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Ai-Powered Operations: Navigating Ethics, Automation, And Strategic Innovation In The Digital Era, Lordt Becklines, Omar F. El-Gayar Jan 2025

Ai-Powered Operations: Navigating Ethics, Automation, And Strategic Innovation In The Digital Era, Lordt Becklines, Omar F. El-Gayar

Research & Publications

Artificial Intelligence (AI) is redefining Operations Management (OM) by transforming how organizations plan, execute, and optimize their core processes. This TREO Talk presents a comprehensive synthesis of AI’s evolution and impact in OM, underscoring its role as a strategic enabler of agility, resilience, and innovation in digitally driven enterprises. Leveraging a Systematic Literature Review (SLR) guided by PRISMA methodology across nine scholarly databases, this research constructs a validated framework that captures the multidimensional role of AI in transforming operational strategies, capabilities, and outcomes across industries. AI's influence spans predictive analytics, robotic process automation, supply chain orchestration, logistics, and real-time quality …

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Non-Functional Requirementsand Key Propositionselicitation For An Hdss:A Grounded Theory Approach, Mohammad Tafiqur Rahman, Omar F. El-Gayar Jan 2025

Non-Functional Requirementsand Key Propositionselicitation For An Hdss:A Grounded Theory Approach, Mohammad Tafiqur Rahman, Omar F. El-Gayar

Research & Publications

Deciding humanitarian actions during relief distribution is a crucial and challengingtask.Humanitarian decision-makers (HDM) make manycritical decisions during disaster responses,but they sufferfrom incomplete, irrelevant, and sometimes excessive humanitarian operations-related disaster datain many situations.Hence, for constructive and meaningful support in decision-making, HDMs oftenappreciate computer-basedinformation systems(IS) (i.e. humanitarian decision support systems) that require non-functional requirements (NFRs) for their development. To identify those necessary NFRs, we applied the grounded theory approach to analyze 61 literature-and field-based decision-making parameters reported in the primary author's previous research (Rahman and Majchrzak (2020)). Our analysis resulted in 13 essentialNFRs and four key propositions to guide relief distribution decision-making …

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Evaluating Topic Models With Openai Embeddings: A Comparative Analysis On Variable-Length Texts Using Two Datasets, Abdullah Wahbeh, Mohammad Al-Ramahi, Omar F. El-Gayar, Ahmed Elnoshokaty, Tareq Nasralah Jan 2025

Evaluating Topic Models With Openai Embeddings: A Comparative Analysis On Variable-Length Texts Using Two Datasets, Abdullah Wahbeh, Mohammad Al-Ramahi, Omar F. El-Gayar, Ahmed Elnoshokaty, Tareq Nasralah

Research & Publications

Topic modeling is a crucial unsupervised machine learning technique for identifying themes within unstructured text. This study compares traditional topic modeling methods, like Latent Dirichlet Allocation (LDA), against advanced embedding-based models, specifically BERTopic-OpenAI. The analysis utilizes two distinct datasets: user reviews from the mental health app Replika and the 20newsgroup dataset. For the Replika dataset, both methods identified common themes, but BERTopic-OpenAI uncovered additional nuanced topics, demonstrating its enhanced semantic capabilities. Quantitative evaluation of the 20newsgroup dataset further highlighted BERTopic-OpenAI's advantage through achieving higher topic coherence and diversity than the best-performing LDA model. These results suggest that embedding-based models provide …

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A Review Of Reasoning In Artificial Agents Using Large Language Models, Nagraj Naidu, Omar F. El-Gayar Jan 2025

A Review Of Reasoning In Artificial Agents Using Large Language Models, Nagraj Naidu, Omar F. El-Gayar

Research & Publications

The increasing sophistication and the use of large language models (LLMs) in artificial agents highlights the need to investigate their reasoning capabilities and limitations. Understanding these aspects is crucial, given the integral role of reasoning in decision-making processes, which are central to a software or embodied agent. This research paper presents a systematic review of the topic. We review the literature by selecting and analyzing highly cited papers using both PRISMA and snowballing. The gathered literature is categorized using a detailed framework of facets and categories. In the results section, we elaborate on our findings and illustrate the mapping through …

