Digital Commons Network^™

Artificial Intelligence (Ai) For Social Innovation In Health Education: Promoting Health Literacy Through Personalized Ai-Driven Learning Tools – A Systematic Review, Dina Mansour Tbaishat, Maha Waleed Elfadel

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Background: Artificial Intelligence (AI) is transforming health education by enabling personalized, adaptive, and scalable approaches that may enhance aspects of health literacy. Despite rapid adoption, comprehensive synthesis of AI tools’ impact on health literacy as social innovation is limited. Understanding these effects guides educators, developers, and policymakers in designing potentially effective, inclusive, and ethical AI interventions. This review examines generative AI models, chatbots, and adaptive learning systems in supporting health literacy globally. Methods: A systematic review was conducted following PRISMA guidelines. Literature was identified primarily through PubMed/Medline, Scopus, and ScienceDirect. Connectedpapers.com was used exclusively as a citation chasing tool, performing …

Radio Frequency Tagging–Enabled Patient Monitoring: Integrating Mobility Tracking With Early Warning Systems For Enhanced Safety, Ahed Abugabah, Prashant Kumar Shukla, Piyush Kumar Shukla, Abhishek Dwivedi

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Ensuring patient safety in healthcare environments requires continuous monitoring systems capable of identifying early warning signs of clinical risk. Traditional surveillance methods often fail to capture meaningful patterns in patient movement, limiting their ability to prevent incidents such as falls, prolonged immobility, or unnoticed health deterioration. Radio Frequency Tagging technology has been increasingly adopted for real-time patient tracking; however, existing systems are generally limited to location detection and lack predictive insights into patient behaviour. To overcome these limitations, this study presents a Radio Frequency Tagging-based patient monitoring framework that integrates mobility tracking with an early warning mechanism to enable proactive …

A Robust Approach For Olive Leaf Disease Detection In Uncontrolled Environments, Rima Grati, Khouloud Boukadi, Emna Ben Abdallah, Ahmed Seffah

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Detecting diseases in olive leaves is crucial for maintaining tree health and ensuring stable olive production. Early signs of infection often appear on the leaves, making them a key indicator for timely disease detection and intervention. Traditionally, farmers rely on visual inspection or laboratory tests to diagnose plant diseases. However, recent advancements in deep learning (DL) have significantly improved the accuracy and efficiency of olive leaf disease diagnosis. Numerous studies in the literature have explored this task using CNN-based architectures and, more recently, Vision Transformers. While these models have shown promising performance on benchmark datasets, they are often trained and …

An Advanced Healthcare System With An Automated Vit Model For Dermoscopic Skin Cancer Identification, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi

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Early and reliable diagnosis of skin cancer from dermoscopic images remains challenging due to class imbalance, subtle inter-class variations, lesion boundary ambiguity, and illumination inconsistency, which can degrade the robustness of conventional convolutional neural networks (CNNs). To address these limitations, this study proposes an automated smart healthcare framework for dermoscopic skin cancer diagnosis using an Enhanced Vision Transformer (E-ViT) that improves global-context modeling through self-attention while strengthening fine-grained lesion representation learning. Unlike standard ViT configurations, the proposed architecture integrates multi-scale patch embedding and attention refinement to better capture border irregularities and color–texture heterogeneity that are critical for melanoma discrimination. Furthermore, …

The Role Of Corporate Sustainability Goals In Shaping Organizational Intentions And Adoption Of Green Technologies In Small- And Medium-Sized Enterprises, Syed Zamberi Ahmad, Abdul Rahim Abu Bakar, Imane Belyamani, Manar Fawzi Bani Mfarrej

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This study investigates green technology adoption (GTA) among small and medium-sized enterprises (SMEs) in the United Arab Emirates (UAE), focusing on the influence of corporate sustainability goals (CSG) and sustainability motivation (SM). Utilizing institutional theory, the theory of planned behavior (TPB), and resource-based view (RBV), the research highlights how SMEs integrate environmental, social, governance (ESG) and economic considerations into their CSG to enhance GTA. Addressing a gap in prior research that has largely emphasized external drivers of adoption while underexploring internal organizational mechanisms, the study conceptualizes CSG as strategic intent and models SM as a second-order construct . Based on …

