Digital Commons Network^™

Explainable Physics-Based Constraints On Reinforcement Learning For Accelerator Optimization, Jonathan Colen, Malachi Schram, Kishansingh Rajput, Armen Kasparian

Data Science Faculty Publications

We present a reinforcement learning (RL) framework for optimizing particle accelerator experiments that builds explainable physics-based constraints on agent behavior. The goal is to increase transparency and trust by letting users verify that the agent’s decision-making process incorporates suitable physics. Our algorithm uses a learnable surrogate function for physical observables, such as energy, and uses them to fine-tune how actions are chosen. This surrogate can be represented by a neural network or by an interpretable sparse dictionary model. We test our algorithm on a range of particle accelerator optimization environments designed to emulate the Continuous Electron Beam Accelerator Facility at …

Applying Transfer Learning For Street-Scale Nuisance Flood Forecasting In Coastal-Urban Environments, Binata Roy, Jonathan L. Goodall, Diana Mcspadden, Chetan Kumar, Steven Goldenberg, Yidi Wang, Malachi Schram

Data Science Faculty Publications

An important challenge with Machine Learning (ML) is its transferability; that is, whether an ML model trained on one set of data can be applied to a second set of data without requiring full retraining of the model. Transfer Learning (TL) addresses this challenge by transferring knowledge learned in the source domain (the data it was trained on) to the target domain (a second set of data that is statistically different but related, which the model was not trained on). This study investigates the use of TL for street-scale nuisance flood forecasting by exploring whether an ML model trained for …

Microfluidic Encapsulation Of Sorafenib-Loaded Zif-8 Nanoparticles In Ph-Responsive Alginate Microparticles For Oral Chemotherapy Of Hepatocellular Carcinoma, Mojdeh Mirshafiei, Zahra Mahmoudi, Mehdi Mehrpouya, Mahdi Mahmoudi, Masoud Rezaeian, Mona Navaei-Nigjeh, Zahra Katoli, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related mortality. Sorafenib is the current first-line oral therapy; however, its therapeutic efficacy is limited by poor aqueous solubility, low bioavailability, and gastrointestinal instability. This study aimed to develop a pH-responsive nano-in-microparticle delivery system using a single-step droplet-based microfluidic process to protect sorafenib in the gastric environment and achieve controlled release for enhanced oral chemotherapy. Sorafenib-loaded ZIF-8 nanoparticles (SZ NPs) were synthesized and characterized by scanning electron microscopy (SEM), Fourier-transform infrared (FTIR) spectroscopy, Energy-dispersive X-ray (EDX) spectroscopy, and X-ray diffraction (XRD), exhibiting a mean diameter of about 72 nm and …

Healthcare Digital Twins: A Methodological Literature Review On Integrating Iot And Ai For Personalized Medicine And Predictive Care, Sara Shahnazinia, Mahsa Tavasoli, Abdolhossein Sarrafzadeh, Ali Karimoddini

Electrical & Computer Engineering Faculty Publications

Digital Twin (DT) technology has the potential to revolutionize healthcare delivery and enhance patient outcomes through personalized and precision medicine, simulation models for operations and interventions, and drug discovery. However, successful implementation of DTs in Internet of Things (IoT) and artificial intelligence (AI) healthcare is contingent upon addressing key challenges such as privacy, ethics, and robust data security. This paper presents a methodological literature review of DT applications in healthcare, systematically analyzing the current state of research, key enabling technologies, and implementation challenges. The review summarizes DT categorization approaches (application-based, technology-based, and real-time function-based); delineates core DT components such as …

Gem-Can: A Real-World Dataset Of Can-Bus Attack Scenarios On An Autonomous Vehicle For Intrusion-Detection Research, Mahsa Tavasoli, Abdolhossein Sarrafzadeh, Ali Karimoddini, Tienake Phuapaiboon, Milad Khaleghi, Daniel Tobias

Electrical & Computer Engineering Faculty Publications

This paper presents GEM-CAN, a labelled Controller Area Network (CAN) dataset captured from an autonomous GEM e6 platform under both normal operation and controlled cyber-attack conditions.

