Digital Commons Network^™

Healthlitpro™: Development Of An Ai Driven Audit & Feedback Tool For Organizational Health Literacy, Carol J. Howe, Yunhe Feng, Song Fu, Donger Chen, Lindsey Patton

2025

RESEARCH

Purpose: Organizational Health Literacy (OHL) refers to the ability of healthcare institutions to support patients and families to access, understand, and use health information. Nurses play a key role in OHL using evidence-based health literacy practices (i.e. plain language, teach-back, open-ended questions, chunking information, and three to five key points) when educating patient families. Yet, implementation is challenging. Audit and Feedback (A&F) is an implementation strategy for promoting fidelity to health literacy practices. Conventionally requiring expert human evaluations that are costly, labor-intensive, and difficult to scale.

Methods: HealthLit was trained using a dataset of simulated nurse-patient education …

The Global Hypophosphatasia Registry: Lessons Learned From A Decade Of Real-World Data., Priya S. Kishnani, Lothar Seefried, Keiichi Ozono, Gabriel Ángel Martos-Moreno, Cheryl Rockman-Greenberg, Deborah Fowler, Luke K. Burke, William R. Mowrey, Eric T. Rush, Peter R. Ebeling, Wolfgang Högler, Agnès Linglart, Shona Fang, Anna Petryk, Kathryn M. Dahir

Manuscripts, Articles, Book Chapters and Other Papers

INTRODUCTION: Hypophosphatasia (HPP) is an inherited, metabolic, rare disease characterized by a high level of clinical heterogeneity. In response to this robust heterogeneity, the Global HPP Registry was formed to characterize the types of manifestations that patients may experience, as well as to compile information on genetic underpinnings of the disease, overall impact on patient quality of life, and safety and effectiveness of enzyme replacement therapy. The objective of this review was to synthesize key learnings gained from the Global HPP Registry, which is now in its tenth year of enrolling patients.

METHODS: Registry data were analyzed to provide up-to-date …

Development And Applications Of A Health Equity Summary Score Using The Medical Expenditure Panel Survey, Ronald R. Sanchez

Dissertations and Theses

Despite sustained national efforts, disparities in healthcare delivery persist among racial and ethnic minorities, low-income individuals, and socially at-risk populations. Monitoring modifiable aspects of care delivery, such as the structures and processes that health systems can directly improve, is a key strategy for addressing these gaps. However, most measures evaluate modifiable aspects of care delivery separately, limiting understanding of how improvements in one domain reinforce the other and how their combined effect influences equitable care.

This dissertation addresses this gap by combining patient experience and clinical quality, two modifiable aspects of care that captures how patients interact with the health …

High-Throughput Screens Identify Genotype-Specific Therapeutics For Channelopathies, Christian L. Egly, Alex Shen, Tri Q. Do, Carlos Tellet Cabiya, Paxton A. Ritschel, Suah Woo, Matthew Ku, Brian P. Delisle, Brett M. Kroncke, Björn C. Knollmann

Physiology Faculty Publications

Genetic diseases such as ion channelopathies substantially burden human health. Existing treatments are limited and not genotype specific. Here, we report a 2-step high-throughput approach to rapidly identify drug candidates for repurposing as genotype-specific therapy. We first screened 1,680 medicines using a thallium-flux trafficking assay against Kv11.1 gene variants causing long QT syndrome (LQTS), an ion channelopathy associated with fatal cardiac arrhythmia. We identified evacetrapib as a suitable drug candidate that improves membrane trafficking and activates channels. We then used deep mutational scanning to prospectively identify all Kv11.1 missense variants in an LQTS hotspot region responsive to treatment with evacetrapib. …

Tesla's Forced Middleman: Why Modernization In The Automobile Industry Requires Louisiana To Revise Its Direct Sales Law, John Brainard

Louisiana Law Review

No abstract provided.

