Digital Commons Network^™

Implementing Lean Principles To Enhance Warehouse Operations At King Abdulaziz Air Base(Kaab): A Case Study Of Royal Saudi Air Force (Rsaf), Saleh A. Alghamdi

Theses and Dissertations

The Royal Saudi Air Force (RSAF) relies on efficient logistics to sustain readiness. At King Abdulaziz Air Base, warehouse receiving inefficiencies caused delays and waste. This study used Lean principles and a six-month time–motion analysis, with Pareto and Fishbone tools, to identify 55% waste in dead pile and 75% in palletized shipments. Standard times of 5.98 and 6.55 minutes were set. Key recommendations include SOPs, cross-training, forklift certification, layout redesign, and RFID. Lean adoption could save 100+ labor hours and $4,000 annually, improving safety, accuracy, and mission readiness.

Effect Of Workplace Design On Collaboration And Satisfaction In Space System Command, Joshua A. Hagood

Theses and Dissertations

This study addresses a significant knowledge gap regarding the influence of physical workplace design on employee collaboration and satisfaction with the physical environment within U.S. Space Force technical military organizations.  While seminal industry research consistently demonstrates that physical design and indoor environmental quality influence employee satisfaction and collaboration (e.g., Candido et al., 2015; Sailer et al., 2021), the understanding of these impacts within military contexts remains limited.  Using a quantitative post-occupancy evaluation survey, adapted from the Sustainable Post Occupancy Evaluation Survey (SPOES), multiple regression analyses revealed that physical elements collectively predict both satisfaction and collaboration.  The final simplified model showed …

Trends And Predictive Modeling Of Real Estate Prices In Major Saudi Arabia Cities, Meshal S. Aldahas

Theses and Dissertations

his research examines historical trends and explanatory modeling of real estate prices in major Saudi cities, with a focus on Riyadh, Jeddah, and Dammam. Using a mixed-methods approach, the study integrates quantitative data from 2010–2023, including housing and macroeconomic indicators, with qualitative insights drawn from over 320 survey responses that captured consumer sentiment on affordability, job security, and housing policies. A combination of descriptive statistics, ARIMA and Exponential Smoothing techniques was applied to detect long-term patterns, seasonal variations, and market shocks. Predictive modeling was conducted using Linear Regression, Decision Trees, and Neural Networks, with results showing that job security consistently …

A Review Of The United States' Long Term War Support Capabilities In The Indo-Pacific Command Region, Brian J. Mullin Jr.

Theses and Dissertations

This study examines U.S. maritime transportation readiness in the Indo-Pacific, highlighting fleet age, mariner shortages, shipyard decline, and port vulnerabilities. It also considers contested logistics and technological threats. Recommendations include fleet recapitalization, mariner pipeline growth, port diversification, and defensive upgrades. The study concludes that secure sea line assumptions are outdated and calls for greater resilience, with follow-on efficiency analysis proposed for ports and ships.

Comprehensive Study Of Integrating Clustering And Adversarial Learning For Enhanced Recommender Systems: A Systematic Review Of Hybrid Methodologies And Applications, M. E. Alqaysi, Murtadha M. Hamad, Ahmed Subhi Abdalkafor

Mesopotamian Journal of CyberSecurity

Recommender systems (RSs) have become critical elements in modern instances of information and decision-support systems, resulting in a transformation of user experiences through highly personalized suggestions for an undeniably vast range of items. Although RSs have become commonplace, they continue to evolve, and their challenges, including sparsity, cold-start, scalability, and vulnerability to adversarial challenges remain. The use of clustering methods has proven highly effective in resolving these issues through the discovery and exploitation of latent user behaviour patterns, segmenting user groups that contribute more towards personalized and adaptable RSs. Additionally, adversarial learning has become a growing focus of study as …

Multilevel Text Protection System Using Aes And Dwt-Dct-Svd Techniques, Nuha Mohammed Khassaf, Nada Hussein M. Ali

Mesopotamian Journal of CyberSecurity

In the digital age, protecting intellectual property and sensitive information against unauthorized access is of paramount importance. While encryption helps keep data private and steganography hides the fact that data are present, using both together makes the security much stronger. This paper introduces a new way to hide encrypted text inside color images by integrating discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD), along with AES-GCM encryption, to guarantee data integrity and authenticity. The proposed method operates in the YCbCr color space, targeting the luminance (Y) channel to preserve perceptual quality. Embedding is performed within …

