Opportunities For Transformation Research Articles

Artificial Intelligence and Human Well-Being: A Review of Applications and Effects on Life Satisfaction through Synthetic Happiness

This paper examines the role of Artificial Intelligence in enhancing human well-being across domains such as healthcare, mental health, and education. A key contribution is the introduction of synthetic happiness—a form of well-being facilitated or enhanced by AI rather than naturally occurring processes. By reviewing current advancements, the study highlights AI’s positive impact on life satisfaction while addressing ethical concerns and potential drawbacks. The paper explores AI’s role in personalised healthcare, mental health support, and adaptive education, demonstrating how it fosters environments conducive to happiness. It further analyses synthetic happiness as a novel perspective on AI-driven well-being, discussing its benefits and risks, including reduced human interaction and over-reliance on artificial systems. While AI presents transformative opportunities to enhance happiness, it must complement rather than replace genuine human experiences. This paper provides a foundation for understanding AI’s role in well-being and offers insights for future research and applications.

Innovative practice of archival data development workflow in the AGI era: a case study of scientist archives project

Introduction. The advent of large language models (LLMs) presents a transformative opportunity for the field of archival science, offering advanced capabilities in intelligent information processing, semantic search, and more. These innovations address critical challenges posed by the exponential growth in archival materials and the increasing demand for efficient data analysis. Traditional archival workflows, often rely on manual description and optical character recognition (OCR), struggle with the complexities of unstructured digital data, especially in the context of digitized historical archives and manuscripts. Method. This paper explores a novel archival workflow through the case study of the scientist archives project, integrating human-machine collaboration and leveraging technologies such as open-sourced archival databases, IIIF-supported OCR environments, and advanced LLMs, including classic retrieval-augmented generation (Classic RAG) and graph-based retrieval-augmented generation (GraphRAG). Analysis. A Scientist Archives project is analysed, which utilises AGI era technologies to mine and manage the archives. Results. By embracing these technologies, the proposed approach seeks to revolutionize archival management, enhancing both efficiency and the depth of content revelation in the AGI era. Conclusions. This study contributes to the ongoing discourse on the intelligent transformation of archival practices, providing a roadmap for future archival data mining and management.

Implementation of Industry 4.0 RFID Technology for Sustainable Packaging Solutions

The adoption of Industry 4.0 RFID (Radio Frequency Identification) technology in packaging has revolutionized supply chain operations by enabling real-time marking, tracking, and tracing of materials. This paper explores the role of RFID technology in enhancing packaging sustainability through the reusability of pallets, boxes, bins, and containers, significantly reducing environmental impact and carbon emissions. By providing unique digital identities to packaging materials, RFID technology ensures seamless monitoring, improves inventory management, prevents counterfeiting, and enhances security measures. This paper discusses the different types of RFID tags—passive, active, semi-passive, and Near Field Communication (NFC) tags—and their specific applications in packaging [1]. It also examines the role of RFID readers in supply chain visibility, enabling automated data collection and reducing operational inefficiencies. The benefits of RFID technology, including enhanced supply chain collaboration, improved customer service, and cost savings, are analyzed alongside challenges such as implementation costs, system integration, and data privacy concerns. Despite these challenges, RFID technology presents a transformative opportunity for industries to optimize packaging processes, promote sustainability, and achieve operational excellence. By leveraging RFID-driven automation, businesses can enhance efficiency, reduce waste, and drive long-term value in supply chain management [5].

A narrative review of advancing medical education through technology: the role of smart glasses in situated learning