Diffog: Differentiable Policy Trajectory Optimization With Generalizability, Zhengtong Xu, Zichen Miao, Qiang Qiu, Zhe Zhang, Yu She

School of Industrial Engineering Faculty Publications

Imitation-learning-based visuomotor policies excel at manipulation tasks but often produce suboptimal action trajectories compared to model-based methods. Directly mapping camera data to actions via neural networks can result in jerky motions and difficulties in meeting critical constraints, compromising safety and robustness in real-world deployment. For tasks that require high robustness or strict adherence to constraints, ensuring trajectory quality is crucial. However, the lack of interpretability in neural networks makes it challenging to generate constraint-compliant actions in a controlled manner. This article introduces differentiable policy trajectory optimization with generalizability (DiffOG), a learning-based trajectory optimization framework designed to enhance visuomotor policies. By …

Node-Attributed Spatial Graph Partitioning: A Kullback-Leibler Divergence Based Approach, Valentin Nechita

Electronic Theses and Dissertations 2020 - Present

This thesis presents a novel approach to node-attributed spatial graph partitioning (NSGP) that addresses limitations in existing homogeneity measures. We introduce a Kullback-Leibler (KL) divergence-based formulation we name KLD that measures attribute similarity by comparing each node’s distribution to its subgraph centroid, providing a computationally efficient method of measuring homogeneity. Integrated within a multilevel graph partitioning framework and Fiduccia-Mattheyses refinement, our approach achieves approximately 90% runtime reduction compared to the baseline Clustering and Local Refinement (CLR) algorithm while maintaining comparable partition quality. Applied to COVID-19 infection data combined with American Community Survey demographics across U.S. FIPS codes, KLD successfully identifies …

Study On The Mechanical Characteristics Of A Natural Fiber-Based Hybrid Polymer Composite, Mohan Kumar Anand Raj, P Manoj Kumar, Praveensabari Palanisamy, Sanjay Dharmaraju, Sureshkumar Periyasamy, Murugesan Palaniappan, Dawit Tafesse Gebreyohannes

Faculty, Staff and Students Publications

In this work, the hybrid fiber-based epoxy composite samples have been prepared with the application of three unlike organic natural fibers viz., Sisal (S), Ramie (R), and Flax (F) and epoxy as the matrix, with a weight ratio of 70:30 for epoxy and fibers. Six different stacking sequences of fibers, pure fibers and pure matrix were used for specimen preparation, namely S/F/F/F/S, F/S/S/S/F, F/R/R/R/F, R/F/F/F/R, R/S/S/S/R, S/R/R/R/S, PS, PR, PF, and Pure matrix. The composite specimen was prepared by manually and uniform thickness was obtained by the compression moulding process. The mechanical trials such as, tensile, impact, hardness, and flexural …

Newsletter 2025.11.24, Fcrh Honors Program

What's Going On, Honors? (2025-26)

No abstract provided.

Modified Artificial Neural Networks In Stochastic Differential Equations To Estimate The Occurrence Rate Of A New Process For Software Reliability Growth Modelling, Adel Sufyan Hussain, Zedan Zubair Mashikhin, Noora Taha Abduirazzaq

Baghdad Science Journal

This paper aims to utilize modified artificial neural networks under stochastic differential equations to improve the estimation of occurrence rates on models towards the growth of software reliability through such models. There has never been a time when reliable assessment methods have been more important as software systems grow ever more sophisticated. This study covers the risks arising from software bugs, security weaknesses, and the need to meet legal requirements. The authors use a new method that combines artificial intelligence techniques with classical reliability models to achieve their goal of a more efficient computational tool for predicting software reliability. It …

Enhancing Brain Mri Classification With Gray Wolf Optimization And Swin Transformers, Lamyaa Fahem Katran, Ebtesam N. Alshemmary, Waleed A. Al-Jawher

Baghdad Science Journal

With the rapid advancement of computational power, deep learning has become integral to medical imaging. Convolutional Neural Networks (CNNs) are widely applied to brain MRI scans for tumor classification due to their strong localization and recognition capabilities. However, their limited ability to capture long-range dependencies often leads to information loss and reduced performance in complex feature extraction. To overcome this, the Swin Transformer introduces a hierarchical attention mechanism with shifted windows that preserves spatial relationships and enhances the modeling of global contexts. This architecture improves the detection of intricate tissue textures and supports high-resolution reconstruction of MRI images. Furthermore, integrating …