Sensors And Smart Food Packaging For Supply Chains: Bridging Expiration Dates And Actual Perishability, Muhammad Umar Azam, Jolina Rodrigues, Mohamed Hamid Salim, Sarath Haridas Kaniyamparambil, Khalid Askar, Imane Belyamani, Blaise L. Tardy, Nouha Alcheikh

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The food supply chain is undergoing critical changes to minimize environmental hazards, such as those associated with packaging, and reduce food waste and loss. One of the critical components of the latter is associated with the high variance in the perishability of individual foodstuffs. Herein, we review the state of the art in smart sensor systems and emphasize the critical role they could play in addressing the mismatch between “batch” based expiry dates and individual food products’ time-dependent responses to spoilage. Following a brief overview of food shelf life and associated legislation, a subsequent section summarizes the development of sensors …

Nepal Brick Dust And Silica Exposure 2023-2025 Combined Data, Brinly Openshaw, Willow A. Call, Parker D. Willis, Claire Owens, Gregory L. Snow, Seshananda Sanjel, James D. Lecheminant, Neil E. Peterson, Andrew J. South, Clifton B. Farnsworth, Jayson Gifford, Scott C. Collingwood, James D. Johnston

ScholarsArchive Data

A quantitative, cross-sectional study was conducted over an approximately three-year period with sample collection events occurring March 13-21, 2023, March 17 – 23, 2024, and February 18 – 26, 2025. Samples were taken across 4 brick kilns in Bhaktapur, Nepal, including Kiln 1 in 2023, Kiln 2 in 2024, and Kilns 3 and 4 in 2025. Participants (N = 248) were recruited by convenience sampling from kiln 1 (n = 49), kiln 2 (n = 70), kiln 3 (n = 69), and kiln 4 (n = 60).

Toward Equitable Energy Futures: The Influence Of Digital Government And Financial Development On Clean Energy Justice, Martin Spraggon, Muhammad Hafeez, Sana Ullah, Chanyanan Somthawinpongsai, Zurul Aisya Osman, Sidra Sohail

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Fossil fuel energy is the largest source of carbon emissions and the main driver of climate change and global warming. Therefore, the world is switching towards clean and green energy sources as an alternative to fossil fuel-based energy sources. Nevertheless, the equitable distribution of clean energy resources in urban and rural areas among every segment of society has become a concern for policymakers. Thus, urban-rural clean energy justice is an investigation topic that needs our attention. In this analysis, our main focus is on investigating the influence of financial development and digital government on clean energy justice using an advanced …

The Impact Of Partner Support On Vaginismus Treatment Outcomes: A Mixed Methods Study, Anna R. Ames, Alisha H. Redelfs, Nana Mensah

ScholarsArchive Data

A mixed-methods design was used to gain a nuanced understanding of how partner support affects the experiences of people with vaginismus.

Study aim: To guide partners of people with vaginismus in understanding how they can best help their partners with their vaginismus experience. 

• Quantitative Data: cross-sectional survey to reveal correlations in the relationship between vaginismus treatment outcomes and partner support [Available]
• Qualitative Data: Individual interviews to explore specific ways that people with vaginismus receive, or want to receive, support from their partners and the significance that they place on partner support  [Not Available]

Survey Data
Survey participants were recruited in …

Melatonin-Functionalized Silver Nanoparticles Enhance Salinity Tolerance In Brassica Juncea By Modulating Antioxidant Defence And Growth Physiology, Mohini Yadav, Manar Fawzi Bani Mfarrej, Vikash Kumar, Ankita Singh, Faheem Ahmad, Saurabh C. Saxena