The dataset contains ∼143 K frames comprising (i) ∼ nominal autonomous operation (∼100k messages), (ii) DoS floods using arbitration ID 0 × 00000000 (∼41 K messages), and (iii) data-tampering injections that reuse legitimate IDs for brake and steering-lock (∼1.3 K messages). Each record includes timestamp, arbitration ID (11/29-bit), DLC, eight payload bytes, and a Normal/Attack label. A companion metadata file enumerates attack windows, PCAN bus-load traces, bitrate, and test conditions. Data were collected with …

Technological Interventions For Reducing Climate Change Impacts On Health: An Overview Of Future Possibilities, Sujatha Alla, Vijay Kumar Chattu, Bawa Singh

Engineering Management & Systems Engineering Faculty Publications

Globally, over five million deaths annually are attributed to extreme weather events exacerbated by climate change, such as heatwaves, hurricanes, wildfires, droughts, and floods, which create health crises and economic losses. The 2015 Paris Declaration emphasized climate technology mechanisms, including research and development, to enhance resilience and reduce greenhouse gas emissions. Biotechnological advancements have mitigated about 20% of economic losses since the 1960s, highlighting technology’s potential to address climate-induced health risks.

A Three-Stage Causal Root-Cause Diagnostic Protocol For Nonstationary Industrial Time Series Data, Cansu Yalim, Resit Unal, Holly A. H. Handley

Engineering Management & Systems Engineering Faculty Publications

Predictive maintenance (PdM) systems effectively forecast failures, but they often fail to find root causes, particularly when system dynamics change over time. This limitation arises from applying static causal models or decoupled segmentation to handle nonstationary industrial time series. For regime-aware causal diagnostics and interventional effect estimation, we introduce a three-stage time-varying dynamic Bayesian network (TV-DBN) protocol. Using a minimum description length (MDL) objective that connects segmentation to mechanism changes, Stage I jointly infers change points and regime-specific graph structure. Stage II produces a completed partially directed acyclic graph (DAG) by orienting edges within each regime using a combination of …

Seeing The Invisible Load: Xr+ Multimodal Sensing For Cognitive Ergonomics In Industrial Training, Jessica M. Johnson, Andwele Grant

Virginia Digital Maritime Center (VDMC) Faculty Publications

Extended reality (XR) technologies are increasingly positioned as disruptive Industry 5.0 tools for human-centric industrial training and intelligent human–system integration. Coupled with multimodal sensing (eye tracking, EEG, HRV, GSR, and other physiological signals), XR environments promise to make otherwise invisible cognitive demands observable, especially for novice trainees entering complex industrial settings. Yet the evidence base is fragmented: (1) there is no quantitative synthesis of the cognitive ergonomics benefits of XR plus sensing; (2) little is known about which XR–sensor configurations yield the strongest effects; (3) prior reviews rarely focus on industrial and manufacturing tasks; (4) multimodal signals are used predominantly …

Make It Maritime: A Simulation-Based Engineering Design Challenge Using Multimodal Technologies, Jessica M. Johnson, Jennifer Renne, Jason Dudley

Virginia Digital Maritime Center (VDMC) Faculty Publications

This paper presents The Incredible Bulk, a multimodal, simulation-based engineering challenge that introduces Grades 4–12 to maritime careers and digital transformation. Students assume the roles of different maritime careers to assemble aircraft carrier bulkhead systems using: VR for spatial orientation and task preview; a 3D model as visual work instruction; paper blueprints for part identification and dimensioning; 3D-printed components for hands-on assembly; and an AR app for quality assurance/inspection. Grounded in constructionism and cognitive apprenticeship, the plan–build–inspect loop externalizes thinking and situates coached, authentic practice that advances engineering design, systems thinking, and technological literacy.