Transformer Network On Global Self-Attention Mechanism For Brain Tumor Segmentation, Ammar Awni Abbas Baghdadi, Mohammed Al-Mukhtar, Ammar S Al-Zubaidi

Baghdad Science Journal

Transformers are a specific category of neural network design. Transformers often depend on extensive pre-training on a large scale and exhibit a notable degree of computational complexity. The disadvantage of using this method is a significant increase in computational complexity, which necessitates a significant commitment of time and computing resources in order to successfully work with these models. Transformer networks possess the desirable benefit of extracting distant characteristics effectively via their self-attention mechanism. In this paper, the Global Self-Attention Transformer module is applied to tackle these issues. The model is based on a segmentation problem called Brain-GS that works as …

Forecasting Big Data Daily Silver Price Based On Hybridizing Support Vector Regression And Meta-Heuristic Algorithms, Ibtihal Muneeb Yahya, Zakariya Yahya Algamal

Baghdad Science Journal

Because commodities are prone to large price swings, forecasting their prices can be extremely difficult. Similar to other commodities, the price of silver is determined by a complicated interplay between a number of factors, including time-lag. Precise forecasting of the silver price is essential for the stable and effective functioning of silver markets. The time series that metal prices follow is non-stationary, nonlinear, and contains periods that fluctuate due to possible growth. Accurate forecasting of silver prices is difficult since they are consistently highly nonlinear and non-stationary. Forecasting metal prices, in general, have been predicted by support vector regression (SVR). …

Energy Management Of Battery Supercapacitor Hybrid Storage In Electric Vehicles With Solar Integration: Review, Islam Sayed, Yousef Mahmoud

Faculty Articles

Hybrid energy storage systems (HESS) integrating batteries and supercapacitors offer a promising solution to overcome the limitations of battery-only architectures in electric vehicles (EVs). By leveraging the high energy density of batteries and the high power density of supercapacitors, HESS can enhance power delivery, improve energy efficiency, and extend battery lifespan. The effectiveness of HESS, however, is largely determined by the energy management system (EMS) that coordinates power flow under dynamic driving conditions. Unlike existing reviews, this work addresses common gaps in the literature, including the lack of industrial energy storage component examples, limited coverage of recently developed EMS strategies, …

Assessment Of Traffic Related Air Pollution Effects On Indoor Air Quality In Educational Buildings, Ahmed Gouda Mohamed, Mohamed Sherif Dr., Fahad Alqahtani Dr., Yousif Deeb Eng.

Civil Engineering

This study assesses the impact of traffic-related air pollution (TRAP) on indoor air quality (IAQ) within a Riyadh school. The main objectives are to pinpoint factors influencing IAQ and to evaluate the effectiveness of existing ventilation and filtration systems. Air quality Egg sensors monitored nitrogen dioxide (NO2), carbon monoxide (CO), and particulate matter (PM1.0, PM2.5, PM10) levels both indoors and outdoors over 30 days. Findings revealed average indoor PM2.5 and PM10 concentrations of 14.09 µg/m3 and 18.15 µg/m3, respectively, while outdoor concentrations averaged 20.63 µg/m3 and 27.88 µg/m3. A strong positive correlation was observed between indoor and outdoor PM levels, …

A Geological Carbon Cycle Sink Hosted By Ocean Crust Talus Breccias, Rosalind M. Coggon, Elliot J. Carter, Lewis Grant, Aled D. Evans, Christopher Lowery, Damon A.H. Teagle, Pamela Kempton, Matthew J. Cooper, Claire Routledge, Elmar Albers, Justin Estep, Gail Christeson, Michelle Harris, Thomas Belgrano, Jason Sylvan, Julia Reece, Emily Estes, Trevor Williams