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Soil salinity is a major abiotic stress that severely limits plant growth and productivity by inducing osmotic stress, oxidative damage, and ionic imbalances. The present study evaluated the potential of melatonin-mediated silver nanoparticles (Mel AgNPs) to enhance salinity stress tolerance in Brassica juncea. Pot experiments were conducted using 21-day-old plants exposed to salinity stress and treated with Mel AgNPs at different concentrations (50 and 100 mg L⁻¹) through both root application and foliar spray. Morphological, physiological, and biochemical responses were assessed 48 h after nanoparticle exposure. Salinity stress markedly increased lipid peroxidation and hydrogen peroxide accumulation while suppressing antioxidant defence. …

Infant Hippocampal And Amygdala Volume In An Observational Follow-Up From A Randomized Clinical Trial For Maternal Prenatal Depression, Catherine H. Demers, Benjamin L. Hankin, Lillybelle K. Deer, Robert J. Gallop, Mercedes Hoeflich Haase, M. Camille Hoffman, Martin A. Styner, Nancy K. Grote, Elysia Poggi Davis

Psychology: Data Sets

Prenatal maternal depression may have intergenerational effects on offspring brain development, with potential socioemotional consequences. In an observational follow-up of a randomized clinical trial of a prenatal depression intervention (the CARE Project; ClinicalTrials.gov NCT03011801), brain development and subsequent negative emotionality were examined among 109 infants born to mothers randomized during pregnancy to brief interpersonal psychotherapy or enhanced usual care. These data include MRI-derived hippocampal and amygdala volumes at approximately 6 weeks of age and a laboratory-based assessment of infant negative emotionality at 6 months.

Resulting Publication: Infant hippocampal and amygdala volume in an observational follow-up from a randomized clinical trial …

Dollar$ And $Ense Newsletter Summer 2026, Nova Southeastern University

Dollars & Sense Newsletter

No abstract provided.

Plant-Dominant Low-Protein Diet Versus Standard Care In Adults With Chronic Kidney Disease Stages 3–5: A Randomized Controlled Trial Protocol, Joelle Abi Kharma, Rana Sultan, Rana Rizk, Dalya Haroun, Hala Kilani, Kamyar Kalantar-Zadeh, Jessica Gubbels, Kathelijne Bessems

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Background The plant-dominant low-protein diet (PLADO), providing 0.6-0.8 g/kg/d of protein with ≥50% derived from plant sources, may improve acid–base balance and metabolic outcomes in chronic kidney disease (CKD). However, concerns remain regarding safety and feasibility, and experimental evidence is limited. Objective This protocol describes a randomized controlled trial (RCT), designed to evaluate the efficacy, nutritional and biochemical safety, implementation feasibility, and cost-effectiveness of PLADO compared with the standard renal diet in adults with CKD stages 3-5. Methods This unblinded, parallel-group RCT will enroll 48 adults with CKD stages 3-5 in a medical center in Lebanon and randomize participants 1:1 …

Social Network Assessment For Adult Protective Services (Snaaps), Version 1.0: A Network Canvas Data Collection Instrument, Rebecca L. Mauldin, Laura E. Carter

Social Networks for Social Good Collection-Archive

The Social Network Assessment Protocol for Adult Protective Services (SNAAPS) is a Network Canvas interview protocol designed to support the collection, organization, visualization, and interpretation of social network data from older adults. The protocol was developed for use by Adult Protective Services practitioners, social workers, first responders, and other service providers who assess, refer, and intervene on behalf of older adults' well-being. The protocol facilitates the identification of social network characteristics associated with risk and protection related to elder mistreatment, including support relationships, financial involvement, conflict within the network, frequency of contact, connections to formal services, and patterns of network …

Best Strategies To Teach Nutrition Courses In Graduate Programs: A Systematic Review, Zeina Hojeij, Suzan Haidar, Rana Rizk, Nadine Mahboub

