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Injectable Hydrogels For Bone Regeneration: Mechanical Reinforcement Strategies Using Nanoparticles And Nanofibers: Review Paper, Fariba Ganji, Morteza Mirzagoli, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background and Purpose: The growing demand for bone regeneration following severe injuries highlights the importance of scaffolds in bone tissue engineering (BTE). Injectable hydrogels have emerged as promising candidates because their properties closely mimic the native extracellular matrix (ECM). However, their limited mechanical strength and structural instability restrict their practical application. Approach: This review summarizes recent strategies for reinforcing in situ-forming injectable hydrogels to improve their mechanical performance for bone regeneration. Particular emphasis is placed on nanomaterial-based strategies, including the incorporation of nanoparticles and nanofibers, and their ability to enhance the physical properties of polymeric networks. Key Results: Evidence from …

Comparative Assessment Of Energy And Emission Costs For Geothermal Heat Pumps And Fossil-Fuel Heating Systems Across U.S. Climatic Zones, Md Shahin Alam, Shima Afshar, Seyed Ali Arefifar, Mohammad Haq

Electrical & Computer Engineering Faculty Publications

In response to growing concerns over global warming and energy sustainability, transitioning from fossil-fuel-based heating systems to renewable alternatives is essential. This study evaluates the economic and environmental performance of geothermal heat pumps for building heating and compares it with conventional coal-fired boilers, natural-gas boilers, and diesel furnaces. Using the heating degree-day (HDD) method, heating energy demand was analyzed for four U.S. cities—Anchorage (AK), San Francisco (CA), Salt Lake City (UT), and Las Vegas (NV)—representing diverse climatic zones. The analysis integrates thermodynamic and economic parameters, including the coefficient of performance (COP = 2–5) and annual fuel-utilization efficiency (AFUE = 80–97%), …

Leveraging Virtual Reality And Haptics To Teach Surgical Skills: A Usability Study On Retropubic Midurethral Slings, Lauren Siff, Ginger S. Watson, Jerome Dixon, Moshe Feldman, Franklin Bost, Philippe J. Giabbanelli

VMASC Publications

Traditional methods to learn soft-tissue surgical procedures rely on cadaver labs or patient-based learning, which are costly and geographically limited, and raise ethical questions. Virtual reality (VR) with haptic feedback offers a scalable alternative, but most current platforms emphasize bone-based rather than soft-tissue procedures learned by feel. We developed a VR+haptic simulation for preoperative training of retropubic midurethral sling (MUS) surgery. This study examines the usability of this platform with thirteen expert urogynecologic surgeons and subsequently makes improvements (e.g., in haptics) to evaluate the platform with twelve trainees based on the NASA Task Load Index for workload and a UTAUT-informed …

Modeling Rank Distribution And The Relative Importance Factor Index In Discrete Power-Law Models: Application To Social Resilience Using The Scopus Database, Brian Llinas, Jose Padilla, Humberto Llinas, Erika Frydenlund, Katherine Palacio

VMASC Publications

Prior research on power-law distributions has primarily focused on modeling frequency patterns, with less attention given to rank distributions and how ranked positions reflect relative importance among elements. In discrete power-law distributions, frequency-based metrics often provide limited discrimination in the tail, where elements may exhibit similar counts but differ in relative dominance. These patterns are especially evident, for instance, in academic publishing, where keywords, affiliations, and citations commonly exhibit power-law behavior. To address this limitation, we introduce the Relative Importance Factor (RIF) Index, a statistical measure derived from the estimated discrete power-law rank distribution rather than an additional independent parameter. …

Standardization Of Neuromuscular Reflex Analysis—Role Of Fine-Tuned Vision-Language Model Consortium And Openai Gpt-Oss Reasoning Llm-Enabled Decision Support System, Eranga Bandara, Ross Gore, Sachin Shetty, Ravi Mukkamala, Christopher K. Rhea, Brittany S. Samulski, Amin Hass, Atmaram Yarlagadda, Shaifali Kaushik, Malith De Silva, Andriy Maznychenko, Inna Sokolowska, Kasun De Zoysa