School of Geography, Earth and Environmental Sciences

Calcium carbonate precipitation in ageing ocean crust sequesters carbon dioxide dissolved in seawater through seafloor weathering reactions, influencing atmospheric CO2 concentrations on million-year timescales. However, this crustal carbon sink, and the extent it balances CO2 degassing during crustal formation at mid-ocean ridges, remain poorly quantified due to limited sampling of the vast ridge flanks where CO2 uptake continues for millions of years. Here we quantify the carbon sink hosted within talus breccias that accumulated through mass wasting 61 million years ago during rift faulting at the slow spreading Mid-Atlantic Ridge, cored during International Ocean Discovery Program South Atlantic Transect Expedition …

Low-Energy Multiphoton Scattering At Tree-Level And One-Loop Order In A Homogeneous Electromagnetic Field, James Edwards, Ivan Ahumada Hernandez, Patrick Copinger

School of Engineering, Computing and Mathematics

We study low energy photons coupled to scalar and spinor matter in the presence of an arbitrary homogeneous electromagnetic field in a first-quantized (worldline) approach. Utilizing a Fock-Schwinger gauge for both the scattering photons and homogeneous background, simple compact expressions are found for both the photon- and background-dressed effective action and propagator in scalar and spinor quantum electrodynamics. The low-energy limit allows identification of the coupling of the scattering photons as one of an effective homogeneous superposition of their field strengths, with amplitudes following from application of a suitable linearization operator. To treat the linearization, several techniques are employed, including …

Mycobacterium Chelonae Outbreak Investigation At A Quaternary Pediatric Hospital Following The Opening Of A Leed-Certified Critical Care Tower: Where Does Water Sustainability Intersect With Infection Control?, Andrea L Ankrum, Silvia M Caceres, Michael Torsell, Elaine Epperson, Vinicius Calado Nogueira De Moura, Jennifer J Gilick, Michael Strong, Qingyun Liu, Matthew J Strand, Rachel N Wilsey, Jennifer R Honda, Jane E Gross, Felicia A Scaggs-Huang

Faculty, Staff and Student Publications

Objective: Investigate the increased incidence of Mycobacterium chelonae positive respiratory cultures in hospitalized patients.

Design: Apply the Healthcare-Associated Links in Transmission of Nontuberculous Mycobacteria (HALT NTM) toolkit to an outbreak investigation of M. chelonae.

Setting: Quaternary-care pediatric hospital and medical center in the United States with a recently opened LEED-certified critical care tower.

Patients: Adult and pediatric patients with M. chelonae positive respiratory cultures between June 2022 and January 2024.

Methods: An epidemiological investigation involving clinical and laboratory practices, water management, building construction and renovation projects. Environmental sampling of air vents, water sources and endoscope reprocessing equipment was performed. M. …

Naphthalimide-Based Type-I Nano-Photosensitizers For Enhanced Antitumor Photodynamic Therapy: H2s Synergistically Regulates Pet And Self-Assembly, Huiyu Niu, Songnan Wang, Yang Liu, Nana Ma, Shuaiwei Cheng, Beidou Feng, Hyunsun Jeong, Yonggang Yang, Ge Wang, Tony D James, Juyoung Yoon, Jonathan L Sessler, Hua Zhang

Faculty, Staff and Student Publications

Photodynamic therapy (PDT) relies on a combination of light and photosensitizers (PSs) to achieve local control over cancerous lesions. However, it is subject to limitations, including tumor hypoxia, low tumor targeting, off‐target phototoxicity, and always‐on fluorescence. Here, we propose a design strategy for activated nano‐PSs (N‐PSs) to simultaneously overcome the limitations of PDT, wherein photoinduced electron transfer (PeT) is coupled with an endogenous H2S‐regulated self‐association process to promote Type‐I photochemical reactions. Using theoretical calculations, spectral analysis, and microscopic imaging, we verified the generation of self‐assembly and occurrence of PeT. And it was also shown that H2S could synergistically inhibit the …

Stiefel Md Anderson Oropharynx Cancer (Mda-Opc) Cohort: A Single-Institution, Prospective Longitudinal Outcomes Study, Amy Moreno, Ariana J Sahli, Faye Johnson, Xiaowen Sun, Carly Barbon, Waree Rinsurongkawong, Wenye Song, Flavie M Luciani, Han Liang, Jun Li, Wei Liu, J Jack Lee, S J Frank, Stephen Lai, Clifton Fuller, Katherine Hutcheson

Faculty, Staff and Student Publications

Purpose: The MD Anderson Oropharynx Cancer (MDA-OPC) cohort is a unique single-institution, prospective longitudinal cancer cohort. The cohort aims to enhance the therapeutic index of OPC management by supporting data needs for independent investigators to conduct rigorous observational studies examining exposures and factors associated with acute and late toxicities, cancer progression, recurrence, new malignancies and quality of life in OPC survivors.

