refers to a reasoned procedure that investigates emancipatory and/or limiting potentials of designs, theorizes the roles of affordances, materials and embodied perception as epistemological resources in media interaction, and clarifies connections between specific design choices and their associated experiential qualities, seductive powers, ideological underpinnings, material operations, and …

Threads Of Empathy: An Integrative Model Of Empathy In The Schools, Arthur J. Clark, Tara M. Simpson

Journal of Human Services Scholarship and Interprofessional Collaboration

Empathy has a distinctive and evolving history in education for cultivating human relationships and engendering mutual understanding. Within a school setting, empathic engagement is essential for the social and emotional development of children and adolescents. From an educational perspective, literature from multiple disciplines and specialties illustrate innovative practices to harness empathy in the classroom and beyond. The representative initiatives hold promise for developing an integrative model of empathy within a school or a school district through a program involving interprofessional collaboration.

A Case Of Listeria Monocytogenes Bacteremia In A Middle-Aged Woman With A History Of Primary Biliary Cholangitis, Caleb Smack, Jared T. Lausen, Aaron Mills

Eastern Virginia Medical Journal

In this report, we discuss the case of a patient with Listeria monocytogenes bacteremia likely resulting from primary biliary cholangitis (PBC) induced cirrhosis. We aim to bolster the body of literature on Listeria bacteremia and establish PBC as a risk factor for this rare complication. Our patient, who presented with sepsis, was subsequently found to have Listeria bacteremia and received intravenous antibiotic treatment of ampicillin for 3 total weeks with complete resolution of her disease. This is the first case suggesting that cirrhosis as a result of PBC may be an independent risk factor for Listeria bacteremia. In patients at …

Integrating Clinical Reasoning Into Mental Health Diagnosis: A Conceptual Framework For Counseling Practice, Ashley F. Waddington, Alexander M. Fields, Haley Ault

Journal of Human Services Scholarship and Interprofessional Collaboration

Clinical reasoning has long guided diagnostic accuracy in nursing and medical fields, but its application in mental health counseling remains limited. This paper presents a conceptual diagnostic decision-making (DDM) process to embed clinical reasoning into the diagnostic process for counselors, incorporating two vital constructs: counselor self-efficacy and counselor bias (implicit and explicit). Grounded in Bandura’s theory of self-efficacy (1977) and Carvalho et al.’s (2017) clinical reasoning model, the framework highlights the cognitive, behavioral, and contextual factors that shape diagnostic decision-making in early-career counselors, including counselor biases. The paper calls for reform in counselor training, emphasizing curriculum enhancements as pathways to …

Maintaining Balance And Wellness In Remote Work, Michelle Bartlett

Educational Leadership & Workforce Development Faculty Publications

In today's rapidly evolving work environments, remote work has become more than a trend; it is now a mainstay and rising (Ewers & Kangmennaang, 2023). This shift has necessitated a re-evaluation of traditional work paradigms, particularly in the realms of work-life balance and employee wellness. This chapter details the core strategies for thriving in remote work settings by setting boundaries, combating isolation, and fostering supportive corporate cultures. Transitioning from offices to remote work can blur the lines between personal and professional lives (Bella, 2023; Beňo, 2023). This section provides practical advice on how remote workers can effectively delineate these aspects. …

Assessing The Possibilities And Speculations Of Blended Teaching-Learning (Btl) Based On The Online Teaching-Learning (Otl) Experience During Covid-19 In Bangladesh, Nazmun Chaitee

Educational Leadership & Workforce Development Faculty Publications

This research paper investigates the potential and viability of implementing Blended Teaching Learning (BTL) in Bangladesh, drawing on the lessons learned from the COVID-19 Online Teaching Learning (OTL) practice experiences. The study specifically focuses on examining the advantages and challenges encountered by teachers and students in online classes during the pandemic. Through a mixed-methods approach, including questionnaire surveys, interviews, and focus group discussions (FGDs), data was collected from secondary-level teachers and students in Bangladesh. The findings highlight the dedicated efforts made by educators and students in embracing and adapting to online education during the COVID-19 crisis. Furthermore, the study identifies …