Blockchain-Powered Dynamic Segmentation In Personal Health Record, Mishall Al-Zubaidie, Wid Alaa Jebbar

Mesopotamian Journal of CyberSecurity

Sensitive patient data must be handled securely in modern oncology care to protect patient privacy, regulatory compliance, and clinical decision-making integrity. Conventional centralized healthcare systems pose serious threats to patient confidentiality and treatment continuity because of their susceptibility to data breaches, illegal access, and single points of failure. This study suggests a blockchain-based decentralized cancer healthcare security solution. The proposed system is based on the idea of layers; each layer has a distinct function that gives it a feature that sets it apart from the others. A hierarchical clustering algorithm (HCA) is used in the first layer to determine the …

Blockchain-Based Accountability: A Systematic Literature Review, Nabeel Z. Tawfeeq, Dujan B. Taha

Mesopotamian Journal of CyberSecurity

The Blockchain algorithm has advanced the accountability and transparency of modern digital infrastructures. Enforcing responsible behavior and data integrity across distributed environments involves several key components, such as smart contracts, access control models, cryptographic techniques, and a decentralized identity framework. Because the blockchain ledger is immutable and transparent, once a transaction is recorded, it cannot be altered without detection, making fraudulent actions easily traceable and thereby ensuring accountability. However, the need for hybrid approaches that combine on-chain and off-chain solutions for an efficient reliability system introduces challenges, including privacy preservation, scalability, and regulatory compliance. This paper analyzes the effective features …

Global Research Trends And Collaboration In Mitre Att&Ck Framework: A Bibliometric And Network Analysis In Cybersecurity, Asad Maqsood, Syifak Izhar Hisham, Ahmad Firdaus

Mesopotamian Journal of CyberSecurity

The MITRE ATT&CK framework has become a foundational tool for organizing adversarial behaviors and techniques in cybersecurity. While its adoption in practice and academia has grown significantly, no prior bibliometric review has comprehensively mapped the global research landscape surrounding this framework. This study addresses that gap by conducting a systematic bibliometric and network analysis of publications related to ATT&CK indexed in Scopus from 2017 to 2025. Using VOSviewer and quantitative bibliometric methods, we analyzed 391 publications to identify trends in research output, influential works, key contributors, thematic areas, and patterns of collaboration. Results show exponential growth in studies related to …

A Proposed Algorithm For Avoiding Jammer In Structure-Free Wireless Sensor Networks, Zainab Shaker Matar Al-Husseini, Hussain K. Chaiel, Amel Meddeb, Ahmed Fakhfakh, Ahmed Fakhfakh

Mesopotamian Journal of CyberSecurity

Wireless Sensor Networks (WSNs) have emerged as a transformative technology with applications in critical and often inaccessible environments, including military and security domains. These networks comprise cooperative sensor nodes that gather and relay data to a base station. However, their inherent resource constraints—particularly the non-rechargeable nature of energy—pose a major challenge to network longevity and reliability. Conventional fixed-path transmission protocols exacerbate this issue, as energy-depleted or jammed nodes can disrupt communication, leading to partial or complete data loss. The primary objective of this study is to design and evaluate a structure-free transmission protocol that dynamically adapts data routing in order …

Improvement Of The Face Recognition Systems Security Against Morph Attacks Using The Developed Siamese Neural Network, Sura Abed Sarab Hussien, Thair Abed Sarab Hussien, Nada Hussein M. Ali

Mesopotamian Journal of CyberSecurity

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility …

Durability Of Tannin-Citric Acid Modified Scots Pine Against Weathering And Fungal Exposures, Sheikh Ali Ahmed, Gianluca Tondi, Reza Hosseinpourpia

Michigan Tech Publications

Wood modification is essential to enhance the performance and longevity of wood as a material while maintaining its natural and sustainable characteristics. By modifying wood, its properties can be significantly improved without the need for toxic preservatives. Thus bio-based wood modification is vital for enhancing wood properties sustainably, reducing environmental impact, and meeting the demand for eco-friendly, non-toxic, and renewable material solutions. In this study, bio-based formulae were used on pine sapwood for enhanced decay and weathering resistance. Quebracho tannin solutions (20 %) with different concentrations of citric acid (CA) as a cross-linker were prepared and then vacuum-pressure impregnated in Scots …