Participants: A total of 1811 patients with OPC with a minimum follow-up of 6 months have been consented to our prospective registry between 18 March 2015 and 29 December 2023. Clinical and treatment (Tx) data are available on all …

On Iterative Method For The Solution Of Non-Linear Equations Using Anti-Lobatto Four Point Quadrature Rule, Tusar Singh, Dwiti Krushna Behera

Baghdad Science Journal

By harnessing the classic anti-Lobatto four-point quadrature rule of degree of precision three, the order of convergence of the Newton-Raphson method has been profoundly enhanced. This newly developed iterative scheme reveals a remarkable order of convergence, reaching three and far surpassing the original Newton-Raphson method. It operates as a two-step iterative method that elevates Newton’s approach by integrating the quadrature rule. A theorem related to this innovative iterative method has been formulated, confirming that its order of convergence is indeed three. In the numerical computation section, insightful scenarios demonstrate the remarkable numerical efficiency of the new method. Through the power …

Efficient Face Mask Recognition Model Based On Deep Learning And Multi-Machine Learning Classifiers, Hassenien Ali Hussein, Firas Muneam Bachay, Saffa Jasim Mosa, Mohammed Hasan Abdulameer

Baghdad Science Journal

Safety in chemical and biological laboratories requires face masks. Nevertheless, the masked face images present obstacles to accommodate the wide pose variations, low resolution, changes in size and incomplete cropping, and varying emotive expressions, making feature extraction and recognition robust difficult. To decern between faces with proper, improper, and no facemask, Deep Learning (the use of Convolutional Neural Networks (CNNs)) and classifiers such as SoftMax, Support Vector Machines (SVM) and K-Nearest Neighbors (KNN) were used. The methodology utilized the 2075 AR face images that contain various resolutions, orientations, and occlusions. The paper develops a Deep Learning-based model utilizing CNNs and …

Next Word Prediction In Social Media Texts For Punjabi-English Bilingual Users With Sequential Cnn-Bilstm, Gurpreet Singh, C P Kamboj

Baghdad Science Journal

Preparing a collection of Punjabi-English social media text and creating a next word prediction system for Punjabi users are the main goals of this study. As the Gurmukhi script has a large character set, typing in Punjabi takes a lot of time. That is the reason behind using the Roman script for communication on social media platforms like WhatsApp, Facebook, and Twitter by many Punjabi users. For such users, we have proposed a sequential CNN-BiLSTM architecture to provide suggestions to improve typing speed and make communication convenient. In our proposed model, we used 128 filters and a kernel size of …

Enhancing Secrecy Rate For Cognitive Radio Based On 5g Communication Systems, Mohammed Kadim Shaybeth Al-Jorani, Hakem Beitollahi

Baghdad Science Journal

The non-orthogonal multiple accesses (NOMA) together with Cognitive radio network (CRN) are critical frameworks in the 5G remote transmission framework. Nonetheless, the framework is an outstanding method for the cognitive clients to get a telecommunication from the interference signals in different info numerous yield (MIMO)- NOMA-relied cognitive radio network. For here project, a modern beamforming strategy is introduced for getting a data trade inside similar units as well as adjoining units about every tempering client. The intervention is brought about through a blemished range detecting of the optional clients (SUs). The SUs is expected to get to the essential communication …

Thinning Antarctic Glaciers Expose High-Altitude Nunataks Delivering More Bioavailable Iron To The Southern Ocean, Kate Winter, John Woodward, Stuart A. Dunning, James R. Jordan, Joseph A. Graly, Matthew J. Westoby, Sian F. Henley, Robert Raiswell