Redefining Educational Technology: A Critical Collaborative Inquiry, Aras Bozkurt, Helen Crompton, Robert Farrow, Agnes Kukulska-Hulme, Jon Dron, Richard West, Agnieszka (Aga) Palalas, Matth Bower, Junhong Xiao, Ahmed Tlili, Danah Henriksen, Angelica Pazurek, Henk Huijser, Thomas K. F. Chiu, Petar Jandrić, Katy Jordan, John Curry, Royce Kimmons, Mutlu Cukurova, Thomas Reeves, Gwo-Jen Hwang, Peter Shea, Jason Lodge, Martin Weller, Davy Ng, Tutaleni Iita Asino

STEMPS Faculty Publications

Educational technologists have not settled on a fixed definition of the field and likely never will. However, attempting to define the field helps to understand the epistemological meanings that shape what the field sees, values, and considers worth pursuing. Through a critical historical review spanning over a century, alongside theoretical engagement with the concepts of entanglement and distributed agency, this paper identifies three key insufficiencies in current educational technology frameworks. These are the persistence of an instrumental-facilitative paradigm that treats technology as a resource deployed by human agents; the theoretical dissolution of the pedagogy-technology dichotomy that existing definitions have not …

Co-Curricular Science Experiences Support Undergraduate Students' Science Gpa, Degree Completion, Workforce Entry, And Motivation, Lisa Linnenbrink-Garcia, Tony Perez, Stacy J. Priniski, Sharlyn Ferguson-Johnson, John Keane, Alexandra Lee, Kristy A. Robinson, You-Kyung Lee, Goun Choi, Matthew J. Schell, Danielle N. Berry, Rochelle Schwatz-Bloom

STEMPS Faculty Publications

Science co-curricular experiences (SciXP)-such as research experiences and internships-are a common, yet understudied, strategy to enhance undergraduates' science career pursuit. Using a doubly robust method to account for initial differences in science motivation, academic readiness, and career intentions, we investigated whether SciXP participation across four years of college predicted undergraduates' (N = 1984) science achievement, career persistence, and motivation at the end of college and after graduation. Participation in science co-curricular experiences was positively associated with science GPA, earning a science degree, being in a more science-intensive career one to two years post-graduation, and viewing science as important and useful …

Rapid Urbanization Reduces Genetic Diversity And Increases Genetic Differentiation Of A Lynx Spider Oxyopes Sertatus In Central Taiwan, Ying-Yuan Lo, Chi Wei, Wan-Jyun Chen, Chung-Ping Lin

Biological Sciences Faculty Publications

Urbanization is a dominant force driving destructive and irreversible changes of natural habitats in modern times. While the effects of urbanization on community composition and phenotypic responses are well-documented, its influence on genetic diversity and population structure remains understudied, particularly for invertebrates in subtropical regions. This study tested the hypothesis that urbanization reduces genetic diversity and increases population differentiation in the lynx spider Oxyopes sertatus, a common foliage-dwelling spider in Taiwan. We sampled 245 individuals from 17 sites distributed along an urban-rural gradient and quantified urbanization intensity using land-use composition at both landscape (4 km²) and local (0.25 km²) …

Evaluating Species At Risk In Data-Limited Fisheries: A Productivity-Susceptibility Analysis For Marine Aquarium Fish, Gabrielle A. Baillargeon, Alice A. Wynn, Jemelyn Grace P. Baldisimo, Michael F. Tlusty, Andrew L. Rhyne

Biological Sciences Faculty Publications

The marine aquarium trade (MAT) is a significant global industry harvesting millions of wild-caught, live coral reef fishes for public and private aquaria markets in the United States and Europe annually, while supporting fisher livelihoods in the Indo-Pacific. This diverse and species-rich trade is considered data-limited, creating barriers to quantifying the current and future socio-ecological sustainability of the fishery. We present a revised and expanded productivity–susceptibility analysis (PSA) that serves as a holistic risk assessment to estimate the vulnerability of marine aquarium fish to overfishing. Our global analysis includes 306 species that are actively in trade. Improvements to the PSA …

