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 …

The Association Between Cyber Behaviors And Hedonic And Eudaimonic Well-Being: The Moderating Role Of Personality Traits, Areej Elsayary, Juan Calmaestra, Mercedes Gómez-López

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The increasing integration of digital technologies into everyday life has intensified engagement in various cyber behaviors, raising important questions about their relationship with individuals' well-being. This study examined the associations between online moral disengagement, problematic internet use (compulsive internet use), benign and toxic disinhibition, cyberaggression, and cybervictimization with both hedonic and eudaimonic well-being among emerging adults in the United Arab Emirates. Furthermore, it explores the moderating role of personality traits in these associations. Data were collected from 671 emerging adults (46.8% women) aged 18–29 years (M = 22.56; SD = 3.04). Results showed that cybervictimization and cyberaggression exhibited the strongest …

Understanding Chatbot-Assisted Collaborative Learning Among Female Undergraduate Students, Mohammad Amin Kuhail, Ahmed Shuhaiber, Sinan Salman, Nazik Alturki

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Computer programming can be daunting for beginners due to complex concepts and syntax. Traditional teaching methods, while engaging through gamification and active learning, often lack personalized approaches. Recent advancements in artificial intelligence (AI), particularly large language models (LLMs), present new possibilities for personalized and interactive learning environments. This study introduces a chatbot-assisted collaborative learning environment (CCLE) that leverages an LLM (GPT-4) to enhance collaborative programming education. The CCLE enables real-time guidance and collaboration through natural language interactions, allowing students to work together on programming tasks, edit code collaboratively, and engage with both peers and the educational chatbot. We conducted an …

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

All Works

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 …

The Impact Of Generative Ai Training On Teachers’ Curriculum Adaptation Using Reflective Practices, Areej Elsayary

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Generative AI tools offer teachers opportunities to adapt curricula to meet diverse student needs. However, many educators lack the structured training and reflective frameworks necessary for effective and critical use of these tools. Numerous studies have examined the appropriate use of generative AI (GenAI) tools in facilitating differentiation, feedback, and personalized learning. However, teachers need to be trained on the “what” and “how” of integrating GenAI into curriculum adaptation to ensure a positive impact on student learning. This study evaluates the impact of training in-service teachers to use GenAI tools for curriculum adaptation. Specifically, the study investigates three research questions: …

Fig-Gan: Fundus Image Generation Via Deep Learning Based Generative Adversarial Network For Amd Disease Diagnosis, Kailasa Thrishul, Ahed Abugabah, Amina Salhi, Manel Ayadi, Mohamed M. Sithik, D. Jayaprakash, A. Ahilan

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Globally, age-related macular degeneration (AMD) remains a main cause of irreversible vision loss. Recently, deep learning models have primarily focused on classifying fundus images for early detection of AMD progression. However, existing models rarely address the generation of future progression-aware fundus images, particularly when complete real longitudinal follow-up scans are unavailable. This limitation makes it difficult to track retinal changes over time and highlights the need for generative models capable of producing realistic drusen-level structural variations. To address these issues, a novel deep learning-based FIG-GAN model is to generate synthetic future fundus images from baseline inputs. Multi-Attention U-Net (MAU-Net) is …

Image And Metadata-Driven Personality Inference For Career Recommendation: A Social Media-Based Ai Framework For Adolescents, Heba Ismail, Maryam Alhefeiti, Ashraf Khalil

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This study presents a novel AI-based framework that leverages Instagram image and metadata analysis to infer Big Five personality traits and deliver personalized career recommendations for high school students in the UAE. Addressing the limitations of traditional recommender systems that rely on self-reported questionnaires or text, the proposed approach uses multimodal visual features—including profile metrics, HSV color patterns, semantic image labels, and texture analysis—to enable a non-intrusive, scalable personalization method. A pilot study involving data from 30 student accounts served as a proof of concept. Correlation analysis identified profile and HSV features as the most predictive, and four machine learning …

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, …

Large Language Models In Nlp: Evolution, Architectural Trends, And Open Challenges, Haseeb Javed, Babar Shah, Farman Ali, Daehan Kwak

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The rise of Large Language Models (LLMs) has transformed how Natural Language Processing (NLP) and its subdomains are approached. Recent technological advancements have driven this transformation. This study offers researchers a detailed overview of LLMs, comparing them with traditional rule-based systems, statistical techniques, machine learning, neural networks, and the rise of transformer-based architectures. From a wider perspective, language models such as GPT, BERT, T5, PaLM, and LLaMA have facilitated the transformation of entire sectors, including healthcare and business, due to their highly scalable nature. Despite their wide range of applications, LLMs face numerous challenges, such as output biases, limited interpretability, …

Lee, Jay, Jay Lee

Queer Mississippi (Complete Collection)

Jimmie “Jay” Lee, a 2022 graduate of the University of Mississippi, disappeared from his off-campus apartment on July 8, 2022. Well-known in the LGBTQ+ community in Oxford, his friends created a social media campaign, "Justice for Jay Lee", to keep his name in the news and advocate for Queer and Black victims of crime until his remains were found in February 2025 in Carroll County.