The Ai Revolution In Virtual Try-Ons: A Means-End Chain Model Perspective, Ju-Young M. Kang, Ji Young Lee, Dooyoung Choi, Sumin Helen Koo, Jeehyun Song, Youngjin Bahng

Educational Leadership & Workforce Development Faculty Publications

Leading brands have begun to implement artificial intelligence-driven virtual try-on (AI VTO) technology, which helps reduce returns and increase conversion rates, repeat purchases, and customer loyalty. This research aimed to examine how retail user experience with specific perceived quality factors of AI VTOs influences users’ value equity and downstream loyalty and to investigate the moderating effects of clothing in relation to the self as structure and concern for physical appearance, based on a Means–End Chain model. Data were collected from 509 U.S. online apparel shoppers using a consumer panel. Structural equation modeling and multigroup analysis were used for data analysis. …

Neighborhood Socioeconomic Deprivation And Physical Activity Associate With Extracellular Vesicle Size And Cargo In A Community-Based Cohort Of Women, Yvonne Baumer, Elizabeth M. Aquino Peterson, Matthew R. Bavuso, Noel Miller, Cristhian A. Gutierrez-Huerta, Nithya P. Vijayakumar, Sam J. Neally, Kaveri Curlin, Valerie M. Mitchell, Billy S. Collins, Neelam R. Redekar, Subrata Paul, Anca D. Dobrian, Tiffany M. Powell-Wiley

Department of Biomedical and Translational Sciences Faculty Publications

African American (AA) women face disproportionate cardiovascular disease (CVD) risk due to adverse social determinants of health (SDoH), including lower socioeconomic status (SES). Physical activity (PA) and plasma extracellular vesicles (EVs) modulate CVD risk, but their relationships with SDoH remain unclear. This study examines associations between SDoH, PA, and plasma EVs in a Washington, DC-based cohort of at-risk AA women. Participants (N = 24, Age: 57 ± 12, BMI: 35 ± 6, ASCVD: 9 ± 5) joined the Step It Up Community-Engaged, Digital Health Physical Activity Intervention pilot study. EVs were isolated from fasting plasma samples. Multivariable regression, adjusted for …

First-Generation Medical School Applicants: A Quantitative Study Designed To Identify Areas Of Educational Support, Bethsabe Romero, Amanda K. Burbage

EVMS School of Health Professions Faculty Publications

First-generation (First Gen) students are unique medical school applicants. Due to their lived experience, they approach patient care by prioritizing trust, comfort and understanding. They have proven ability to overcome obstacles and were found to be more resilient than their continuing generation (Cont Gen) peers. Despite these notable attributes, they face unique challenges in gaining medical school acceptance. There are very few quantitative studies examining this student subpopulation, and our study identifies characteristics of first-generation medical school applicants while highlighting areas of needed support. This cross-sectional study used deidentified Application and Matriculating Student Questionnaire survey data that was obtained from …

Multi-Grade Deep Learning, Yuesheng Xu

Mathematics & Statistics Faculty Publications

Deep learning requires solving a nonconvex optimization problem of a large size to learn a deep neural network (DNN). The current deep learning model is of a single-grade, that is, it trains a DNN end-to-end, by solving a single nonconvex optimization problem. When the layer number of the neural network is large, it is computationally challenging to carry out such a task efficiently. The complexity of the task comes from learning all weight matrices and bias vectors from one single nonconvex optimization problem of a large size. Inspired by the human education process which arranges learning in grades, we …

A New Functional Setting For Term Structure Modeling Using The Health-Jarrow-Morton Framework, Michael Pokojovy, Ebenezer Nkum, Thomas M. Fullerton Jr.