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Introduction – Graduate-level nutrition education requires innovative teaching strategies that foster advanced clinical competence, professional communication, cultural responsiveness, and self-directed learning. Methods – This systematic review synthesized evidence from fifteen peer-reviewed studies examining diverse teaching strategies in graduate nutrition programs. Results – Most interventions employed simulation-based learning, experiential placements, or flipped classrooms, often incorporating technology such as virtual simulations and online collaborative platforms. Simulation and experiential approaches improved clinical competence, communication skills, empathy, and self-efficacy by providing realistic, hands-on experiences that bridged theoretical knowledge with professional practice. Flipped classrooms, though less frequently implemented, promoted teamwork, problem-solving, and reflective learning, while …

The Association Between Ethical Ai Use And Well-Being Among Young Adults In The Uae: A Structural Equation Modeling Approach, Areej Elsayary, Zeina Hojeij, Lames Abdul Hadi

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This study examines the association between ethical AI use and young people’s emotional, social, and psychological well-being in the United Arab Emirates (UAE), where the number of hours spent on GenAI serves as a moderator. Framed within the Theory of Planned Behavior and aligned with the Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being) and SDG 13 (Climate Action), this research examines how responsible digital engagement is associated with both individual mental health and broader digital sustainability. A Structural Equation Modeling approach assessed how ethical AI behaviors are associated with well-being. A total of 204 participants, predominantly …

Beyond Religious Narcissistic Identification: Agnostic And Atheistic Narcissism, Magdalena Żemojtel-Piotrowska, Jarosław Piotrowski, Bartłomiej Nowak, Vassilis Saroglou, John Maltby, Constantine Sedikides, Mladen Adamovic, Nur Amali Aminnuddin, Seth Christopher Yaw Appiah, Rahkman Ardi, Zana Hasan Babakr, Einar Baldvin Baldursson, Sergiu Bălțătescu, Muhammed Bilgehan Aytaç, Aidos Bolatov, Bruno Bonfá-Araujo, Matthias Burghart, Phatthanakit Chobthamkit, Marilyn Clark, Magali Clobert, Richard G. Cowden, Jesus Alonso Datu, Sandesh Dhakal, Sonya Dragova-Koleva, Begoña Espejo, Dmitry Grigoryev, Emanuela Gritti, Katherine Gundolf

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Agnosticism and atheism are often grouped simply as nonreligious identities, yet emerging research highlights their distinct psychological profiles and social implications. Among these distinctions, collective narcissism–characterized by strong attachment to one’s group, exceptionalism, and grievance for recognition–offers a framework for understanding identity processes in both nonreligious groups. We examined whether agnostics and atheists exhibit collective narcissism and its forms (agentic–focused on exceptional effectiveness; communal–focused on exceptional morality) similarly to believers. We explored cross-denominational variance in agentic and communal collective narcissism levels relying on data from 77 countries (N = 3,570; 1227 agnostics, 2343 atheists). Agnostics and atheists from secular countries …

Companionships, Transportation, And Health Among Members Of A Hispanic Senior Center: A Sociometric Social Network Dataset, Rebecca Mauldin Phd, Msw, Vismaya Prakasan Msis, Akshay Thakare Msis, Rupal Parekh Phd

Social Networks for Social Good Collection-Archive

This dataset contains survey and social network data from 42 members of a predominantly Puerto Rican senior center in Hartford, Connecticut. It includes two linked components (1) participant-level information on demographics, health, mobility, and transportation, and (2) a sociometric network of companionship ties among members. The data are designed for use in social network analysis and research on aging, mobility, and social relationships. These data can be used to explore questions such as how companionship ties are structured among older adults in a community setting; whether individuals with similar characteristics (e.g., age, gender, health status) are more likely to form …

Graduates List - May 2026, University Of Nebraska At Omaha

Commencement Lists

No abstract provided.