His case was profiled by Dateline NBC on January 29, 2026. (Trailer: "Bringing Jay Home")

Tolkien Fanzine Dataset, 1967-2017 [Bulk 1969-1979], Robinson Ensz, Gabriel Marotto, Aidan Oakey, Ivy Stanich, Ethan Thomas

Tolkien Resources

This dataset reveals the heretofore hidden contents of fan magazines (fanzines) related to the works of J.R.R. Tolkien that were created from 1969 through the publication of Tolkien’s The Silmarillion in 1977. It supplements the earlier Tolkien Fandom Review by S. Gary Hunnewell that discussed fanzines created through 1968. The dataset provides an item level index of the fanzines’ content and is intended to aid researchers in Fan Studies. It is accompanied by an inventory document that lists the fanzine titles and provides brief notes about some of them. Data was drawn from Marquette’s large holding of Tolkien fanzines, including …

Students’ Perceptions At The University Of Puerto Rico Secondary School Regarding Cellphone Use In The School Environmen, Nicolás Ramos, Nydiaam Vilanova

IALS Journal

This mixed-methods study investigates students’ perceptions of cellphone use at the University of Puerto Rico Secondary School. Data were collected from 133 students through a structured electronic survey examining phone ownership, usage patterns, emotional responses, parental regulation, and opinions regarding cellphone restrictions in schools. Results indicate that most students perceive their cellphone use as appropriate, recognize both educational and social benefits, and oppose complete bans while supporting responsible use and guided autonomy. The findings suggest that schools should emphasize digital citizenship, self-regulation, and balanced technology use rather than punitive restrictions.

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 …

Shimmer Methodology: May 2026 Cultural Studies Association Of Australasia, Lola Montgomery

Staff Scholarship - Australia & Dubai

This webinar presents an overview of the contemporary state of creative-practice research and autotheory before introducing Shimmer, an emerging methodological framework developed through creative practice, postgraduate supervision, and reflective inquiry. The presentation argues that while creative-practice research has successfully established creative work as a legitimate form of knowledge production, and autotheory has legitimised lived experience as theoretical material, both traditions leave relatively under-theorised the embodied moment through which insight first emerges.

The significance of the work lies in its contribution to ongoing debates around embodiment, affect, intuition, and knowledge production within creative-practice research. Shimmer proposes a language for understanding …

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 …

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 …

Recombinant Hagfish Intermediate Filament Proteins Enable Neural Culture Substrates That Promote Neurite Extension And Reduce Oxidative Stress, Justin Jones, Kristin Durrant

Browse all Datasets

This dataset supports the production, characterization, and biological validation of a novel recombinant hagfish intermediate filament (rHIF) protein functionalized with spider silk motifs (rHIF-alpha-GRGGL). The data demonstrates a scalable bioprocess resulting in a 7.76 g/L yield, high structural alpha-helicity (77.2%), and significant support for N2a cells.

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 …

Review On Data Privacy And Security For Iot-Based Multifunctional Layers Of Cyber-Physical Systems In Smart Grids, Mohammad Kamrul Hasan, Md Mehedi Hasan, Nabeel Al-Qirim, Siti Norul Huda Sheikh Abdullah, Shayla Islam, Md Abdur Razzaque

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Smart grid cyber-physical systems (SG-CPS) are intelligent platforms that incorporate IoT-enabled multifunctional layers including the physical, perception, communication, cyber, and application layers. It includes supervisory control and data acquisition, wide-area measurement systems, and advanced metering infrastructure for remote data aggregation, monitoring, and control operations. From an environmental perspective, these green technologies support two-way operations, which generate and transmit data over wired and wireless communication systems. However, this critical infrastructure faces data privacy and cybersecurity challenges. Hence, extensive research is required to address data privacy and security gaps to strengthen national grid cybersecurity and reduce economic losses. Therefore, this review highlights …

In What Style Shall I Confront Them? The Role Of Social Relationships In Social Correction Of Misinformation Among The Uk And Arab Social Media Users, Muaadh Noman, Mohamed B. Almourad, Ala Yankouskaya, Firoj Alam, Raian Ali

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This study investigates how social factors influence the likelihood of employing direct or indirect communication styles when correcting misinformation on social media in two different cultural contexts, the United Kingdom (UK) and the Arab Gulf Cooperation Council (GCC) countries. We conducted an online survey, supported by vignettes, that involved 686 participants, 367 from the UK and 319 from the Arab GCC countries. Participants were presented with a misinformation scenario and asked about their likelihood of using direct or indirect communication styles to correct their acquaintances. The survey captured variations in gender similarity (same vs. different gender), social status (lower vs. …

Norris Burroughs, Mark Naison, Steven Payne

Oral Histories

No abstract provided.