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Exploring The Interoperability For Information Exchange Between Acute And Post-Acute Care Settings, Madhu Gottumukkala, Cherie Noteboom, Omar F. El-Gayar Jan 2025

Exploring The Interoperability For Information Exchange Between Acute And Post-Acute Care Settings, Madhu Gottumukkala, Cherie Noteboom, Omar F. El-Gayar

Research & Publications

The seamless transfer and assimilation of healthcare data are foundational to delivering holistic, timely, and effective patient care across the healthcare spectrum. However, disparities in Electronic Health Record (EHR) system adoption, especially in long-term and post-acute care (LTPAC) settings, consistently obstruct interoperability. This study explores the factors that impede and facilitate health information exchange in LTPAC environments, focusing on technical and organizational facets. Grounded theory guided our qualitative case study research, involving 35 stakeholder interviews. Key technical findings highlight the need for integrated, reliable data structures, robust infrastructure, and standardized practices. Organizational insights reveal a shift towards integrative, patient-centric strategies …

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Latent Subtypes Of Comorbidities In Multiple Sclerosis Patients: Insights From Social Media, Laxmi Manasa Gorugantu, Nevine Nawar, Omar F. El-Gayar Jan 2025

Latent Subtypes Of Comorbidities In Multiple Sclerosis Patients: Insights From Social Media, Laxmi Manasa Gorugantu, Nevine Nawar, Omar F. El-Gayar

Research & Publications

Multiple Sclerosis is a chronic neurological disease associated with various physical and cognitive impairments. Individuals with MS might also experience medical and psychiatric comorbidities that can exacerbate the severity of the disease and lower their overall well-being. Therefore, it becomes essential to identify these co-occurring health conditions at the early stages to optimize treatment and improve patient outcomes. Consequently, the objective of this study is to explore the commonly occurring comorbidities among MS patients around the globe from social media discourse. Furthermore, it aims to unveil public perceptions, providing insights that might not be captured via clinical research methods. The …

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Highlighting Competency Gaps In Health Informatics Education Using Advanced Text-Embedding Models, Omar F. El-Gayar, Abdullah Wahbeh, Mohammad Al-Ramahi, Ahmed Elnoshokaty Jan 2025

Highlighting Competency Gaps In Health Informatics Education Using Advanced Text-Embedding Models, Omar F. El-Gayar, Abdullah Wahbeh, Mohammad Al-Ramahi, Ahmed Elnoshokaty

Research & Publications

The healthcare sector anticipates substantial growth, with 125,000 job openings by 2026, including 69,000 middle-skilled positions. Despite this growth, data use and integration inefficiencies cost the sector $750 billion annually. Health informatics, an interdisciplinary field blending healthcare, computer, information, and cognitive sciences, can address these challenges through enhanced healthcare management via information technology. However, there is a critical disparity between competencies taught in educational programs and those demanded by the job market. This study examines competencies from job postings on Indeed.com and accredited health informatics programs, comparing them with the Health Information Technology Competencies (HITComp) database. Utilizing advanced text-embedding models, …

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Towards Adaptive Learning: A Review Of Machine Learning On Lms Data, Cindy Zhiling Tu, Gary Yu Zhao, Omar F. El-Gayar Jan 2025

Towards Adaptive Learning: A Review Of Machine Learning On Lms Data, Cindy Zhiling Tu, Gary Yu Zhao, Omar F. El-Gayar

Research & Publications

This study presents a literature survey on the application of machine learning (ML) in learning management system (LMS) data analytics, aiming to provide insights into adaptive learning development and propose an agenda for future research. The literature survey is based on a proposed adaptive learning framework and critically analyzes the results within this context. The results reveal that machine learning methods can be used to evaluate the effectiveness of instructional interventions and combining online behaviors with textual data can improve the outcome of performance prediction. Key findings also highlight several open issues, including using small datasets and the need for …

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Generative Ai And Academic Integrity In Higher Education: A Systematic Review And Research Agenda, Kyle Bittle, Omar F. El-Gayar Jan 2025

Generative Ai And Academic Integrity In Higher Education: A Systematic Review And Research Agenda, Kyle Bittle, Omar F. El-Gayar