The Devil Is In The Det[Ai]Ls: Ai Agents, Ghost Students, And The Crisis Of Verified Presence In An Agentic Ai World, Aras Bozkurt, Helen Crompton, Caroline Fell Kurban

STEMPS Faculty Publications

The transition from reactive Generative Artificial Intelligence (GenAI) to agentic AI systems marks a categorical shift in digital education, moving beyond simple content generation to goal-oriented, autonomous execution. This paper explores the emergence of the “ghost student”: a digital surrogate created by the coupling of Large Language Models (the “mind”) and agentic AI browsers (the “body”). These entities are capable of navigating Learning Management Systems (LMS), engaging with content, and completing assessments with human-like mimicry, often rendering the actual learner’s presence optional. We argue that this phenomenon creates a verification gap that traditional proctoring and detection tools are structurally unable …

Chatgpt In Secondary English Language Learning: Educators' And Students' Literacy, Perceptions, And Experiences, Victoria Brenes, Sierra Outerbridge, Xinyue Ren

STEMPS Faculty Publications

The increasing use of generative artificial intelligence (GenAI) has shown the potential of transforming teaching and learning practices in various educational settings, such as in English language learning (ELL). As English language learners (ELLs) often experience many challenges and barriers in schools in the United States, it is urgent to leverage the educational affordances of GenAI in fostering the effectiveness of ELL. Given the limited research investigating GenAI adoption, especially ChatGPT literacy within K-12 ELL, this convergent mixed methods research aims to investigate students' and teachers’ perceptions of using ChatGPT and their ChatGPT literacy in secondary ELL contexts. We will …

A Comparison Of Conversational Chatbots And The Internet For Consumer Information Search, Wondwesen Tafesse, Yoseph Mamo

STEMPS Faculty Publications

This study compares consumer perceptions of conversational chatbots and the internet for information search. While the internet is a mature platform, conversational chatbots represent an emerging technology, and insight into how consumers view them in relation to the internet for information search is lacking. Drawing on the information source utility perspective, the study builds a comparative model based on four key dimensions: information currency, information customisation, information trustworthiness, and media richness. Additionally, the study investigates consumers’ prior experience with conversational chatbots as a moderating factor. Data was collected from 191 respondents recruited through MTurk. Paired sample t-tests assessed mean differences …

Climate Change Impacts On Hydrology In The Upper James Watershed, Imiya Mudiyanselage Chathuranika, Dalya Ismael

Engineering Technology Faculty Publications

Hydrological modeling of the Upper James Watershed (UJW), Virginia, is critical for predicting water availability, flood management, agriculture, ecosystem protection, and hydropower production under increasing climate change. The Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) is applied to evaluate climate change impacts on key hydrological components within the watershed. Future climate conditions were assessed for the near (NF: 2026-2050), mid (MF: 2051-2075), and far (FF: 2076-2100) periods using three Global Climate Models (GCMs) under Shared Socioeconomic Pathways SSP 2-4.5 and SSP 5-8.5. Climate data were bias-corrected using the Linear Scaling Method (LSM) and used to drive the HEC-HMS model. Results project …

Identifying Industry-Preferred Automation Software In Engineering: An Indeed-Based Analysis To Inform Engineering Technology Curriculum Design, Triet Minh Phan, Collins Okafor, Winifred Okafor, Devang Mehta, Mohsen Souissi, Jenora Waterman, Connie Mayberry, Misty Thomas, Orlando Ayala, Angie Price, Maurizio Manzo

Engineering Technology Faculty Publications

In the evolving field of automation engineering, staying aligned with industry software demands is critical to preparing graduates for the modern workforce. This study investigates the prevalence of leading industrial automation platforms—Rockwell / Allen-Bradley (RSLogix / Studio 5000), Siemens (TIA Portal / Step 7), and Schneider Electric (EcoStruxure / Unity Pro)—across job postings collected from Indeed using the keyword "automation engineering." The research compiles a structured dataset of job postings with seven fields: ID, Job Title, Organization, Rockwell / Allen-Bradley, Siemens, Schneider Electric, and Posting URL. Each entry is manually coded to indicate whether the listed software platforms are mentioned, …