Csbsju Ash Tree Maps, Trevor Barton

Celebrating Scholarship and Creativity Day (2018-)

Ash trees in MN are recently susceptible to the invasive species of Emerald Ash Borer. These insects burrow into native MN ash trees, lay their larvae, and significantly harm or kill the trees. MN native ash trees are not equipped to deal with this invasive species and rather need to be chemically treated to save the trees. These maps depict the GPS locations of the ash trees on CSBSJU campus proper. Trees were mapped by hand with a Garmin GPS device while size, health, and value to campus assessments were recorded to pair along with the maps in a separate …

Smart Medical Support System And Swin Transformer Framework For Breast Cancer Detection And Segmentation In Mammograms, Ahed Abugabah, Prashant Kumar Shukla, Piyush Kumar Shukla, Abhishek Dwivedi

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Accurate and reliable breast cancer detection from mammographic images remains a critical challenge due to subtle lesion appearance, high intra-class variability, and class imbalance inherent in clinical datasets. To address these issues, this study proposes Swin-BreastNet, an explainable and optimization-driven deep learning framework for binary classification of benign and malignant breast lesions from full-field digital mammograms. The proposed approach leverages the hierarchical Swin Transformer model to effectively capture fine-grained local texture patterns and long-range contextual dependencies through Shifted Window Multi-head Self-Attention (SW-MSA). A key novelty of this work lies in the integration of Harris Hawks Optimization (HHO) for automated hyperparameter …

The 12-Week Silence: A Scrollytelling Investigation Into Early Pregnancy Loss And The Case For Continuous Progesterone Monitoring, Audrey Gold

FHSS Mentored Research Conference

Opens with the scale of the problem (up to 1M miscarriages annually, all in the most data-poor window of pregnancy), describes the methodology (2 original surveys, 4 clinical interviews, peer-reviewed literature), walks through what the piece does visually (the distribution curve, the blind-spot timeline, the 5-phase progesterone chart, the intervention pathway), and closes with the central argument — that the silence is a gap in technology, not an inevitability.

Quality Improvement Project: The Critical Role Of Provider Knowledge In The Golden Hour, Kimberly Mcglothan

Doctor of Nursing Practice Projects

Maternal and infant mortality rates in the Southern United States remain disproportionately high, and inconsistent implementation of the Golden Hour, defined as uninterrupted skin to skin contact for at least the first hour after birth, continues to limit its evidence based maternal and neonatal benefits. The aim of this Doctor of Nursing Practice (DNP) quality improvement project was to evaluate the impact of a structured provider education intervention on Golden Hour compliance and provider confidence. Guided by Benner’s Novice to Expert Theory and implemented using Kotter’s 8-Step Change Model, a quantitative, quasi experimental pre-post design was used. The project was …

The Intricate Dance Of Emotions And Psychophysiology: Unveiling The Secrets Of Microexpressions, Jaiteg Singh, Deepika Sharma, Babar Shah, Sukhjit Singh Sehra, Farman Ali, Irfan Hussain

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Background: Emotion recognition plays a pivotal role in behavioral analysis, mental health assessment, and human-computer interaction. Micro-expressions, which are brief and involuntary facial movements, offer valuable insights into concealed emotions. However, validating micro-expressions remains a challenge due to their subtlety and short duration. This study aims to enhance the validation and classification of micro-expressions by integrating electromyogram (EMG) signals with facial action units (AUs). Methods: EMG data was collected using the EMG Muscle Sensor Module V3.0, interfaced with an Arduino Mega 2560 microcontroller. To ensure signal clarity, various data filtration techniques were applied to eliminate noise, motion artifacts, and baseline …

Polypeptide Sequence Effects On Virus Thermostability In Complex Coacervate Formulations, Pratik U. Joshi, Claire Decker, Arvind Sathyavageeswaran, Xianci Zeng, Hong Liu, Milad Kheirvari, Ebenezer Tumban, Lynn M. Manchester, Idris Tohidian, Eduardo Barbieri, Sarah L. Perry, Caryn Heldt

Michigan Tech Research Data

Current vaccine formulations heavily rely on cold chains to avoid
degradation during transportation and storage. Vaccines typically degrade
when exposure to temperature outside of 2 – 8°C range, leading to waste and
logistical challenges, particularly in rural areas. This study investigates
the ability of poly(lysine)- and poly(glutamate)-based peptide coacervates
to improve the thermal stability of porcine parvovirus (PPV), a model
non-enveloped viral vaccine. We hypothesized that both the length and
specific amino acid sequence of the peptides forming the coacervates would
influence the stability of PPV. Long polypeptides (400–800 mers) provided
significant protection, slowing PPV inactivation at 60°C for up …