School of Geography, Earth and Environmental Sciences

Glacial systems entrain and transfer sediment, rich in essential nutrients, from continental sources to the ocean, where they are released by meltwater. In the Southern Ocean, primary producers are limited by the availability of micronutrients, like iron (Fe), so any increase in continental sediment supply could enhance primary productivity and subsequent drawdown of atmospheric CO₂. Here we provide a systematic account of labile Fe concentrations in Antarctic continental sediments. Ferrihydrite and crystalline Fe (oxyhydr)oxides were extracted from 27 Antarctic samples collected from nunataks, lateral moraines and blue ice areas in the Sør Rondane Mountains, East Antarctica. We report …

Regulating Privacy Policies On Digital Platforms, Michele Bisceglia, Alessandro Bonatti, Fiona Scott Morton

Cowles Foundation Discussion Papers

We study how privacy regulation affects menu pricing by a monopolist platform that collects and monetizes personal data. Consumers differ in privacy valuation and sophistication: naive users ignore privacy losses, while sophisticated users internalize them. The platform designs prices and data collection options to screen users. Without regulation, privacy allocations are distorted and naive users are exploited. Regulation through privacy-protecting defaults can create a market for information by inducing payments for data; hard caps on data collection protect naive users but may restrict efficient data trade.

Innovation Curse: The Wastefulness Of Technologies Believed To Mitigate Climate Change, Minh Hoang Nguyen, Valoree Gagnon, Thanh Tu Tran, Thi Mai Anh Tran

Michigan Tech Publications

Technological innovations are increasingly promoted as solutions to climate change. However, many innovations, including Carbon Capture and Storage, bioplastics, and glacier geo-engineering, suffer significant limitations from high costs, speculative efficacy, and adverse ecological consequences. Using Granular Interaction Thinking Theory (GITT), a transdisciplinary framework grounded in information theory, quantum mechanics, and mindsponge theory, in this study, we explain how such technological innovations become systemically favored despite their flaws. We introduce the concept of the “innovation curse,” which arises when institutional and cognitive filtering systems, operating under high informational entropy, default to familiar but ineffective techno-solutions while marginalizing Indigenous and Local Knowledges …

South Carolina Reemployment Services And Eligibility Assessments (Resea) Randomized Controlled Trial Design Report, Gabrielle Pepin, Ethan Jenkins, Christopher J. O'Leary, Aaron Sojourner

Upjohn Institute Technical Reports

No abstract provided.

Spatial–Temporal Deep Learning For Electric-Vehicle Charging Demand: An Exploratory Study Of Graph Convolutional And Lstm Networks Performance, Maher Alaraj, Carla Martins, Mohammed Radi, Mohamed Darwish, Munir Majdalawieh

All Works

Electric-vehicle (EV) charging is a localized, time-varying load that challenges distribution networks. This study offers practical insights into when spatial graph structure adds value beyond temporal context, utilizing real-world data and a transparent evaluation. We compare Long Short-Term Memory (LSTM) and Graph Convolutional Network (GCN) models for hourly EV-charging energy forecasting, based on 145,778 sessions recorded in Boulder, Colorado (2018–2023). After preprocessing and temporal alignment, temporal covariates (hour, day, month, year) and, when applicable, ZIP-code indicators were engineered. LSTMs were trained with 1 h and 24 h input windows, with or without ZIP features, and evaluated through 5-fold cross-validation. GCNs …

Career Interest And Work Values Of Online Filipino Psychology Graduates: Basis For Retention Program, Henmar C. Cardiño, Erwin B. Sario, Rommel P. Sergio

Social Sciences and Development Review

The main objective of the study is to evaluate the significant association between career interests and workplace values among Filipino online psychology graduates in 2022 and to provide retention strategies for diverse organizations. The study’s goal was to identify the gap between the participants’ career interests and their work values and offer possible retention programs to bridge the gap. The researcher employed a quantitative correlational research design and utilized two research instruments, the RIASEC Test by John L. Holland and the Work Values Inventory by Ronald E. Super, to measure career interest and work values, respectively. In August 2022, a …