Improving Medical Diagnostics With Vision-Language Models: Convex Hull-Based Uncertainty Analysis, Ferhat Ozgur Catak, Murat Kuzlu, Taylor Patrick, Michel Audette

Engineering Technology Faculty Publications

In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. However, concerns remain regarding VLMs’ consistency and uncertainty, particularly in critical applications such as healthcare, which demand a high level of trust and reliability. This paper proposes a novel approach to evaluate uncertainty in VLMs’ responses using a convex hull approach on a healthcare application for visual question answering (VQA). For any VLM, temperature refers to a sampling parameter used in probabilistic generation, which controls the randomness of the model’s output. The LLM-CXR model is selected as the medical …

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 …

A Methodological Framework For Modernizing Engineering Course Content With Large Language Models, Katherine Smith, Dalya Ismael, Otilia Popescu, Murat Kuzlu, Adel El-Shahat, Vukica M. Jovanovic

Engineering Technology Faculty Publications

The rapid evolution of technology presents challenges for engineering educators. While the core engineering methods often remain relevant over time, course materials rapidly become outdated in presentation and pedagogical approach. This paper presents a methodological framework for using large-language models (LLMs) to modernize engineering course content with a case study in an advanced technical analysis course.

The methodology follows a phased approach that is designed to be repeatable and verify the accuracy and completeness of course content. During the first phase, an LLM is used to map outdated text-heavy content to a modern format using a LaTeX template. The second …

Flood-Season Surface Water-Groundwater Interactions Across Distinct Geomorphic Units In A Yellow River Great Bend Tributary Basin, Yinlong Wang, Ruizhong Gao, Debin Jia, Xixi Wang, Tingxi Liu, Xiaomin Liu, Shiming Bai

Civil & Environmental Engineering Faculty Publications

Surface water-groundwater interactions are complex in the Great Bend region of the Yellow River. Clarifying water exchange and source differences among geomorphic units is important for understanding regional hydrological processes and improving water resources management. In this study, the Wulanmulun River Basin, a typical tributary of the Yellow River, was selected as the study area. A total of 90 water samples were collected, including 25 river water samples, 43 groundwater samples, and 22 precipitation samples. Gibbs diagrams, multivariate statistical analysis, PMF, and MixSIAR models were used to investigate the hydrochemical and isotopic characteristics, source contributions, and transformation relationships of surface …

Nanosecond Pulsed Electric Fields For Extracellular Vesicle Engineering: From Electro-Exocytosis To Cargo Modulation, Art Neal, Teresa Graham, Mohamadmahdi Samandari, Arash Ghorbannia, Anca Dobrian, Stephen J. Beebe, Ruben M. L. Colunga-Biancatelli

Bioelectrics Publications

Extracellular vesicles (EVs), including small extracellular vesicles (sEVs) and medium/large extracellular vesicles (MVs), have emerged as promising therapeutic vectors and diagnostic biomarkers across various branches of biomedicine. However, the clinical translation of EV-based technologies remains constrained by persistent challenges in manufacturing: insufficient yield from primary cell sources, limited control over cargo composition, and the absence of scalable, standardized production platforms. Nanosecond pulsed electric fields (nsPEF) represent an emerging biophysical approach that can address several of these limitations. Unlike conventional electroporation, which targets the plasma membrane using microsecond-to-millisecond pulses, nsPEF delivers ultrashort (1–300 ns), high-amplitude (10–300 kV/cm) pulses that penetrate intracellularly …