BackgroundThe integration of smart glasses technology in medical education has emerged as a promising approach to enhance medical education specially in clinical setting. Grounded in situational learning theory, smart glasses provide immersive experiences that allow students to engage with real-world clinical scenarios. The purpose of this study is to investigate the application and impact of smart glasses technology in medical education.MethodIn this study, two databases, PubMed and ScienceDirect, were used from 2016 to 2024 with related keywords and specific terms. In the process of searching and collecting studies, we utilized the Statement of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The studies reviewed included full-text quantitative, qualitative, and review articles that addressed the impact of smart glasses. In the initial review, 123 articles were found, and after applying the inclusion and exclusion criteria, 13 articles were evaluated by the reviewers. Finally, 28 articles were selected for review.ResultThe outcome of this review indicated that smart glasses significantly enhance procedural training by allowing students to observe live surgeries and interact with instructors in real-time. Additionally, the technology facilitated remote collaboration, enabling students to participate in training sessions regardless of geographical constraints.ConclusionThe integration of smart glasses into medical education presents a transformative opportunity to enhance traditional training methods and improve situated learning for students. By providing immersive and interactive learning experiences, smart glasses can enhance skill acquisition and foster a more engaging educational environment for future healthcare professionals.

Solanum pan-genetics reveals paralogues as contingencies in crop engineering.

Pan-genomics and genome-editing technologies are revolutionizing breeding of global crops1,2. A transformative opportunity lies in exchanging genotype-to-phenotype knowledge between major crops (that is, those cultivated globally) and indigenous crops(that is, those locally cultivated within a circumscribed area)3-5 to enhance our food system. However, species-specific genetic variants and their interactions with desirable natural or engineered mutations pose barriers to achieving predictable phenotypic effects, even between related crops6,7. Here, by establishing a pan-genome of the crop-rich genus Solanum8 and integrating functional genomics and pan-genetics, we show that gene duplication and subsequent paralogue diversification are major obstacles to genotype-to-phenotype predictability. Despite broad conservation of gene macrosynteny among chromosome-scale references for 22 species, including 13 indigenous crops, thousands of gene duplications, particularly within key domestication gene families, exhibited dynamic trajectories in sequence, expression and function. By augmenting our pan-genome with African eggplant cultivars9 and applying quantitative genetics and genome editing, we dissected an intricate history of paralogue evolution affecting fruit size. The loss of a redundant paralogue of the classical fruit size regulator CLAVATA3 (CLV3)10,11 was compensated by a lineage-specific tandem duplication. Subsequent pseudogenization of the derived copy, followed by a large cultivar-specific deletion, created a single fused CLV3 allele that modulates fruit organ number alongside an enzymatic gene controlling the same trait. Our findings demonstrate that paralogue diversifications over short timescales are underexplored contingencies in trait evolvability. Exposing and navigating these contingencies is crucial for translating genotype-to-phenotype relationships across species.

Integrating artificial intelligence into multidisciplinary evaluations of HCC: opportunities and challenges

Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer and a leading cause of cancer-related mortality globally. The heterogeneity of HCC complicates prognostic, management, and predictive strategies across different patient populations. Recent advancements in artificial intelligence (AI) and machine learning (ML) offer transformative opportunities to improve HCC management. This review consolidates findings from various studies regarding integrating AI in detecting, diagnosing, and treating HCC, leveraging diverse data sources such as radiological imaging, genomics, and clinical records. AI-based approaches have shown potential to improve the accuracy and efficiency of HCC screening, early detection, tumor characterization, and treatment response evaluation, surpassing traditional methods. However, the deployment of AI technologies is hindered by challenges, including data standardization, validation across multiple centers, and ethical considerations regarding AI applications. This review emphasizes the need to establish comprehensive multimodal datasets and collaborative research efforts to validate AI applications in HCC management. By addressing these challenges, the integration of AI technology has the potential to revolutionize HCC care, ultimately leading to improved patient outcomes and a more personalized approach to treatment strategies.

Large language models and GenAI in education: Insights from Nigerian in-service teachers through a hybrid ANN-PLS-SEM approach