VMASC Publications

Background/Objectives: Accurate assessment of neuromuscular reflexes, such as the Hoffmann reflex (H-reflex), plays a critical role in sports science, rehabilitation, and clinical neurology. Conventional interpretation of H-reflex electromyography (EMG) waveforms is subject to inter-rater variability and interpretive bias, limiting reliability and standardization. This study aims to develop an automated, interpretable, and robust agentic AI–driven framework for H-reflex waveform analysis. Methods: We propose a fine-tuned Vision–Language Model (VLM) consortium combined with a reasoning Large Language Model (LLM)–enabled decision support system for automated H-reflex interpretation. Multiple VLMs were fine-tuned on curated datasets of H-reflex EMG waveform images annotated with expert clinical observations, …

Distilling The Complexity Of Agent-Based Simulations Into Textual Explanations Via Large Language Models, Noé Y. Flandre, Philippe J. Giabbanelli

VMASC Publications

Communicating the design and results of agent-based models (ABMs) to subject matter experts is challenging, which hinders participation and limits trust in simulation-based decision support. Large language models (LLMs) can communicate ABMs as textual summaries, thus complementing traditional disclosure through statistical and visualization techniques. While prior work translated the structure of conceptual models into narratives via LLMs, our extension covers the dynamics of simulation models via an automated simulation-to-text method that extracts contextual information from NetLogo ABMs, performs repeated simulations, and generates narrative descriptions (including the model’s purpose, parameters, and simulation dynamics) using mutimodal LLMs. Furthermore, four summarization algorithms spanning …

Machine Learning Classification Of Prostate Cancer Genomic Sequences Using K-Mer And Sequence-Derived Features, Kuldeep Rawat, Hirendra Nath Banerjee, Jamie Noble, Saa Naudia Deloatch, Satyendra Banerjee, Sachin Shetty, Soumya Banerjee

VMASC Publications

Prostate cancer disproportionately impacts African American men, who experience significantly higher mortality rates and earlier disease onset than other populations. Current diagnostic approaches, including prostate-specific antigen testing and biopsy, lack sufficient specificity and sensitivity, underscoring the need for accurate, molecular-level classification tools. This paper presents a machine learning framework for binary classification of genomic DNA sequences as cancerous or healthy. A dataset of 1684 FASTA-formatted sequences obtained from the National Library of Medicine - GenBank was analyzed, with 1662 sequences retained after quality control filtering. Feature engineering yielded 67 attributes, including GC content, Shannon entropy, sequence length, and trinucleotide k-mer …

Sex Differences In Freezing Behavior And Extinction Learning Among Wistar Rats Exposed To Social Isolation And 15cgy Gcrsim Space Radiation Both Alone And In Combination, Zachary N. M. Luyo, Riley S. Heerbrandt, Alea F. Boden, Frederique E. E. Keumeni, Richard A. Britten, Laurie L. Wellman, Larry D. Sanford

Department of Biomedical and Translational Sciences Faculty Publications

Long-term space missions traveling beyond the Earth’s magnetosphere will expose astronauts to prolonged periods of social isolation (SI) and exposure to space radiation (SR). Throughout these missions, astronauts will have to cope with these stressors and adapt to their environment to carry out mission objectives. It is known that SI and SR can impact mission performance and overall health. Additionally, behavioral stress responses can differ between sexes. However, the independent and interactive effects of SI and SR on fear behavior and extinction learning between sexes is unknown. This study compared freezing behavior and stress-induced hyperthermia (SIH) in female and male …

Does Fishery Management For Groupers (Teleostei: Epinephelidae) Protect Them Effectively? Context From The Iucn's Red List Of Threatened Species, Sean T. Fennessy, Christi Linardich, Kevin Rhodes, Joao P. Barreiros, David Pollard, Eloy Sosa-Cordero, Felicia Coleman, Alfonso Aguilar-Perera, Christopher R. Malinowski, Thierry Brulé, Pedro Afonso, Kayan Ma, Min Liu, Muktha Menon, Colin Wen, Stanley K. H. Shea, Sean N. Porter, Matthew Craig, Yvonne Sadovy De Mitcheson