A Complete Diploid Human Genome Benchmark For Personalized Genomics, Nancy F. Hansen, Nathan Dwarshuis, Hyun Joo Ji, Arang Rhie, Hailey Loucks, Glennis A. Logsdon, Mitchell R. Vallger, Jessica M. Storer, Juhyun Kim, Eleni Adam, Nicolas Alternose, Dmitry Antipov, Mobin Asri, Sofia Barreira, Stephanie C. Bohaczuk, Andrey V. Bzikadze, Sara A. Carioscia, Andrew Carroll, Kuan-Hao Chao, Yanan Chu, Arun Das, Peter Ebert, Adam English, Mark Fleharty, Laura E. Fleming, Giulio Formenti, Andrea Guarracino, Gabrielle A. Hartley, Katharine Jenike, Jenna Kalleberg, Yu Kang, Robert King, Josipa Lipovac, Mira Mastoras, Matthew W. Mitchell, Shloka Negi, Nathan D. Olson, Keisuke K. Oshima, Luis F. Paulin, Brandon D. Pickett, David Porubsky, Jane Ranchalis, Desh Ranjan, Mikko Rautiainen, Harold Riethman, Robert D. Schnabel, Fritz J. Sedlazeck, Kishwar Shafin, Mile Sikic, Steven J. Solar, Alexander P. Sweeten, Winston Timp, Justin Wagner, Dongahn Yoo, Ying Zhou, Erik Garrison, Evan E. Eichler, Michaeel C. Schatz, Andrew B. Stergachis, Rachel J. O'Neill, Karen H. Miga, Steven L. Salzberg, Sergey Koren, Justin M. Zook, Adam M. Phillippy

School of Medical Diagnostics & Translational Sciences Publications

Human genome sequencing typically relies on mapping reads to a reference genome to call variants, but this approach introduces technical biases, excluding duplicated and structurally polymorphic regions of the genome. To overcome this, we present a telomere-to-telomere genome benchmark with near-perfect accuracy across 99.4% of the diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), which were absent from prior benchmarks. We annotated genes and repeats on both haplotypes, including 19,956 protein-coding genes on the maternal haplotype and 19,190 on the paternal haplotype, and developed new methods to measure the accuracy of …

Role-Differentiated Ai Competencies And Curriculum Implications For Health Professions Education: Qualitative Study, Yuyi Park, Yejin Han, Hyeongjo Kim, Solmoe Ahn, Frederick William Kron, Jihyun Lee

Department of Family and Community Medicine Faculty Publications

Background: As AI fundamentally transforms the healthcare landscape, medical education curricula have struggled to keep pace with these technological shifts. While current research has established a foundation for general AI literacy, less attention has been given to the role-specific competencies required for the diverse functions that healthcare professionals perform in an AI-integrated environment. Although existing tiered and domain-based competency models have clarified general AI competency requirements, they offer limited guidance on how such competencies should be differentiated according to the roles healthcare professionals perform in practice.

Objective: This study aimed to explore how AI-driven changes in healthcare shape competency requirements …

Pt/Zno-Decorated Laser-Induced Graphene For Nonenzymatic Glucose Monitoring Under Physiological Conditions, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Diabetes continues to impose significant global health and economic burdens, driving the demand for robust, enzyme-free glucose sensors capable of reliable operation under physiological conditions. Here, we report the development of a high-performance nonenzymatic glucose sensor based on laser-induced graphene (LIG) modified with zinc oxide (ZnO) and platinum (Pt) nanostructures. ZnO was electrodeposited onto LIG with modulation potential and deposition duration systematically optimized. The ZnO/LIG electrodes were characterized electrochemically using potassium ferricyanide and evaluated for glucose oxidation in phosphate-buffered solution. Subsequent electrodeposition of Pt under analogous optimized conditions yielded a ternary Pt/ZnO/LIG architecture with enhanced electrocatalytic activity. Sensor performance was …

Bridging Mission And Execution: Integrating Participatory Design In Early-Phase Mission Engineering For Stakeholder Alignment And Mission Clarity, Rafi Soule

Knowledge and Creativity Expo

This research examines mission framing during the early phase of Mission Engineering. Stakeholder interpretations diverge under ambiguity. Interoperability constraints are often not surfaced early. These conditions reduce mission clarity and weaken mission-to-system mapping readiness. The study integrates a participatory design-inspired, artifact-first workflow with RAG-enabled retrieval from a closed corpus to support evidence-grounded reasoning and traceable citations.