Research & Publications

This systematic literature review rigorously evaluates the impact of Generative AI (GenAI) on academic integrity within higher education settings. The primary objective is to synthesize how GenAI technologies influence student behavior and academic honesty, assessing the benefits and risks associated with their integration. We defined clear inclusion and exclusion criteria, focusing on studies explicitly discussing GenAI’s role in higher education from January 2021 to December 2024. Databases included ABI/INFORM, ACM Digital Library, IEEE Xplore, and JSTOR, with the last search conducted in May 2024. A total of 41 studies met our precise inclusion criteria. Our synthesis methods involved qualitative analysis …

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A Systematic Literature Review Of Ai, Education, And Change In Radiology Practice, Cherie Noteboom, Vahini Atluri, Sai Mounika Chintalapudi Jan 2025

A Systematic Literature Review Of Ai, Education, And Change In Radiology Practice, Cherie Noteboom, Vahini Atluri, Sai Mounika Chintalapudi

Research & Publications

Radiology is undergoing a role change as Artificial Intelligence (AI) becomes increasingly embedded in clinical workflows, reshaping the roles, responsibilities, and educational needs of radiologists. As professionals known for their autonomy and expertise, radiologists face significant transitions that require effective change management and educational support. The systematic literature review is guided by the PRISMA methodology and synthesizes findings from peer-reviewed research between 2019 and 2024 to explore how AI integration influences radiology practice and training. Anchored in the GrandFusion Framework—a novel theoretical synthesis of Dewey’s Experiential Learning, Simon’s Bounded Rationality, Lewin’s Change Management, Davis’s Technology Acceptance Model, and Rogers’s Diffusion …

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From Imaging To Insights: Ai’S Role In Radiology Transformation Through 2pdt And 4aim, Cherie Noteboom, Sai Mounika Chintalapudi, Vahini Atluri Jan 2025

From Imaging To Insights: Ai’S Role In Radiology Transformation Through 2pdt And 4aim, Cherie Noteboom, Sai Mounika Chintalapudi, Vahini Atluri

Research & Publications

Artificial intelligence (AI) is progressively integrated into radiologists' processes, improving diagnostic precision, decision-making, and operational efficiency. This systematic literature review (SLR) is a Meta- analysis utilizing the PRISMA framework that investigates the transformative impact of AI in radiology by analyzing studies published from January 2019 to December 2024 across the academic databases of ACM Digital Library, IEEE/IET, Elsevier ScienceDirect, ProQuest, and PubMed. The research employs the People, Process, Data, and Technology (2PDT) framework to classify AI technologies and assess their effects on patient outcomes, radiologists' experiences, and healthcare system performance. The findings indicate the substantial contributions of AI, including enhanced …

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A Systematic Literature Review On Ai Chatbots In Automating Customer Support For E-Commerce, Sai Mounika Chintalapudi, Omar F. El-Gayar, Cherie Noteboom Jan 2025

A Systematic Literature Review On Ai Chatbots In Automating Customer Support For E-Commerce, Sai Mounika Chintalapudi, Omar F. El-Gayar, Cherie Noteboom

Research & Publications

The rapid advancement of artificial intelligence (AI) has significantly transformed the e-commerce sector, particularly through the integration of AI-powered chatbots. This study conducts a systematic literature review to examine how chatbots align with the eight foundational features of e-commerce technology: ubiquity, global reach, universal standards, interactivity, information richness, information density, personalization/customization, and social technology. Guided by the PRISMA framework, the review addresses two primary research questions: (1) How do AI-driven chatbots support the unique features of e-commerce technology? and (2) What technological advancements enhance their functionality in this context? Relevant literature was retrieved from five major academic databases: ACM Digital …

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Mapping The Intersection Of Blockchain And Project Management: A Bibliometric Review, Cherie Noteboom, David Zeng, Sai Neelima Seru, Sai Mounika Chintalapudi Jan 2025

Mapping The Intersection Of Blockchain And Project Management: A Bibliometric Review, Cherie Noteboom, David Zeng, Sai Neelima Seru, Sai Mounika Chintalapudi

Research & Publications

This study presents a bibliometric analysis of 93 peer-reviewed articles examining the intersection of blockchain technology and project management. Utilizing PRISMA and analytical tools such as VOSviewer, bibliometrix R, and python, it identifies publication trends, keyword co-occurrence, and three thematic clusters: blockchain infrastructure, project management, and industry application domains. Results reveal rapid growth since 2018 and conceptual tensions between centralized project methods and decentralized technologies. This analysis contributes a structured overview of how blockchain is reshaping project environments, offering insights for both researchers and practitioners seeking to align emerging technologies with project governance and execution models.