The Immeasurable Value Of Plankton To Humanity, Maria Grigoratou, Susanne Menden-Deuer, Abigail Mcquatters-Gollop, George Arhonditsis, Luis Felipe Artigas, Sakina-Dorothée Ayata, Dalida Bedikoğlu, Beatrix E Beisner, Bingzhang Chen, Claire Davies, Lillian Diarra, Owoyemi W Elegbeleye, Jason D Everett, Tatiane M Garcia, Wendy C Gentleman, Rodrigo Javier Gonçalves, Tamar Guy-Haim, Svenja Halfter, Jana Hinners, Richard R Horaeb, Jenny A Huggett, Catherine L Johnson, Maria T Kavanaugh, Ana Lara-Lopez, Christian Lindemann, Celeste López-Abbate, Monique Messié, Klas Ove Möller, Enrique Montes, Frank E Muller-Karger

School of Biological and Marine Sciences

Plankton, a diverse group of aquatic organisms, make Earth livable, regulate aquatic life, and provide benefits to human societies such as access to clean water, food security, and well-being. They also support economies and inspire biotechnological innovations. This article aims to raise awareness of the value of plankton to humanity and serves as an informative guide for aquatic professionals, policymakers, and anyone interested in plankton. We present the value of plankton across six themes of human interest: biogeochemistry; ecology; climate; the evolution of science; economy; and culture, recreation, and well-being. Guided by the 2022 Intergovernmental Science-Policy Platform on Biodiversity and …

Wind Turbine Rotor Design Using High-Fidelity Aerostructural Optimization, Marco Mangano, Sicheng He, Yingqian Liao, Denis-Gabriel Caprace, Andrew Ning, Joaquim R. R. A. Martins

Faculty Publications

Large wind turbines yield more energy but demand careful aeroelastic blade design. Coupled multiphysics design strategies can reduce wind energy costs exploiting fluid-structure interactions. This work presents the first high-fidelity aerostructural optimization study of a large wind turbine rotor.We use blade-resolved fluid dynamics and structural solvers in a monolithic gradient-based optimization framework to explore steady-state torque and blade mass trade-offs. The coupled-adjoint approach computes gradients efficiently, enabling the optimization of over 100 structural and geometric parameters simultaneously. Our optimization study modifies a DTU 10 MW benchmark with a simplified structure and isotropic material properties. The tightly coupled optimizations increase torque …

Effect Of Short-Chain Polymer Binders On The Mechanical And Electrochemical Performance Of Silicon Anodes, Fei Sun, L. Zurita-Garcia, Dean R. Wheeler

Faculty Publications

Polymer binders are crucial components in providing both mechanical support and chemical stability to the structure of porous Li-ion electrodes. Particularly in silicon anodes, the active material undergoes substantial volume expansion of up to 275%. Due to the mechanical constraint of the current collector, these silicon materials tend to expand in the normal direction while exhibiting substantial particle rearrangement and plastic deformation. Conventional rigid binders such as polyacrylic acid (PAA) and polyimide (PI), while providing satisfactory initial capacity, do not eliminate diminished long-term performance. Our research attempts to develop binder formulations that can accommodate sufficient flexibility for the substantial volume …

Opportunities And Impacts For Recreational Fishing From The Westport Development: Final Report, Matt Navarro, Michael Burton, Abbie Rogers, Joanna Pearce, Julian Clifton, Milena Kim, Clara Obregón

Reports accepted as research outputs

Executive summary: This project employs a mixed methods approach to evaluate the significance of Cockburn Sound for recreational fishers, examine the potential effects of the proposed port development on recreational fishing experiences, and understand fishers' preferences for initiatives to improve recreational fishing in Cockburn Sound. Initial qualitative interviews with six local recreational fishing stakeholders were conducted to establish an early understanding of the primary issues and contextual factors with respect to opportunities and impacts of the proposed Westport development. These were followed by on-site surveys at boat ramps and shore access points across Cockburn Sound and the surrounding region. In …