Dataset For Geospatial Interpolation Of Soil Profile Depth In The Magic Valley, Idaho, Usa: Use Of Publicly Available Well Report Data, Akira Byrne, David P. Huber, Dylan Thompson, Josh Enterkine, Jennifer Pierce

Geosciences Research Data

Soil depth is critical to ecosystem productivity, acting as a reservoir for water, nutrients, and carbon. Deeper soils enhance water holding capacity to withstand droughts in native and agricultural systems, and provide more volume for long-term carbon sequestration, directly influencing soil health and climate regulation. This dataset scraped public well log (AKA well driller’s report) data from the Idaho Department of Water Resources (IDWR) to create a soil depth map across the Magic Valley in south-central Idaho, USA. Soils in this region are predominantly loess-derived silt-loams, underlain by undulating beds of basalt on top of deep rhyolite. Starting in the …

Evolving Landscape Of Respiratory Infections And Amr In The Uae: A 12-Year Nationwide Study Of Regional Burden, Epidemiologic Trends And Policy Implications, Madikay Senghore, Jens Thomsen, Najiba M. Abdulrazzaq, Wei Chen, Eveline Kaambo, Stefan Weber, Fouzia Jabeen, Godfred Antony Menezes, Carole Ayoub Moubareck, Dean B. Everett, Abiola Senok

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Objectives This study characterizes the epidemiological trends and resistance profiles of respiratory tract infections (RTIs) in the United Arab Emirates (UAE) from 2010 to 2022, aiming to inform national control strategies. Method We conducted a retrospective observational study of RTI cases across 345 UAE healthcare settings using data from the national surveillance network. Pathogen identification and resistance profiling were performed using advanced diagnostics and standardized antimicrobial susceptibility testing, in accordance with Clinical and Laboratory Standards Institute (CLSI) guidelines. Results Lower respiratory tract infections (LRI) comprised most cases (73.1%; n = 100,856), including 6416 due to Mycobacterium tuberculosis , while upper …

Obesity And The Gut Microbiota In The Middle East: A Cross-Cultural Study Of Lebanese And Emirati Adults, M. Ali Ahmad, M. Abou-Samra, E. Blaak, M. Karavetian, C. Ayoub Moubareck, K. Venema

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Obesity is a growing public health concern in the Middle East and North Africa (MENA) region, yet limited research has explored how gut microbiota varies between Arab populations. This study compared the gut microbiota composition and diversity of Emirati and Lebanese adults with obesity and assessed the role of age and nationality in shaping microbial variation. A total of 43 Emirati and 30 Lebanese individuals with obesity (body mass index (BMI) ≥35 kg/m2) were recruited. Participants provided anthropometric and biochemical data, dietary records, and stool samples for 16S rRNA sequencing. The analysis revealed significantly higher BMI, weight, and fat mass …

Supporting Data – Urban Stream, Cardinal Court, Isu, Normal, November 9, 2023 To May 1, 2025, Eric Wade Peterson, Ava Miller

Faculty Publications - Geography, Geology, and the Environment

Between November 9, 2023 to May 1, 2025, water samples were collected upstream and downstream along a segment of a stream adjacent to Cardinal Court on the Illinois State University campus. At each location, samples were collected at the surface. In-situ measurements of Dissolved Oxygen, Specific Conductance, and Temperature were recorded with a YSI 85. Anion samples were analyzed using a Ion Chromatograph for fluoride (F^-), chloride (Cl^-), nitrate as nitrogen (NO3-N), phosphate (PO₄^3-), and sulfate (SO₄^2-). The available dataset provides the recorded field parameters and the analyzed ion concentrations.

Terrence Dean, Mark Naison, Steven Payne, Pastor Crespo Jr., Akilah Shedrick

Oral Histories

No abstract provided.