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The Impact Of Knowledge Management In The Banking Industry: A Systematic Literature Review, Sai Anurag Illendula, Omar El-Gayar Jan 2025

The Impact Of Knowledge Management In The Banking Industry: A Systematic Literature Review, Sai Anurag Illendula, Omar El-Gayar

Research & Publications

The banking industry is experiencing unprecedented transformation due to rising employee turnover, increasing regulatory pressures, and intense competition from fintech companies offering personalized digital services. In this knowledge-intensive and low-margin environment, effective Knowledge Management (KM) is critical for maintaining a competitive edge. Despite its importance, the relationships between KM processes, performance outcomes, and mediating variables remain underexplored. This study conducts a Systematic Literature Review (SLR) of peer-reviewed journal articles to investigate how KM influences both organizational performance (OP) and employee performance within the banking sector. The review reveals that effective KM processes enhance efficiency, foster innovation, mitigate risks, and empower …

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Enhancing Climate Change Mitigation: An Ai-Based System For Real-Time Monitoring Of Environmental Changes Using Satellite Data, Yesu Vara Prasad Kollipara, Omar El-Gayar Jan 2025

Enhancing Climate Change Mitigation: An Ai-Based System For Real-Time Monitoring Of Environmental Changes Using Satellite Data, Yesu Vara Prasad Kollipara, Omar El-Gayar

Research & Publications

This study presents a real-time AI system for environmental monitoring using satellite imagery. The framework integrates EfficientNet-B0 with attention for spatial classification, LSTM for temporal forecasting, and transfer learning for cross-satellite generalization. Trained on EuroSAT and validated on Landsat-8, the system achieved 77.7% classification accuracy with inference times under 0.15 seconds per image. A cloud-based dashboard enables visualization of deforestation, carbon trends, and land cover changes for policymakers. Aligned with SDG 13 and CORSIA, the approach demonstrates scalability, efficiency, and policy relevance, offering a practical AI-based tool for climate change mitigation.

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Systematic Review Of Lattice-Based Cryptography Algorithms For Securing Blockchain Networks In The Post-Quantum Era, Salim Arfaoui, Omar El-Gayar Jan 2025

Systematic Review Of Lattice-Based Cryptography Algorithms For Securing Blockchain Networks In The Post-Quantum Era, Salim Arfaoui, Omar El-Gayar

Research & Publications

The rise of quantum computing threatens blockchain security as traditional cryptographic schemes become vulnerable. Lattice-based cryptography has emerged as a promising quantum-resistant solution. This systematic literature review uniquely provides an in-depth, blockchain-specific analysis of lattice-based cryptographic integration challenges. Following PRISMA guidelines, we analyzed 48 studies published between 2017-2025 from major academic databases. Unlike previous reviews that broadly examine post-quantum cryptography, we identify critical blockchain-specific implementation barriers, performance bottlenecks, and standardization gaps. Key challenges include computational overhead, protocol compatibility, and the need for lightweight cryptographic standards. Despite these challenges, lattice-based cryptography demonstrates significant potential for enhancing blockchain security in the quantum …

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Knowledge Management Processes For Improving Supply Chain Performance - A Systematic Literature Review, Sai Neelima Seru, Omar El-Gayar Jan 2025

Knowledge Management Processes For Improving Supply Chain Performance - A Systematic Literature Review, Sai Neelima Seru, Omar El-Gayar

Research & Publications

This study presents a systematic review of 36 articles published between 2020 and 2025 to explore how knowledge management processes improve supply chain performance. Using the Resource-Based, Knowledge-Based, and Dynamic Capability View as theoretical lenses, the review examines KM processes - creation, storage, sharing, and application across the People-Process-Technology (PPT) dimensions. The findings show that KM enhances collaboration, agility, resilience, innovation, and sustainability by balancing human enablers, structured processes, and digital technologies. The review positions KM as a strategic capability and suggests that future research should explore KM integration with AI and blockchain to build smarter, more adaptive supply chains.