A Consensus Guide To Preclinical Indirect Calorimetry Experiments, Alexander S Banks, David B Allison, Thierry Alquier, Ansarullah, Steven N Austad, Johan Auwerx, Julio E Ayala, Joseph A Baur, Stefania Carobbio, Gary A Churchill, Morten Dall, Rafael De Cabo, Jose Donato, Nathalia R V Dragano, Carol F Elias, Anthony W Ferrante, Brian N Finck, Jose E Galgani, Zachary Gerhart-Hines, Laurie J Goodyear, Justin L Grobe, Rana K Gupta, Kirk M Habegger, Sean M Hartig, Andrea L Hevener, Steven B Heymsfield, Corey D Holman, Martin Hrabě De Angelis, David E James, Lawrence Kazak, Jae Bum Kim, Martin Klingenspor, Xingxing Kong, Sander Kooijman, Louise Lantier, K C Kent Lloyd, James C Lo, Irfan J Lodhi, Paul S Maclean, Owen P Mcguinness, Gema Medina-Gómez, Raghavendra G Mirmira, Christopher D Morrison, Gregory J Morton, Timo D Müller, Yoshihiro Ogawa, David Pajuelo-Reguera, Matthew J Potthoff, Nathan Qi, Marc L Reitman, Patrick C N Rensen, Jan Rozman, Jennifer M Rutkowsky, Kei Sakamoto, Philipp E Scherer, Gary J Schwartz, Radislav Sedlacek, Mohammed Selloum, Saame Raza Shaikh, Shuai Chen, Gerald I Shulman, Vojtěch Škop, Alexander A Soukas, John R Speakman, Bruce M Spiegelman, Gregory R Steinberg, Katrin J Svensson, John P Thyfault, Tony Tiganis, Paul M Titchenell, Nigel Turner, Licio A Velloso, Antonio Vidal-Puig, Christopher S Ward, Ashley S Williams, Christian Wolfrum, Allison W Xu, Ying Xu, Juleen R Zierath, International Indirect Calorimetry Consensus Committee (Iiccc)

Children’s Nutrition Research Center Staff Publications

Understanding the complex factors influencing mammalian metabolism and body weight homeostasis is a long-standing challenge requiring knowledge of energy intake, absorption and expenditure. Using measurements of respiratory gas exchange, indirect calorimetry can provide non-invasive estimates of whole-body energy expenditure. However, inconsistent measurement units and flawed data normalization methods have slowed progress in this field. This guide aims to establish consensus standards to unify indirect calorimetry experiments and their analysis for more consistent, meaningful and reproducible results. By establishing community-driven standards, we hope to facilitate data comparison across research datasets. This advance will allow the creation of an in-depth, machine-readable data …

Time-Frequency Fingerprint Analysis In Seeg Source-Space To Identify The Epileptogenic Zone, Yash Shashank Vakilna, Deniz Atilgan, Johnson Hampson, Chinmay Chinara, Takfarinas Medani, Richard M Leahy, Nuria Lacuey, Samden D Lhatoo, Sandipan Pati, John C Mosher, Jay R Gavvala

Faculty, Staff and Student Publications

This case study highlights the application of seizure fingerprint analysis in the source-space of stereo-EEG (SEEG) data to accurately localize the epileptogenic zone (EZ) in patients with complex cortical malformations. A 25-year-old female with extensive bilateral perisylvian polymicrogyria (PMG) presented with intractable focal seizures. The source-level analysis performed in Brainstorm using the sLORETA imaging algorithm subsequently showed EZ fingerprint analysis. The patient underwent MR-guided laser interstitial thermal therapy (LITT), targeting the identified EZ, resulting in postoperative seizure freedom with minimal complications. Extending the analysis from the sensor-space to the source-space could further enhance surgical planning and improve outcomes in complex …

Minimally Invasive, Bioadaptive Multimodal Sensor Probe With Safe Deployment For Real-Time Acute Compartment Syndrome Diagnosis, Seung Gi Seo, Amanda M Westman, William Moritz, Joseph Ribaudo, Mitchell A Pet, Et Al.

2020-Current year OA Pubs

Acute Compartment Syndrome (ACS) is a serious medical condition that arises from increased pressure within osteofascial compartments, leading to impaired blood flow and potential tissue damage. Early and accurate diagnosis is critical for preventing permanent damage. Current methods rely largely on qualitative assessments with limited accuracy, and those that exploit invasive pressure measurements often prove inadequate. Herein, a soft materials-based multimodal sensor probe is introduced, as well as the mechanical and thermal influences to monitor intra-compartmental pressure, tissue oxygen saturation (StO

Enhanced Key Generation Method Using Deep Q-Networks Algorithm With Chaotic Maps, Ali A. Mahdi, Mays M. Hoobi