Background The rapid integration of Artificial Intelligence (AI) in education offers transformative opportunities to enhance teaching and learning. Among these innovations, Large Language Models (LLMs) like ChatGPT hold immense potential for instructional design, personalized learning, and administrative efficiency. However, integrating these tools into resource-constrained settings such as Nigeria presents significant challenges, including inadequate infrastructure, digital inequities, and teacher readiness. Despite the growing research on AI adoption, limited studies focus on developing regions, leaving a critical gap in understanding how educators perceive and adopt these technologies. Methods We adopted a hybrid approach, combining Partial Least Squares Structural Equation Modelling (PLS-SEM) and Artificial Neural Networks (ANN) to uncover both linear and nonlinear dynamics influencing behavioral intention (BI) of 260 Nigerian in-service teachers regarding ChatGPT after participating in structured training. Key predictors examined include Perceived Ease of Use (PEU), Perceived Usefulness (PUC), Attitude Towards ChatGPT (ATC), Your Colleagues and Your Use of ChatGPT (YCC), Technology Anxiety (TA), Teachers’ Trust in ChatGPT (TTC), and Privacy Issues (PIU). Results Our PLS-SEM results highlight PUC, TA, YCC, and PEU, in that order of importance, as significant predictors, explaining 15.8% of the variance in BI. Complementing these, ANN analysis identified PEU, ATC, and PUC as the most critical factors, demonstrating substantial predictive accuracy with an RMSE of 0.87. This suggests that while PUC drives adoption, PEU and positive attitudes are foundational in fostering teacher engagement with AI technologies. Conclusion Our results highlight the need for targeted professional development initiatives to enhance teachers’ digital competencies, reduce technology-related anxiety, and build trust in AI tools like ChatGPT. Our study offers actionable insights for policymakers and educational stakeholders, emphasizing the importance of fostering an inclusive and ethical AI ecosystem. We aim to empower teachers and support AI-driven educational transformation in resource-limited environments by addressing contextual barriers.

The Anxious Generation Theory and Generation Z Behaviour in the Workplace: A Correlation Analysis

This paper explores the intersection between Jonathan Haidt's Anxious Generation Theory and Generation Z’s behaviours in the workplace, offering a comprehensive analysis of how overprotective parenting, social media influence, and safetyism shape the professional identity and expectations of this generation. Using a mixed-methods approach, the research examines workplace behaviours, organisational dynamics, and adaptation strategies. Findings reveal that Generation Z prioritises mental health, inclusivity, and purpose-driven work environments, often accompanied by risk aversion and a preference for frequent feedback. These traits influence leadership styles, team collaboration, and policy development. While presenting challenges, such as heightened turnover rates and dependence on validation, Generation Z also offers opportunities for innovation and cultural transformation. This study concludes with actionable strategies for organisations to align with Generation Z’s values while maintaining productivity and adaptability, contributing to a deeper understanding of integrating this emerging workforce into global organisational contexts.

3D Nano‐architected Polymer Shell Enables Reconfigurable Stabilized Blue Phase Soft Crystals

AbstractBlue phases (BPs), formed through the self‐assembly of chiral liquid crystal molecules into 3D nanolattices with cubic symmetries, exhibit dynamic photonic bandgaps in the visible spectrum, offering transformative opportunities for advanced optical circuits, sensing and communication technologies. However, their thermal stability is restricted to a narrow temperature range (0.5–1.0 K), limiting practical applications. Polymer stabilization of bulk BPs has extended thermal stability but often compromises the dynamic behavior essential for fast‐response functionalities. Here, experimental and computational approaches are integrated to investigate the effect of curvature and interfacial interactions on BP polymer stabilization. It is demonstrated that photo‐polymerization of reactive monomers within BP microdroplets produces polymer shells, a few hundred nanometers thick, featuring BPs disclination network nano‐architecture. This nano‐architected shell provides surface topology and anchoring conditions to direct BP nucleation and growth, with the degree of curvature dictating the stabilized BP lattice structure within microdroplets. Remarkably, while enhancing thermal stability across a broad temperature range, this polymer shell enables reconfigurable crystal‐to‐crystal transformations in stabilized BP droplets. This work introduces a novel approach to tailoring BP properties by leveraging curvature, confinement, and interfacial interactions to create thermally stable, reconfigurable photonic crystals, paving the way for adaptive sensors and next‐generation fast‐response optical devices.

Re-imagining human cell culture media: Challenges, innovations, and future directions.

Re-imagining human cell culture media: Challenges, innovations, and future directions.

Will AI reshape or deform pharmacy education?