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Adapting Project Management Life Cycles For Blockchain Implementation: A Thematic Pilot Study., Cherie Noteboom, Aravindh Sekar, Deb Tech Jan 2025

Adapting Project Management Life Cycles For Blockchain Implementation: A Thematic Pilot Study., Cherie Noteboom, Aravindh Sekar, Deb Tech

Research & Publications

Blockchain implementation challenges traditional project management practices due to its decentralized, cross-organizational nature. This exploratory study examines how project management life cycle processes must adapt to support successful blockchain adoption. Using open coding and thematic analysis of five expert interviews, key themes were identified and mapped to the five PMBOK process groups. The findings reveal that blockchain projects demand broader stakeholder engagement, iterative planning, human-centered execution, decentralized monitoring, and long-term sustainability planning. By aligning emergent themes with established project management phases, this study highlights the need for a flexible, ecosystem-focused approach to managing blockchain initiatives. The results offer practical insights …

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Germination Capacity Of Artemisia Umbelliformis Lam. Wild Populations And Agro-Techniques To Enhance Seedling Production, Matteo Case, Eric Mozzanini, Andrea Mainett, Íris Marisa Maxaieie Victorino, Erica Lumini, Sonia Demasi, Valeria Bianciotto, Laura Poggio, Valentina Scariot Jan 2025

Germination Capacity Of Artemisia Umbelliformis Lam. Wild Populations And Agro-Techniques To Enhance Seedling Production, Matteo Case, Eric Mozzanini, Andrea Mainett, Íris Marisa Maxaieie Victorino, Erica Lumini, Sonia Demasi, Valeria Bianciotto, Laura Poggio, Valentina Scariot

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Artemisia umbelliformis Lam. is an alpine herbaceous species that grows in the wild and is mainly used for producing génépi liqueur. It has applications as an ingredient in several food products. Its propagation and cultivation have become the only way to ensure a sustainable supply, thus conserving its occurrence in natural habitats. However, low success rates in seed germination usually limit its propagation. Selected seeds and fine-tuned agro-techniques are priorities in nursery production systems. The current research explored seed germination in three wild A. umbelliformis populations from Valnontey, Soana, and Urtier in the Italian Alps. We evaluated seed germination ability …

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Investigating Tree Diversity And Structure Across Varying Land Cover Classes And Altitudes In The Savanna Woodlands Of Sudan, Nasradeen A. H Gadallah, Zoro Bertin Gone B, Victor Ongoma, Abdelhakam Esmaeil Mohamed Ahmed, Ahmed M. M. Hasoba, Ahmed A. H Siddig Jan 2025

Investigating Tree Diversity And Structure Across Varying Land Cover Classes And Altitudes In The Savanna Woodlands Of Sudan, Nasradeen A. H Gadallah, Zoro Bertin Gone B, Victor Ongoma, Abdelhakam Esmaeil Mohamed Ahmed, Ahmed M. M. Hasoba, Ahmed A. H Siddig

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Climate and land use changes significantly endanger tree species’ structure and diversity in savanna woodlands. The destruction of these ecosystems hinders the achievement of several global environmental and development targets, notably SDGs 2, 13, and 15, which underscores the need for continuous tree monitoring to inform decision-making on biodiversity conservation. This study aims to characterize the relationships between tree diversity and structure across different land cover (LC) classes—Dense tree cover (D), Sparse tree cover (S), Grasslands (G), and Wetlands (W)—and altitudinal gradients (AGs) in Alain forest, located in Sudan’s savanna woodlands. A systematic sampling was used across varying AGs and …

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Barriers To Ensuring And Sustaining Street Food Safety In A Developing Economy, Abigail Ampomah Adaku, Irene Susana Egyir, Cynthia Gadegbeku, Angela Parry-Hanson Kunadu, Vincent Amanor-Boadu Jan 2025