Phase 1 uses an online survey to establish baseline patterns in practice (N = 86). Shared understanding is positively associated with mission clarity (r = 0.60, p < 0.001). Phase 2 uses a time-bounded comparative workshop with two conditions. Expert reviewers rate mission statement quality higher for the participatory design condition (mean 3.5) than the traditional condition (mean 2.8). Technical feasibility ratings are similar across conditions. Phase 3 demonstrates RAG-enabled, closed-corpus, retrieval-supported traceability using the Referencer tool. It is reported as a proof-of-concept for evidence-grounded rationale and auditability, and as a pathway …

Using A Study Journal To Support Class Engagement And The Development Of Entrepreneurial Mindset Habits, Otilia Popescu, Dimitrie C. Popescu

Engineering Technology Faculty Publications

Engineering Technology programs were historically introduced to support non-traditional students and offer college pathways for students working and having already a developing career. This is even more true in the current academic environment, with a large percentage of students enrolled in engineering technology programs being either fully or part-time employed, active or retired military, and at different stages in their lives, usually with families to care for. Often, non-traditional students attend classes online, either synchronously or even more often asynchronously, due to their schedule constraints. Course instructors regularly face schedule or time management constraints from the students’ side, and they …

Criterion Validity Of The Functional Status And Pain Assessment Scale Versus Pain And Length Of Stay In Hospitalized Adults With Scd, Wally R. Smith, Daniel M. Sop, Yue May Zhang, Margaret S. Guy, Rehan Qayyum

Department of Medicine Faculty Publications

Objectives

In prior research we demonstrated face, construct, discriminant, and preliminary convergent validity of the newly developed, 10-item Functional Status Pain Assessment (FSPA) scale (0-50) in adult SCD patients hospitalized with VOC. We aimed in this study to further demonstrate criterion validity of the FSPA.

Methods

This was a prospective observational study of 561 daily functional and pain assessments from 91 hospitalized adults with SCD from January 2018 to June of 2019. Principal Component Analysis (PCA) Partial Least Squares (PLS) models determined the relationship between LOS, pain intensity, and FSPA. A Generalized Linear Model (GLM) to quantified the impact of …

Circulating Biomarker Results From A Phase 2 Study Of Seralutinib In Pulmonary Arterial Hypertension, Robin Osterhout, Athénaïs Boucly, Raymond L. Benza, Richard N. Channick, Kelly M. Chin, Robert P. Frantz, Anna R. Hemnes, Luke S. Howard, Vallerie V. Mclaughlin, Olivier Sitbon, Jean-Luc Vachiéry, Rotham T. Zamanian, Richard Aranda, Matt Cravets, Zhaoqing Ding, Thao Duong-Verlé, David Mattola, Robert F. Roscigno, Ravikumar Sitapara, Lawrence S. Zisman, Jean-Marie Bruey, Hossein-Ardeschir Ghofrani

Department of Medicine Faculty Publications

[Introduction] To the Editor: Pulmonary arterial hypertension (PAH) is a progressive disease characterized by obstructive pulmonary arterial remodeling (1). Seralutinib, an investigational inhaled tyrosine kinase inhibitor, potently and selectively targets kinases relevant to PAH pathobiology including platelet-derived growth factor receptors (PDGFR) α and β, colony stimulating factor 1 receptor (CSF1R), and mast/stem cell growth factor receptor kit (c-KIT) (2). In preclinical models, seralutinib improved cardiopulmonary hemodynamics, reversed pulmonary vascular pathology and decreased right ventricular hypertrophy (3). In TORREY, a phase 2, multicenter, double-blind, randomized, placebo-controlled trial in PAH, seralutinib significantly reduced pulmonary vascular resistance (PVR) after 24 weeks with good …