Biological Sciences Faculty Publications

Worldwide, groupers (Epinephelidae) are commercially valued fishes, which also play key ecological roles on tropical and subtropical reefs. In 2007 and 2016, the IUCN's Groupers and Wrasses Specialist Group assessed all 160+ grouper species, with 17 of these being identified as threatened in 2016 and the major threat factor being overexploitation. Our present study aimed to identify whether management measures (MMs) for previously assessed groupers were established, whether these measures aligned with IUCN's Red List categories, and whether they effectively protect grouper populations. Experts in grouper biology and management assigned scores per grouper species based on the extent to which …

The Coral Microbiome Under Climate Change: Shifting Symbiotic Interactions, Katherine E. Parker, Kate M. Quigley

Biological Sciences Faculty Publications

Host–microbe symbioses are central to organismal health, yet these complex partnerships are often strongly shaped by the environment. Climate change is increasingly altering environmental conditions, disrupting the balance of host–microbe interactions and pushing them along a continuum from mutualism (both partners benefit) toward parasitism (one partner gains at the other’s expense). Reef-building corals provide a clear example of this vulnerability, as the coral holobiont, an ecological unit comprising diverse photosynthetic algal symbionts (Symbiodiniaceae) and other microbial partners, depends largely on these mutualistic interactions for nutrition, immunity, and stress tolerance. Increasingly, evidence suggests that under heat stress, the algal symbionts retain …

Larval Genomics As A Viable, Fisheries-Independent Tool For Investigating Population Structure In Tropical Pacific Tunas, Jacob E. Jaskiel, Hannah E. Aichelman, Giulia Anderson, Louw Claassens, James E. Fifer, Christina M. Hernandez, Alexa K. Huzar, Joel K. Llopiz, Jan W. Witting, Sean P. Mullen, Randi D. Rotjan

Biological Sciences Faculty Publications

Understanding how dispersal, life history, and environmental variability shape genetic connectivity in the open ocean remains a central challenge in evolutionary biology. Highly migratory marine predators like tunas have traditionally been considered genetically homogeneous across ocean basins, yet emerging genomic evidence suggests that cryptic population structure can persist even in species with high gene flow and large effective population sizes. We used 2bRAD sequencing of 348 larval and subadult skipjack (Katsuwonus pelamis), yellowfin (Thunnus albacares), and bigeye tuna (T. obesus) collected from the central Pacific across 7 years of sampling to examine species boundaries, …

The Shoreline Protection Potential Of Oyster Reefs: A Systematic Review And Meta-Analysis, Jessica R. Fergel, Robert E. Isdell, Gabriella Dipetto, Karinna Nunnez, Sean T. Gregory, Evan Hill, Donna Marie Bilkovic

Biological Sciences Faculty Publications

Nature-based solutions for erosion control that incorporate oyster reefs, alone or in combination with other habitats, are an increasingly popular approach due to their potential to protect shorelines and enhance oyster production. However, the extent to which natural or constructed oyster reefs provide shoreline protection remains unclear. We conducted a global systematic literature review and meta-analysis to summarize and evaluate the potential of oyster reefs in attenuating waves, promoting sediment accretion, and/or reducing shoreline erosion. Factors extracted from studies included shoreline protective measures examined, oyster reef structure type, and oyster reef tidal location. The results of the meta-analysis showed generally …

Mitochondrial Genome Of The Indo-Pacific Mesophotic Coral Leptoseris Columna (Scleractinia: Agariciidae) Assembled Using Pacbio Long-Read Sequencing, Nomita Rani Adhikary, Daniel J. Barshis, J. Antonio Baeza