Barriers To Ensuring And Sustaining Street Food Safety In A Developing Economy, Abigail Ampomah Adaku, Irene Susana Egyir, Cynthia Gadegbeku, Angela Parry-Hanson Kunadu, Vincent Amanor-Boadu

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Street foods are one of the highest contributors to foodborne illness in most developing economies around the world. In Ghana, diarrhoeal diseases, which are usually food or waterborne, are among the top ten causes of death. Most street food safety risks are avoidable when all food safety regulations are complied with. This paper identified and examined the barriers to the implementation of street food safety regulations in Ghana. A qualitative research approach was adopted by collecting data from nine focus group discussion sessions involving a total of 94 participants and five key informant interviews. The research uncovered three broad but …

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Environmental Determinants Of Tree Productivity And Biomass Carbon Stock In Semiarid Ethiopia, Haftu Abrha, Victor Ongoma, Soro Dodiomon, Berihu Tesfamariam, Girmay Gebresamuel, Haftom Hagos, Mamadou Cherif, Emiru Birhane Jan 2025

Environmental Determinants Of Tree Productivity And Biomass Carbon Stock In Semiarid Ethiopia, Haftu Abrha, Victor Ongoma, Soro Dodiomon, Berihu Tesfamariam, Girmay Gebresamuel, Haftom Hagos, Mamadou Cherif, Emiru Birhane

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Trees are crucial for climate change mitigation and adaptation. Assessing their ability at the individual tree level is effective because it allows precise quantification of carbon storage, which supports better management and conservation strategies for climate change responses. This study quantifies the carbon stock of Dobera glabra and examines how environmental factors such as land-use changes, soil properties, and tree size affect fruit occurrence in Ethiopia. Using a systematic random sampling design, 25 plots (20 m × 20 m) per land use type were established, where presence, tree growth, fruit and soil properties were measured. Logistic regression examined relationships between …

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A Feasibility Study On Barriers To Access To Solar Photovoltaic Energy: A Survey Study Of Moundou, Chad, Latchiba Wakiang Emile, Sebastian M. Waita, Robert Krueger, Julius Mwakondo Mwabora Jan 2025

A Feasibility Study On Barriers To Access To Solar Photovoltaic Energy: A Survey Study Of Moundou, Chad, Latchiba Wakiang Emile, Sebastian M. Waita, Robert Krueger, Julius Mwakondo Mwabora

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It is widely acknowledged that energy sources such as the sun are potential providers of clean, limitless, and free energy that could satisfy energy needs now and in the future. This is particularly relevant when only small amounts of energy are necessary, such as in tiny homes or rural areas. For this study, we conducted a feasibility analysis by surveying local authorities and households in Moundou, Chad. The aim was to identify the barriers preventing households from accessing energy. The key decision-making data in this paper are based on the sample proportion of respondents and the margin of error associated …

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Biobased Emulsion Breakers: Investigating Red Onion Skin And Orange Mesocarp Extracts For Oilfield Application, Victor-Oji Cynthia Onyekachi, Emechebe, Stanley Chijioke, Ikwani Chizurumoke God’Sdelight, Opusunju Allwell, Akaranta Onyewuchi Jan 2025

Biobased Emulsion Breakers: Investigating Red Onion Skin And Orange Mesocarp Extracts For Oilfield Application, Victor-Oji Cynthia Onyekachi, Emechebe, Stanley Chijioke, Ikwani Chizurumoke God’Sdelight, Opusunju Allwell, Akaranta Onyewuchi

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Oilfield emulsions pose significant operational challenges, affecting crude oil recovery efficiency and refining processes. Conventional chemical demulsifiers, often derived from petroleum-based compounds, pose environmental and economic concerns due to their toxicity and high production costs. This study investigates the potential of plant-based alternatives—Red Onion Skin Extract (ROSE) and Orange Mesocarp Extract (OME) - as environmentally friendly, cost-effective demulsifiers. This novel approach leverages the bioactive compounds in these extracts to destabilize oil-water emulsions efficiently. Four demulsifier formulations were developed: ROSE, OME, ROSE-NaBenzoate (ROSE-NaB), and OME-NaBenzoate (OME-NaB). Fourier Transform Infrared (FTIR) spectroscopy confirmed the presence of active functional groups responsible for interfacial …