Mesopotamian Journal of CyberSecurity

In contemporary digital environments, exponential cyber threat growth has made cryptographic key generation a critical security challenge. Traditional Pseudo-Random Number Generators (PRNGs) and existing chaos-based methods often exhibit insufficient entropy, limited randomness quality, and inadequate resistance to statistical attacks. Current implementations frequently produce suboptimal entropy values and fail to meet modern cryptographic security standards and rigorous randomness testing protocols. This paper aims to design and implement an advanced cryptographic key generation system that combines Deep Q-Networks (DQN) algorithms with multiple chaotic maps to produce cryptographically secure stream key bits with high randomness and strong resistance to cryptanalytic attacks. The proposed …

Mitigating Zero-Day Vulnerabilities In Iiot Systems: Challenges And Advances In Ai-Powered Intrusion Detection Systems, Khalid Asaad Hashim, Yusnani Binti Mohd Yussoff, Shahrani Binti - Binti Shahbudin

Mesopotamian Journal of CyberSecurity

Zero-day attacks are one of the great challenges that intrusion detection systems have been facing and keep on facing today, especially worsening within Industrial Internet of Things environments since their ability to take advantage of unknown vulnerabilities results in a high rate of false negatives. It is under this framework that this paper presents a set of experiments that have been carried out with the objective of analyzing the consequences of zero-day attacks with regard to performance degradation in Intrusion Detection System (IDS) and, secondly, and with greater emphasis, about those failings which have been pointed out up to now …

Improving Hospital 30-Day Readmission Rates Through Post-Discharge Follow-Up Phone Calls, Maureen R. Wright

DNP and Student Works

Background: Thirty-day hospital readmissions compromise patient safety, increase mortality risk, and impose financial penalties on hospitals. Ineffective discharge education and care transitions leave patients vulnerable after discharge. Evidence shows that post-discharge follow-up calls within 24–72 hours can identify risks early and reduce preventable readmissions.

Purpose: This Doctor of Nursing Practice (DNP) project aimed to reduce 30-day hospital readmission rates by implementing post-discharge follow-up telephone calls guided by the Agency for Healthcare Research and Quality (AHRQ) Re-Engineered Discharge (RED) Toolkit.

Methods: Registered nurses conducted structured follow-up calls within 24–72 hours of discharge from the medical-surgical unit, reviewing health status, medications, appointments, …

Robust Ai Solutions For Financial Markets Through Generative Modeling, Dynamic Graph Learning, And Reinforcement-Based Portfolio Optimization, Jingyi Gu

Dissertations

Financial markets are inherently uncertain and dynamic, driven by complex factors such as macroeconomic signals, investor sentiment, and evolving inter-asset relationships. While machine learning has advanced financial modeling, existing approaches often fall short in addressing the real-world intricacies of finance. This dissertation confronts two critical challenges, human-driven stochasticity and risk-intensive decision-making under real-world trading constraints, while seizing a pivotal opportunity, the structural dynamics of evolving financial systems. These elements are foundational to advancing robust and practical financial intelligence.

To this end, this dissertation develops a unified framework for robust financial modeling and decision-making. The framework is architected as a progressive, …

Large-Scale Graph Algorithms And Applications With An Emphasis On Fintech Data, Fuhuan Li

Dissertations

Graph algorithms are essential analytical tools with applications spanning cybersecurity, biology, social media, and increasingly, financial technology (FinTech). The complex and interconnected nature of financial data, particularly in cryptocurrency networks, presents unique opportunities for graph-based analysis in fraud detection and anomaly identification.

This dissertation presents the design and implementation of scalable graph algorithms tailored for large-scale networks, with particular emphasis on FinTech applications. The primary contributions include: (1) novel cover-edge based triangle counting algorithms that significantly reduce computational overhead through breadth-first search preprocessing, achieving substantial speedups over traditional methods and dramatic communication reduction in distributed settings, (2) optimized parallel implementations …

Bodipy-Based Photocages For The Controlled Release Of Hydrogen Sulfide And Persulfides, Yanmei Li

Dissertations

Reactive sulfur species (RSS) such as hydrogen sulfide (H2S) and hydropersulfides (RSSH) are crucial mediators in a variety of physiological and pathological processes. Their regulatory roles span from maintaining cellular redox balance to influencing signaling pathways critical for homeostasis and stress responses. This dissertation investigates H2S and RSSH as biologically important molecules and explores the development of boron-dipyrromethene (BODIPY)-based photocages for its controlled, light-triggered release. Given H2S and RSSH's critical role in redox regulation and cellular protection, achieving spatiotemporal control over its delivery is essential for both therapeutic and research applications. BODIPY scaffolds offer favorable photophysical properties, including visible-light activation …