Mathematics & Statistics Faculty Publications

The well-known Heath–Jarrow–Morton (HJM) framework provides a universal and efficacious instrument for modeling the stochastic evolution of an entire yield curve by explaining the interest rate dynamics in continuous time under no-arbitrage conditions. Existing implementations involve exponentially weighted function spaces as theoretical settings for the former stochastic evolution. While the choice of weight can have a drastic effect on model calibration and subsequent forecasting, it cannot be estimated from market data and does not allow for any objective interpretation. The proposed approach does not have this shortcoming as it adopts a suitably designed unweighted function space. The HJM equation is …

The State Of Interprofessional Practice Between Behavior Analysts And Speech-Language Pathologists, Sara Snyder, Heartley Huber, Danika Pfeiffer, Dannette Murray

Speech-Language Pathology Faculty Publications

Interprofessional practice (IPP) is necessary to ensure assessment and interventions are designed and implemented both efficiently and effectively. We sought to investigate how Board Certified Behavior Analysts (BCBAs) and Speech-Language Pathologists (SLPs) engage in IPP. Both professionals may provide evaluations and interventions related to communication in schools and community-based healthcare systems. We disseminated a survey to BCBAs and SLPs to elicit information about their collaboration with each other. Topics included: (a) frequency of collaboration and communication with the other professional; (b) confidence engaging in IPP; (c) interprofessional training experiences; (d) barriers and facilitators to collaboration with the other profession; and …

Aura: An Ai-Powered Multimodal Prototype For Adaptive Apraxia Of Speech Therapy And Communication Support, Omotayo Omoyemi, Rachel K. Johnson

Speech-Language Pathology Faculty Publications

Apraxia of Speech (AOS) is a motor speech disorder that significantly limits communication and requires intensive, long-term therapy. Access to consistent treatment is often constrained by shortages of speech-language pathologists, high costs, and limited opportunities for continuous monitoring outside clinical settings. Recent advances in Artificial Intelligence (AI) provide new opportunities to support scalable and personalized speech therapy.

This paper presents AURA (Adaptive Understanding and Relearning Assistant for Apraxia), a multimodal AI framework designed to support speech therapy, progress monitoring, and communication for individuals with AOS. The system integrates speech analysis, machine learning–based error detection, reinforcement learning for adaptive therapy, and …

Part Ii: Industrial Information Integration Review 2020-2025, Jinzhi Li

Information Technology & Decision Sciences Faculty Publications

Industrial Information Integration Engineering (IIIE) has become increasingly essential for improving operational efficiency and harmonizing heterogeneous industrial systems through advanced digital integration approaches. Fueled by rapid advancements in Industry 4.0 technologies—including digital twins, artificial intelligence, immersive interfaces, and IoT infrastructures—IIIE is substantially transforming traditional enterprise architecture and integration frameworks. This systematic review synthesizes recent developments and emerging trends, with particular attention to the accelerating adoption of digital twins and the deepening convergence between operational technologies (OT) and information technologies (IT) across multiple sectors. While notable progress has been made, significant challenges persist, especially in developing resilient integration architectures and fully …

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 …

Identifying Relevant Covariates In Rna-Seq Analysis By Pseudo-Variable Augmentation, Yet Nguyen, Dan Nettleton

Mathematics & Statistics Faculty Publications

RNA-sequencing (RNA-seq) technology allows for the identification of differentially expressed genes, which are genes whose mean transcript abundance levels vary across conditions. In practice, RNA-seq datasets often include covariates that are of primary interest in addition to a set of covariates that are subject to selection. Some of these covariates may be relevant to gene expression levels, while others may be irrelevant. Ignoring relevant covariates or attempting to adjust for the effect of irrelevant covariates can compromise the identification of differentially expressed genes. To address this issue, we propose a variable selection method that uses pseudo-variables to control the expected …

Utilizing Machine Learning Techniques For Computer-Aided Covid-19 Screening Based On Clinical Data, Honglun Xu, Andrews T. Anum, Michael Pokojovy, Sreenath Chalil Madathil, Yuxin Wen, Md Fashiar Rahman, Tzu-Liang (Bill) Tseng, Scott Moen, Eric Walser

Mathematics & Statistics Faculty Publications

The COVID-19 pandemic has highlighted the importance of rapid clinical decision-making to facilitate the efficient usage of healthcare resources. Over the past decade, machine learning (ML) has caused a tectonic shift in healthcare, empowering data-driven prediction and decision-making. Recent research demonstrates how ML was used to respond to the COVID-19 pandemic. This paper puts forth new computer-aided COVID-19 disease screening techniques using six classes of ML algorithms (including penalized logistic regression, random forest, artificial neural networks, and support vector machines) and evaluates their performance when applied to a real-world clinical dataset containing patients’ demographic information and vital indices (such as …