Biological Sciences Faculty Publications

Leptoseris columna, a mesophotic coral species belonging to the family Agariciidae, is distributed throughout the Indo-Pacific region. This species is considered as of "Least concern" by the IUCN, yet, faces multiple local and global stressors. To support conservation plans, this study sequenced and characterized the complete mitochondrial genome of L. columna. The complete mitochondrial genome of Leptoseris columna was assembled using PacBio long-reads with a coverage of 459× per bp. The AT-rich mitochondrial genome of Leptoseris columna is 18,546 bp long and comprises 13 protein-coding genes (PCGs), 2 transfer RNA genes (trnM and trnW), and 2 ribosomal RNA …

Acute Lower Leg Transcutaneous Electrical Nerve Stimulation Increases Leg Blood Flow And Exercise Capacity In Patients With Peripheral Arterial Disease, Thomas K. Pellinger, Catherine B. Neighbors, Joshua C. Hefta, Patrick H. Luo, Carl B. Suarez, Erotokritos T. Varlas, Grant H. Simmons, Brett J. Wong

EVMS School of Health Professions Faculty Publications

We tested the hypothesis that two different durations of lower leg transcutaneous electrical nerve stimulation (TENS) increase post-TENS popliteal artery blood flow (PABF), popliteal vascular conductance (PVC), and 6-min walk distance (6MWD) in patients with peripheral artery disease (PAD). Seven subjects (5 male, 2 female) with PAD (67.9 ± 7.4 years; claudication: ankle-brachial index (ABI) < 0.90) participated in three randomized treatment sessions: control or bilateral TENS (3.0 Hz burst mode, 250 µs) for either 15 or 45 min. PABF (Doppler ultrasound) was measured before and after treatment. 6MWD and time/distance to claudication onset were measured 25 min post-treatment during each session. PABF, PVC and 6MWD increased after both 15 and 45 min of TENS (P < 0.05, post-TENS vs. pre-TENS baseline/control). Our preliminary results suggest that as little as 15 min of lower leg TENS increases leg blood flow and exercise capacity in individuals with PAD.

Contextualizing The Aspe Standards Of Best Practice: Reflecting On The Past, Present, And Future Of Sp Methodology, Amelia M. Wallace, Cory Krebsbach, Janice Radway, Lou Clark

EVMS School of Health Professions Faculty Publications

As we celebrate the publication of the Association of SP Educators Standards of Best Practice (ASPE SOBP) for Physical Exam Teaching Associates (PETAs) and corresponding literature review, we, elected leaders of ASPE, offer reflections on SP methodology history, current practices, and future opportunities. Our aim is to contextualize this addition to what is now the third SOBP publication [1, 2] that guides the global simulation community on best practices of simulated participant (SP) methodology.

Thank you to the ASPE members and SP Educators who made time to share their expertise as authors on these new standards- in addition to their …

Part 4: Arts And Culture In Hampton Roads: Exploring A Challenging Future, Dragas Center For Economic Analysis And Policy, Old Dominion University

State of the Region Reports: Hampton Roads

Hampton Roads hosts a remarkably vibrant and dynamic arts and culture ecosystem. It includes not only high-caliber professional institutions such as the Virginia Arts Festival, Virginia Opera, Virginia Symphony Orchestra, and Chrysler Museum of Art—but many other museums and galleries, theaters and performance spaces, open-air festivals, creative districts, public art, independent artists and creators, large performance venues for outside talent, and a wide array of professional and amateur arts organizations. This chapter discusses the arts in Hampton Roads and explores its impact on the region.

Medical Image Feature Extraction And Selection Based On Inception V3 And Gini Index For Cervical Cancer Cells Identification, Rachida Assawab, Mounir Ouzir, Badreddine Benyacoub, Abderrahim Electrochemical Sensor For Tenofovir Allati, Ismail El Moudden

Research and Infrastructure Service Enterprise (RISE) Faculty Publications

Background: Cervical cancer remains the fourth most common cancer in women globally, with 604,000 new cases annually. Early detection through cytological screening is critical, but manual interpretation suffers from high false negative rates and requires expert pathologists often unavailable in resource-limited settings.