Emerging Threats In Ai: A Detailed Review Of Misuses And Risks Across Modern Ai Technologies, Niyat Seghid, Farkhund Iqbal, Khalifa Al-Room, Áine Macdermott

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The swift evolution of artificial intelligence (AI) has enabled unprecedented capabilities across domains, while simultaneously introducing critical vulnerabilities that can be maliciously exploited or cause unintended harm. Although multiple initiatives aim to govern AI-related risks, a comprehensive and systematic understanding of how AI systems are actively misused in practice remains limited. This paper presents a systematic review of AI misuse across modern AI technologies. We analyze documented incidents, attack mechanisms, and emerging threat vectors, drawing from existing AI risk repositories, prior taxonomies, and empirical case reports. These sources are synthesized into a unified analytical framework that categorizes AI misuse across …

Critical Tourism Studies In Business Journals, Paolo Mura, Heather Jeffrey, Martin Sposato

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Business is commonly understood as a parent discipline of tourism research, making business journals essential for epistemological inquiry. This paper reviews tourism literature in business journals, analysing the presence of Critical Tourism Studies, which addresses limitations of management-oriented approaches. Our analysis reveals limited engagement with Critical Tourism Studies in business journals, only 27% of reviewed articles aligning with its tenets. We propose a framework for Critical Tourism Business Studies that identifies knowledge gaps and highlights future directions for scholars publishing tourism-related topics in business journals. This framework aims to bridge disciplinary gaps and enhance interdisciplinary research. The article contributes to …

Students’ Perceptions At The University Of Puerto Rico Secondary School Regarding Cellphone Use In The School Environmen, Nicolás Ramos, Nydiaam Vilanova

IALS Journal

This mixed-methods study investigates students’ perceptions of cellphone use at the University of Puerto Rico Secondary School. Data were collected from 133 students through a structured electronic survey examining phone ownership, usage patterns, emotional responses, parental regulation, and opinions regarding cellphone restrictions in schools. Results indicate that most students perceive their cellphone use as appropriate, recognize both educational and social benefits, and oppose complete bans while supporting responsible use and guided autonomy. The findings suggest that schools should emphasize digital citizenship, self-regulation, and balanced technology use rather than punitive restrictions.

Prevalence And Factors Associated With Regular Fast-Food Consumption Among The Adult Population In Qatar: Cross-Sectional Analysis From Qatar Biobank Cohort, Alaa Zuhair Massarweh, Lynne Alexandra Kennedy, Asayel Saleh, Aljazi Al-Thani, Ala Al Rajabi

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Background The Eastern Mediterranean Region has undergone a rapid nutrition transition over the last three decades, with healthier traditional table diets displaced by energy-dense convenience foods. To the best of our knowledge, this is the first large cohort-based estimate of regular fast-food consumption (RFFC >= 1 time/week) and its correlates among the adult population in Qatar using Qatar Biobank, a volunteer prospective cohort of Qataris and long-term residents.Methods A cross-sectional study using a simple randomized sample of 2,000 adult participants from the Qatar Biobank (QBB) longitudinal cohort. Dietary intake was assessed using a validated food-frequency questionnaire. RFFC was modeled as …

Usaid Grant Recipient Data Fy2002-2025, Susan Turner Haynes

Faculty Works

Grant recipient data from USAID from fiscal years 2002-2025.

Anonymized Survey Dataset On Road Safety Assessment During Construction Of Bus Rapid Transit (Brt) Corridors In Dar Es Salaam, Tanzania, Lorain Salufu

Open Data

This dataset contains anonymized survey responses collected for a study on road safety assessment during construction of the Dar es Salaam Bus Rapid Transit (BRT) Phase 3 corridor. The dataset includes responses from 400 participants, together with the survey. The data were collected to assess perceived safety conditions, adequacy of construction-phase safety measures, effectiveness of traffic diversions, and the effects of construction activities on road users and nearby communities. No personally identifiable information is included in the shared files.

01. Elfie, Second Edition (Novel - Ebook), Matthew Lipman

Early Elementary School Curriculum

Elfie is in the first grade and is so shy she can’t speak in class and can hardly even formulate a question. Yet little escapes her and her mind puzzles over everything that happens in class and at home. When the principal proposes a contest aimed at improving reasoning, her whole class is caught up in figuring out how sentences work and how distinctions and connections are made. At the same time, Elfie and her classmates discover many distinctions fundamental to inquiry: appearance and reality, the one and the many, parts and wholes, similarity and difference, permanence and change.

The Deepfake Litmus Test: A Multimedia Authenticity Mechanism, Amna Alzaabi, Hessa Alqubaisi, Fatima Alzaabi, Richard Ikuesan

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Deepfake technologies have made it increasingly difficult to distinguish authentic video content from manipulated media. This paper presents a forensic detection framework, referred to as the Litmus Test, which focuses on structural analysis of MP4 container files to detect signs of tampering. Unlike conventional AI-based approaches that operate as black boxes, this method examines the atomic composition of video containers to identify anomalies. The proposed method performs atom-level inspection of MP4 file hierarchies and structural markers to uncover anomalies indicative of synthetic manipulation. Evaluations using datasets such as CelebDF, UADFV, and DeeperForensics reveal that the framework can identify inconsistencies common …