Reduced Order Models Of Hydrodynamically Interacting Flapping Wings, Jose Pabon

Dissertations

Fish schools exhibit a collective behavior and self-organization that is mediated by hydrodynamic interactions between individual fish. However, the long-time evolution of hydrodynamically interacting collectives is challenging to investigate due to the persistent influence of long-lived vortical structures, and the high-resolution requirements of direct numerical simulation at large Reynolds numbers. Reduced-order models have therefore played an important role in theoretical investigations of collectives of swimming bodies. The main results detailed herein are several new reduced-order models of swimmers that self-propel by flapping, i.e., by executing a prescribed periodic rigid body motion. The models are extensions of a discrete-time dynamical system …

Optimizing Hip And Knee Assistance For Walking And Sit-To-Stand Transitions: An Intrinsic Muscle Mechanics Based Predictive Approach, Neethan Ratnakumar

Dissertations

As the global population ages, the demand for wearable assistive technologies continues to rise, driven by their potential to enhance mobility and independence in older adults. Effectively designed controllers for lower-limb exoskeletons to assist sit-to-stand (STS) and walking are crucial for delivering efficient, safe, and comfortable assistance during daily activities. Traditionally, controller optimization involves biomechanical modeling and user-specific customization. Musculoskeletal simulations play a central role in this process by providing insights into human-exoskeleton interaction dynamics, thereby informing and refining control strategies.

This work presents a simulation-driven approach for developing exoskeleton controllers for walking and STS using two distinct methods: optimal …

Braingenebot: A Framework For Variant Prioritization And Generative Pretrained Transformer-Informed Interpretation Across Polygenic Risk Score Studies, Gang Qu, Nitesh Enduru, Xinyi Liu, Xiaoqian Jiang, Zhongming Zhao

Faculty, Staff and Student Publications

Polygenic risk scores (PRS) are widely used to assess genetic susceptibility in Alzheimer's disease (AD) research. However, the rapid expansion of PRS studies has led to dataset-specific biases-stemming from factors like population makeup, genotyping methods, and analysis pipelines-that result in inconsistent variant prioritization and limit generalizability and reproducibility. To address these challenges, we propose a transductive learning framework that integrates multiple PRS datasets for more robust risk variant prioritization, incorporating genome-wide association study (GWAS) priority scores as biologically informed priors. Additionally, we introduce BrainGeneBot, an AI-driven tool leveraging generative pretrained transformers with retrieval-augmented generation technology to streamline genomic analyses in …

Exploring Technology-Enhanced Learning: A Comparative Study Of Online And Offline Interactive Practices In The Iranian Higher Education System, Naser Rashidi, Mohamad Reza Farangi, Ali Hosseini

The Qualitative Report

This study explored how interactive teaching and learning are enacted through technology-enhanced methods in Iran’s higher education system. Using an exploratory qualitative design, it investigated the pedagogical strategies employed by instructors and examined whether these practices align with the principles of Technology-Enhanced Learning (TEL) across online and in-person contexts. Data were collected through the analysis of 263 class reports and 37 semi-structured interviews with university instructors. Thematic analysis using MAXQDA revealed six cohesive and interpretive themes: fostering human connection, empowering student voices, learning as dialogue, adaptive teaching, multimodal engagement, and feedback as dialogue. These themes reflect a holistic view of …

Patient Education On Conversion From Oral Art/Prep To Long-Acting Injectable (Lai) To Improve Patient Treatment Adherence, Marnel Reina Mae M. Hernandez

Doctor of Nursing Practice Final Manuscripts

Patient Education on conversion from oral ART/PrEP to Long-Acting Injectable (LAI) improves patient adherence.

Marnel Reina Mae Hernandez, MSN, RN

Joseph, F. Burkard, DNSc, CRNA, EBP-C

Background: Long-acting injectables (LAI) have been shown to be equally effective in viral load suppression. Implementing nurse led educational interventions in the use of oral treatment to LAI will address if LAI prescriptions can improve adherence and patient retention. Despite the availability of LAI for ART (antiretroviral treatment) and PrEP (pre-exposure prophylaxis for HIV) patients continue to have a low appointment adherence which can impact adherence and overall viral detectability. LAIs will continue to …