Methods: We developed a novel hybrid framework combining InceptionV3-based deep feature extraction with Gini Index feature selection for automated cervical cancer cell classification. Using the Herlev dataset (917 Pap smear images: 242 normal, 675 abnormal), we extracted 2048 deep features and applied systematic feature selection to identify optimal discriminative subsets. Comprehensive clustering analysis (K-means, K-medoid, Fuzzy clustering) validated …

Racial Differences In Adverse Pregnancy Outcomes And Incident Hypertension: A Mediation Analysis, Lucia C. Petito, Xiaoning Huang, C. Noel Bairey, Natalie Bello, Janet Catov, Ernesto Licon, Abbi Lane, David M. Haas, Lisa D. Levine, Rebecca B. Mcneil, Eliza Miller, Uma M. Reddy, Bethany Barone Gibbs, George Saade, Lauren Theilen, Laura E. Wiener, Brian M. Mercer, Hyagriv N. Simhan, Lynn M. Yee, Philip Greenland, William A. Grobman, Sadiya S. Khan

Department of Obstetrics & Gynecology Faculty Publications

Background

Adverse pregnancy outcomes (APOs) are associated with increased hypertension risk. Black women experience higher rates of APOs and hypertension compared with White women, but whether APOs contribute to Black-White hypertension disparities remains unknown.

Methods

The nuMoM2b-HHS (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be-Heart Health Study) prospectively recruited nulliparous pregnant people at 8 US centers (2010-2013) with follow-up 2 to 7 years postpartum (2014-2017). Race, which represents a social construct, was self-identified. The primary outcome was incident hypertension at follow-up. APOs included hypertensive disorders of pregnancy, preterm birth, and small-for-gestational age birth. Potential confounders (psychological health, social factors, and health behaviors) …

Srgan-Based Deep Learning Framework For Wind Turbine Damage Detection From Sentinel-2 Imagery, Kübra Çakir, Onur Elma, Murat Kuzlu

Engineering Technology Faculty Publications

The operational reliability of wind turbines is critical for sustainable energy production in smart grids. This study proposes a remote monitoring approach using perceptually enhanced satellite imagery. Sentinel-2 multispectral data (10 m resolution) has been processed with a Super-Resolution Generative Adversarial Network (SRGAN) to improve visual quality to a perceptual resolution of 30 cm. Although true spatial refinement is not achieved, the sharper structural details enhance classification accuracy. The data set comprises 15,000 images—10,000 SRGAN-enhanced and 5000 augmented through rotation, zoom in, increasing brightness, noise addition, and blurring. A custom Convolutional Neural Network (CNN) has been trained to classify turbines …

Interpretable Machine Learning For Bridge-Pier Scour Prediction And Flood Resilience, Adil Khan, Dalya Ismael

Engineering Technology Faculty Publications

Bridge-pier scour is a leading cause of flood-induced bridge failure, yet practice still lacks transparent, physics-informed tools that link data-driven prediction with design guidance. This study develops an interpretable, physics-aware machine-learning framework to predict equilibrium scour depth and translate those predictions into actionable strategies for flood-resilient infrastructure. Using the 2014 U.S. Geological Survey Pier-Scour Database (569 laboratory cases), five models: Gradient Boosting, AdaBoost (Tree), XGBoost, Gaussian Process (RBF kernel), and Kernel Ridge (polynomial), were trained and evaluated with K-fold cross-validation. Model performance was evaluated using R², RMSE, and MAE. Gradient Boosting performed best, achieving training and testing R² of 0.99 …

Generative Ai And Llm Applications In Renewable Energy And Smart Grids: A Systematic Review For The Sustainable Energy Transition, Umit Cali, Ugur Halden, Merlinda Andoni, Ferhat Ozgur Catak, Si Chen, Benoit Couraud, Emre Kantar, Samuel Knapper, Ibrahim Kucukdemiral, Huseyin Kusetogullari, Murat Kuzlu, Yashar Mousavi, Sonam Norbu, Taha Selim Ustun, David Flynn