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Insights Into The Optoelectronic And Thermoelectric Properties Of Lead-Free Rb2nairf6 Double Perovskite Compound: A First-Principles Study, Mwende Mbilo, Robinson Musembi, John Peter Kachira, Wisley Nyangau Onsate, Fanuel Mugwanga Keheze, Refilwe Edwin Mapasha Jan 2025

Insights Into The Optoelectronic And Thermoelectric Properties Of Lead-Free Rb2nairf6 Double Perovskite Compound: A First-Principles Study, Mwende Mbilo, Robinson Musembi, John Peter Kachira, Wisley Nyangau Onsate, Fanuel Mugwanga Keheze, Refilwe Edwin Mapasha

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This study investigated the structural, electronic, elastic, mechanical, thermodynamic, optical, and thermoelectric properties of the Rb2NaIrF6 lead-free double perovskite compound using first-principles methods. The structural stability of the perovskite was confirmed by the Goldschmidt tolerance and octahedral factors. Dynamic stability was confirmed through the negative energy of formation and positive frequency modes of the phonon dispersion curve. The dynamic stability results suggest that the studied compound could be potentially synthesised experimentally. The Rb2NaIrF6 compound is a direct semiconductor with electronic band gaps within the range of 2.14–3.76 eV, computed using different approximations. The mechanical stability was confirmed by the elastic …

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Ab-Initio Investigation Of The Structural, Electronic, Mechanical, Thermophysical, And Optical Properties Of The Zintl-Phase K₂Agsb Ternary Compound For Optoelectronic Applications, John Peter Kachira, Robinson Juma Musembi, Francis Nyongesa, Mwende Mbilo, Martin Nyamunga, Ibrahim Musanyi Jan 2025

Ab-Initio Investigation Of The Structural, Electronic, Mechanical, Thermophysical, And Optical Properties Of The Zintl-Phase K₂Agsb Ternary Compound For Optoelectronic Applications, John Peter Kachira, Robinson Juma Musembi, Francis Nyongesa, Mwende Mbilo, Martin Nyamunga, Ibrahim Musanyi

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A Zintl-phase K₂AgSb ternary compound has been investigated using density functional theory (DFT) on its structural, electronic, mechanical, thermophysical, and optical properties. Various exchange-correlation functionals have been employed, including the local density approximation (LDA) and generalised gradient approximation (GGA). Regularised strongly constrained and appropriately normed (RSCAN) and Tran-Blaha modified Becke-Johnson (TB-mBJ) functionals were utilised to enhance the accuracy of electronic structure predictions. The computed band gap values were 1.1601 eV and 1.2559 eV using LDA and GGA approximations, respectively. In contrast, more refined estimates of 1.5274 eV and 1.8917 eV were obtained using the RSCAN and TB-mBJ functionals. Machine …

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First-Principles Study Of The Structural, Electronic, Mechanical, And Optical Properties Of Zintl-Phase K2agbi Ternary Compound For Optoelectronic Applications Open Access, John Peter Kachira, Robinson Musembi, Francis Nyongesa, Mwende Mbilo, Martin Nyamunga, Ibrahim Musanyi Jan 2025

First-Principles Study Of The Structural, Electronic, Mechanical, And Optical Properties Of Zintl-Phase K2agbi Ternary Compound For Optoelectronic Applications Open Access, John Peter Kachira, Robinson Musembi, Francis Nyongesa, Mwende Mbilo, Martin Nyamunga, Ibrahim Musanyi

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A comprehensive first-principles study was conducted to explore the structural, electronic, mechanical, thermophysical, and optical properties of a Zintl-phase K2AgBi ternary semiconductor compound using density functional theory. The calculations employed the local density approximation (LDA), generalized gradient approximation (GGA), and meta-GGA methods. The computed negative formation energies proved the thermodynamic stability of the K2AgBi ternary compound. The computed bandgap values were 0.6732 and 0.7848 eV for the LDA and GGA, respectively. More refined bandgap estimates were obtained using meta-GGA methods, with the Tran–Blaha modified Becke–Johnson potential yielding 0.9346 eV and the revised strongly constrained and appropriately …