Wearable Biosensors For Continuous Monitoring Of Chronic Kidney Disease: Materials, Biofluids, And Digital Health Integration, Anupamaa Sivasubramanian, Shankara Narayanan, Gymama Slaughter

Center for Bioelectronics Publications

Chronic kidney disease (CKD) is a progressive and irreversible disorder affecting over 850 million individuals globally and is associated with significant morbidity, mortality, and healthcare burden. Conventional diagnostic approaches rely on intermittent laboratory measurements, including serum creatinine, estimated glomerular filtration rate (eGFR), and urinary albumin, which provide limited temporal resolution and fail to capture dynamic physiological changes. Recent advances in wearable biosensing technologies offer new opportunities for continuous, non-invasive monitoring of biochemical and physiological markers relevant to renal function. This review provides a comprehensive analysis of wearable biosensors for CKD monitoring, focusing on sensing mechanisms (electrochemical, optical, and field-effect transistor), …

Counseling And The Neurodiversity Paradigm: A Call To Action, Emily Goodman-Scott, Rawn Boulden, Aaron Albright, Jenna Alvarez, Betsy M. Perez

Counseling & Human Services Faculty Publications

The counseling profession is rooted in prevention, wellness, mental health, and a critical social justice approach to serving historically marginalized communities, including people with disabilities. The overarching construct of disability comprises subtypes, such as neurodivergence. Given the prevalence of neurodivergent individuals worldwide (approximately 15%-20%), the counseling profession must be prepared to support this community. At the same time, there is a dearth of peer-reviewed literature on neurodiversity specifically for the counseling profession. In this article, we address a timely topic in the profession. We discuss utilizing a critical counseling lens and centering marginalized identities, such as people with disabilities; prominent …

A Macrocognitive Design Taxonomy For Simulation-Based Training Systems: Bridging Cognitive Theory And Human-Computer Interaction, Jessica M. Johnson

Virginia Digital Maritime Center (VDMC) Faculty Publications

Simulation-based training systems are increasingly deployed to prepare learners for complex, safety-critical, and dynamic work environments. While advances in computing have enabled immersive and data-rich simulations, many systems remain optimized for procedural accuracy and surface-level task performance rather than the macrocognitive processes that underpin adaptive expertise. Macrocognition encompasses higher-order cognitive processes that are essential for performance transfer beyond controlled training conditions. When these processes are insufficiently supported, training systems risk fostering brittle strategies and negative training effects. This paper introduces a macrocognitive design taxonomy for simulation-based training systems derived from a large-scale meta-analysis examining the transfer of macrocognitive skills from …

The Rise And Fall Of The Small Bronze Tripod Used For Pouring Heated Libations (A Pre-Confucian Libation Rite), Elizabeth Childs-Johnson

Art Faculty Publications

The rite of pouring out heated alcohol in honor of spirits begins during the Late Neolithic but matures as a formal institution known in writing and in cast bronze during the earliest phases of the historic Bronze Age, namely the Erlitou (ca. 1900-1600 BC) and Shang periods (ca. 1600-1046 BC). As will be analyzed, the libation rite known as ... [示 + 爵 = ...] (jue/guan) in Shang oracle bone divinations involved the use of the tripod jue爵 (bronze vessel). Although the rite [...] continues to appear in written inscriptions through most of the Western Zhou era, by the 9th-8th …

Exploring Healthcare Students' Perceptions About Race And Privilege At A Large Academic Medical Center: A Pilot Study Of A Peer Education Program, Elizabeth A. Brown, Dante Pelzer, Katrina Black Reed, Chinieka Jackman-Rogers, Madison Kimmell

Health Behavior, Policy & Management Faculty Publications

Amid the racial unrest stemming from the summer of 2020, in the United States, many institutions had difficult conversations about race and the impact of racism with employees, students, and patients. In January 2021 and February 2021, we recruited undergraduate students for the Peer Education Program (PEP), a voluntary program conducted at a large academic medical center, and encouraged students to have a safe space to discuss controversial topics in healthcare. From April 2021 to July 2021 four interdisciplinary healthcare students met once a month for 1 hr to discuss privilege, race/racism, leadership, and advocacy and their influence on health …