Engineering Technology Faculty Publications

The global energy transition toward decarbonization and digitalization requires advanced methods to manage decentralized, data-intensive cyber-physical energy systems. This systematic review analyzes 106 research studies on Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) in renewable energy and smart grids, organized into seven application clusters covering forecasting, system design, operation, reliability, data and cybersecurity, and energy markets. The review situates these applications within a Cyber-Physical-Social Systems (CPSS) framework. Results show that GANs dominate current applications (47.2%), followed by LLMs (10.4%) and VAEs (9.4%), with growing adoption of diffusion and score-based models (7.5% each). Selected studies report improved probabilistic forecasting …

A Large Language Model-Based Academic Advising Assistant For Engineering Technology Students, Murat Kuzlu, Vukica M. Jovanovic, Katherine Smith, Otilia Popescu, Adel El-Shahat, Ryan Cotton, Kayla Marie Seegers, William Austin Henderson

Engineering Technology Faculty Publications

In recent years, Artificial Intelligence (AI)-based solutions, particularly Large Language Models (LLMs), have been applied to a variety of domains, such as energy, finance, transportation, healthcare, and education. Among these domains, education has become increasingly popular due to strong interest among educators and students. This study proposes an academic advising assistant system that uses LLMs to help Engineering Technology (ET) students plan their course load based on their educational history, departmental course offerings, and personal constraints, such as their preferred semester course load. The proposed LLM-based academic advising assistant system maintains a database of students' course histories and upcoming course …

Artificial Intelligence (Ai) In Educating Next Generation Of Engineering Technology Students, Adel El-Shahat, Murat Kuzlu, Vukica M. Jovanovic, Katherine Smith, Abdullah Al Mamun, Otilia Popescu

Engineering Technology Faculty Publications

Artificial Intelligence (AI) is transforming education, particularly for electrical engineering technology (EET) students, by presenting adaptive learning, immediate responses, and unconventional tools. Therefore, this paper proposes investigating modern learning to employ AI in educating future electrical engineering technology students. Firstly, the paper explores how to shape AI knowledge for EET students, supplying them with hands-on skills in AI tasks, clarifying coding, data analysis, and AI ethical usage. Then, as educators, what are the efficient AI tools to utilize in teaching, such as tailored tutoring, automated code assessment, AI-driven design/simulation, lecture dictation, and smart content creation? Key tools, for instance, Google …

Deep Learning-Based High-Resolution Spectrogram Reconstruction For Robust Bearing Fault Diagnosis, Sabyasachi Biswas, Saifur Rahman Tushar, Md Ebtidaul Karim, Abdullah Alam Mamun, Mahathir Mohammad Bappy

Engineering Technology Faculty Publications

Accurate and reliable bearing fault diagnosis is critical for the safe and efficient operation of rotating machinery. Conventional time–frequency (TF) analysis techniques, such as the short-time Fourier transform (STFT), are limited by their fixed window sizes and the inherent trade-off between time and frequency resolution, often leading to suboptimal fault representation under varying operating conditions. To address these challenges, this paper proposes a deep learning-based framework that reconstructs high-resolution, noise-robust TF representations directly from raw vibration signals. The proposed model integrates a denoising encoder with a learnable TF transformation network to adaptively capture fault related frequency patterns without manual parameter …

Limits Of Machine Learning For Predicting Stillbirth At Term: A Population-Based Cohort Of 302,192 Pregnancies In Northern Italy, M. Benuzzi, T. Kawakita, F. Monari, B. Melis, G. Guariglia, A. La Marca, I. Neri, G. Saade, F. Facchinetti, I. El Moudden

Department of Obstetrics & Gynecology Faculty Publications

Background

Objective

Study Design

Prepregnancy Overweight And Obesity In Kuwait Birth Cohort Study, Abdullah Al-Taiar, Ali H. Ziyab, Eelaf A. Husain, Maryam M.Y. Mohammad, Maryem A. Shamsah, Noor Salah Alali, Reem Sharaf-Alddin, Majeda S. Hammoud

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Objectives: This study aimed to estimate the prevalence of prepregnancy obesity and overweight, and to identify a set of sociodemographic factors that could guide weight management interventions for women prior to conception.