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Geagrow: A Mobile Tool For Soil Nutrient Prediction And Fertilizer Optimization Using Artificial Neural Networks, Olusegun Folorunso, Oluwafolake Ojo, Mutiu Busari, Muftau Adebayo, Joshua Adejumobi, Daniel Folorunso, Femi Ayo, Orobosade Alabi, Olusola Olabanjo Jan 2025

Geagrow: A Mobile Tool For Soil Nutrient Prediction And Fertilizer Optimization Using Artificial Neural Networks, Olusegun Folorunso, Oluwafolake Ojo, Mutiu Busari, Muftau Adebayo, Joshua Adejumobi, Daniel Folorunso, Femi Ayo, Orobosade Alabi, Olusola Olabanjo

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Introduction: Most farmers in Nigeria lack knowledge of their farmland’s nutrient content, often relying on intuition for crop cultivation. Even when aware, they struggle to interpret soil information, leading to improper fertilizer application, which can degrade soil and ground water quality. Traditional soil nutrient analysis requires field sample collection and laboratory analysis; a tedious and timeconsuming process. Digital Soil Mapping (DSM) leverages Machine Learning (ML) to create detailed soil maps, helping mitigate nutrient depletion. Despite its growing use, existing DSM-based ML methods face challenges in prediction accuracy and data representation. Aim: This study presents GeaGrow, an innovative mobile app that …

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Cleancity Iot: A Vehicle-Mounted Platform For Real-Time Urban Air-Quality Monitoring And Forecasting In Resource-Constrained African Cities, Eric Nizeyimana, Damien Hanyurwimfura, Gabriel Uwanyirigira, Bonaventure Karikumutima, Jimmy Nsenga, Irene Niyonambaza Mihigo Jan 2025

Cleancity Iot: A Vehicle-Mounted Platform For Real-Time Urban Air-Quality Monitoring And Forecasting In Resource-Constrained African Cities, Eric Nizeyimana, Damien Hanyurwimfura, Gabriel Uwanyirigira, Bonaventure Karikumutima, Jimmy Nsenga, Irene Niyonambaza Mihigo

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Urban air pollution is a growing public-health challenge in African cities, yet traditional monitoring stations are sparse and expensive. The paper presents CleanCity IoT, a deployed, low-cost, vehicle-mounted air-quality platform that combines IoT sensors, GSM connectivity, cloud aggregation, and machine learning to produce near-real-time exposure maps and 2-hour forecasts for multiple pollutants. Each device integrates low-cost sensors for PM2.5, PM10, NO₂, O₃, SO₂, and CO₂, alongside temperature and humidity. Measurements are geotagged and transmitted over mobile networks form vehicles to a cloud backend, where data are validated, stored, and visualized through a user-friendly dashboard that also issues automated alerts and …

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Therapeutic Potential Of Brassica Carinata Microgreens Extract In Alleviating Symptoms Of Type 2 Diabetes In Wistar Rats, Lilian Nakakaawa, Ifeoluwa D. Gbala, Joel L. Bargul, Xavier Cheseto, John M. Wesonga Jan 2025

Therapeutic Potential Of Brassica Carinata Microgreens Extract In Alleviating Symptoms Of Type 2 Diabetes In Wistar Rats, Lilian Nakakaawa, Ifeoluwa D. Gbala, Joel L. Bargul, Xavier Cheseto, John M. Wesonga

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Microgreens of Brassica plants have attracted increasing research interest in the management of the prevailing epidemic of Type 2 diabetes mellitus (T2DM) because of their high nutritional value. This study evaluated the antidiabetic effects of Brassica carinata Microgreens Ethanolic Extract (BMEE) in type-2 diabetic rats. For the normoglycemic assay, rats were divided into five groups and received a single oral dose of 100, 250, and 500 mg/kg of BMEE while the control groups received distilled water and Glibenclamide. Fasting blood glucose (FBG) levels were determined on a weekly basis for 28 days in diabetic rats after treatment with BMEE at …

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