Advancing Food Equity Through Explainable Ai (Xai): Identifying Place-Based Factors And Conditions Of Food Security, Leslie Hoglund, Hyoshin Park

Health Behavior, Policy & Management Faculty Publications

Food behaviors, food security, and their association with socioeconomic factors constitute a critical area of study with implications for public health, economic stability, and social equity. Understanding these relationships are essential for developing effective policies and interventions that promote sustainable, healthy food systems and greater food equity. This paper employs explainable artificial intelligence (XAI) methods to identify key features influencing household food behaviors. The insights gained from the XAI analysis are further utilized in conjunction with inverse reinforcement learning (IRL) to examine expert behaviors related to eating habits satisfaction. The XAI results reveal that household health conditions, spending patterns, and …

Machine Learning: Thematic Feature Grouping, And The Magnificent Seven: A Forecasting Analysis, Mirarmia Jalali, Mohammad Najand, Andrew Cohen

Finance Faculty Publications

This study examines the predictability of monthly excess returns for the “Magnificent Seven” U.S. technology firms using machine learning and economically motivated thematic feature grouping. Framed as a focused study of the most systemically consequential equity panel in modern markets—seven firms representing over 30% of the S&P 500—the analysis confronts a small-N, large-P environment where economically structured dimensionality reduction is essential. Using 154 firm-level characteristics categorized into 13 economic themes, we evaluate linear, penalized, tree-based, and neural network models in a small-N, large-P setting. Unrestricted models suffer substantial overfitting and fail to outperform the historical average benchmark out-of-sample. In contrast, …

Natural Resource Rents And Energy Poverty Nexus In Next Eleven Economies, Muhammad Salah Uddin, Ayub Ali, Zobayer Ahmed, Md Nasir Uddin Sikdar, Ahsan Habib, Abdullah Elah Al-Mahde

Finance Faculty Publications

Energy poverty (EP) remains a persistent global challenge with important implications for economic development, public health, and social welfare. While natural resources, particularly oil and gas, are often viewed as key sources of energy access, their effectiveness in mitigating EP remains underexplored in emerging economies. This study examines the relationship between natural resource rents (NRR), specifically oil rents (OR) and natural gas rents (NGR), and energy poverty (EP) in the Next Eleven (N-11) countries from 2000 to 2020. The primary objective is to assess how NRR influences EP at various levels of poverty using the Method of Moments Quantile Regression …

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 …

Sleep Problems In Children With Adhd: Associations With Internalizing Symptoms And Physical Activity, Xiao Liang, Mengping Zhao, Li Su, Justin A. Haegele, Richard H. Xu, Jiayue Li, Jinxian Guo, Choi-Yeung Tse, Shirley X. Li, David H. K. Shum

Human Movement Studies & Special Education Faculty Publications

Children with attention deficit hyperactivity disorder (ADHD) experience high rates of sleep problems and are at increased risk for developing internalizing problems. This study aimed to examine the association of sleep problems and physical activity with internalizing symptoms in children with ADHD. This cross-sectional study included 188 children with ADHD (M age = 8.60 ± 1.38, 78.7% boys). Self-reported questionnaires were used to assess sleep problems (Pittsburgh Sleep Quality Index [PSQI]) and internalizing symptoms (Depression Anxiety Stress Scale 21 [DASS 21]). The presence of sleep problems was defined as a PSQI score > 5. Physical activity was recorded by an ActiGraph …

Can We Talk? A Correspondence Study To Examine Responsiveness Of Physical Educators To Requests For A Phone Call From Parents Of Children With Disabilities, Sean Healy, Justin A. Haegele, Steven K. Holland

Human Movement Studies & Special Education Faculty Publications

The Individuals with Disabilities Education Improvement Act (2004) mandates that parental input be considered when making educational decisions for children with disabilities, including in physical education. However, parents of children with disabilities often report suboptimal communication experiences with physical educators. The purpose of the current study was to examine if the initiation of a parent–physical educator relationship is influenced by whether students have a disability or not. An online message correspondence study methodology was used to detect potential disparities in the responsiveness of a sample of 320 physical educators to electronic message requests for a phone call to discuss physical …