Design, Sample, and Measurements: Pregnant women (N = 989) were recruited in the Kuwait Birth Cohort Study during the period June 2017 to February 2020. Prepregnancy weight and height were self-reported, while current weight and height were measured in a standardized procedure. Data on sociodemographic factors were collected through face-to-face interviews conducted by a trained data collector. Multinomial logistic regression was used to investigate the association between sociodemographic …

The Impact Of Substance Abuse Problems And Serious Mental Illness/Serious Emotional Distress On Post-Discharge Residential Status Among Clients With Behavioral And Cognitive Disorders: Evidence From Samhsa Mh-Cld Data, Eden Moges, Norma Rochez, William Peycha, Aditya Chakraborty

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

BACKGROUND: Behavioral and cognitive disorders can undermine housing stability, a key determinant of mental health recovery, with persistent disparities across demographic and socioeconomic groups. This study examined the associations of substance abuse problems (SAP) and serious mental illness/serious emotional distress (SMISED) with residential status at discharge from mental health facilities.

METHODS: This cross-sectional study used the utilized data from the Substance Abuse and Mental Health Services Administration (SAMHSA). Descriptive statistics were used to summarize demographic characteristics, whereas univariate and multivariable logistic regression models were employed to assess associations between the covariates and the residential outcome, adjusting for a variety of …

Paneugenesis: A Regenerative Systems Hypothesis For Advancing Health Promotion, Craig M. Becker, Leslie Hoglund, Beth Chaney, Joseph G. L. Lee, Michael Stellefson, Alex Davis

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Despite major advances in health promotion science, dominant approaches remain largely prevention-and risk-reduction-oriented. The prevailing orientation creates a substantial opportunity to advance generative, system-design strategies that intentionally produce well-being rather than merely prevent disease. This article proposes paneugenesis as a regenerative systems framework and a testable theoretical model for the intentional creation of net-positive outcomes, thereby extending health promotion beyond its traditional pathogenic emphasis. Paneugenesis integrates systems science, salutogenesis, behavioral science, complexity theory, and quality management principles into a unified four-function process: operationalizing idealized outcomes, identifying key precursors, optimizing processes, and continually plotting progress through feedback mechanisms. The central hypothesis …

The Moderating Role Of Social And Emotional Support In The Association Between Adverse Childhood Experiences And Adult Mental Health Across Racial Groups: The Need For Investing In Social Capital, Syeda S. Jesmin, Aditya Chakraborty

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background

The sustained impact of Adverse Childhood Experiences (ACE) on mental health outcomes in adulthood is well documented in the literature. ACE survivors may be especially vulnerable to poor mental health outcomes if they have limited or no social support. This study examined the moderating role of social support on the association of ACEs and mental health across different racial groups.

Methods

Data were obtained from the 2022 Behavioral Risk Factor Surveillance System (n = 14,327). The nine ACE questions about traumatic events in childhood were used to create ACE scores. Chi-square tests were used for bivariate comparisons. Both stratified …

Modeling Healthcare Data With Logistic Quantile And Uniform-Based Mixture Polynomial Distributions, Mohan D. Pant, Aditya Chakraborty, Jovanna A. Tracz

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Continuous healthcare data often deviate from normality, which can substantially increase the risk of making invalid inferences, given that many inferential statistical procedures rely on normality assumption. To obviate this issue, we propose a new family of non-normal distributions based on a linear combination of the quantile functions of standard logistic and uniform (0, 1) distributions. This new family of non-normal distributions is studied within three different methods: L-moments, conventional moments, and percentiles. Its performance is compared among the three methods in the context of parameter estimation and data modeling. The results of Monte Carlo simulation and bootstrapping techniques indicate …