Will AI reshape or deform pharmacy education?

Breakthrough Opportunities of Nanotheranostics in Psoriasis: From Pathogenesis to Management Strategy.

In this paper, we have discussed recent advances in our understanding of the aetiology of psoriasis, particularly as they relate to aryl hydrocarbon receptors in DCs, Langerhans cells, macrophages, signal transducer and activator of transcription 3 pathways, and dermal vascular endothelial cells. Here, we have shown that the ability to target specific cellular and molecular components of psoriasis pathogenesis with nanoscale precision using phosphodiesterase 4 inhibitors represents a transformative opportunity to address the complex nature of this dermatological condition. In this review, we have examined the molecular mechanisms behind the pathogenic features of psoriasis and new treatments being tested in clinical settings. There is research being done on new treatments created in the last ten years. This field highlights the advantages of nanotechnological technologies as cutting-edge candidates for drug delivery systems in psoriasis and other inflammatory chronic skin disorders. Future Developments: Nanotechnology-based treatments currently under study show good efficacy and low side effect profiles. However, long-term prospective trials are required to demonstrate long-term safety and effectiveness. Phosphodiesterase inhibitors, Janus kinase inhibitors, nonsteroidal anti-inflammatory drugs, combinations of vitamin D3 derivatives and corticosteroids, and coal tar formulations are some of the newer topical treatments for psoriasis. The psoriasis treatment continues to involve conventional medications (i.e., medicines that are generally acknowledged as either normal therapy or outdated remedies), whether used topically or orally. Nonetheless, we are starting to see initiatives to create pharmaceuticals and biosimilars with better therapeutic results, fewer side effects, and greater efficacy.

A Study On 3d Printed Food and Its Potential for Personalized Nutrition

The emergence of 3D food printing presents a transformative opportunity for personalized nutrition, allowing precise customization of meals based on individual dietary needs. This study explores the feasibility, benefits, and challenges of 3D printed food in creating personalized nutrition solutions. An experimental approach was employed, where nutrient-rich ingredients were formulated and printed using a 3D food printer. Nutritional and structural analyses confirmed that printed foods maintained their integrity while meeting targeted macronutrient and micronutrient compositions. Survey responses from nutritionists and food scientists indicated strong support for 3D food printing as a tool for dietary personalization, though concerns about consumer acceptance, affordability, and taste persist. Expert interviews highlighted the need for further advancements in ingredient formulation, printing efficiency, and public awareness to enhance adoption. The study also identified key challenges, including ingredient compatibility, printing speed, and large-scale production feasibility. The findings suggest that while 3D food printing holds significant promise for personalized nutrition, further research is required to optimize printing technology, expand ingredient diversity, and assess long-term health impacts. With continued technological advancements and industry collaboration, 3D food printing could revolutionize dietary personalization, improve health outcomes, and contribute to a more sustainable and efficient food system.

The Lobito Corridor as an Anchor of Economic and Value Chain Development in Angola, Democratic Republic of Congo, and Zambia: Exploring the Issues

ABSTRACTThe development of the Lobito Corridor offers immense opportunities for trade, economic transformation, development and regional integration in Southern Africa. This paper discusses the role of the Lobito Corridor in supporting development in the three member states. Using a random effects panel model estimated using the structural gravity model, the paper evaluated the corridor's infrastructure, value chain, and regional integration capacity as the main explanatory variables using six main variables namely corridor remoteness, regional trade agreements, corridor imports, special economic zone, corridor geographical distance and corridor infrastructure. The results showed that the corridor's infrastructural capacity, capacity to anchor critical value chains and regional integration all had a positive impact on the volume of exports moved through the corridor. The paper concluded that the development of the corridor can be leveraged to reorient Southern Africa's transport infrastructure to drive economic development and transformation through agriculture and mining value chains and facilitation of the strengthening of bilateral and multilateral relations along the corridor.

Ethical Consideration in Implementing AI-based Tutoring Systems as Educational Technology Tool in Education: Balancing Efficiency with Privacy and Equity in the Teaching of Students

This article explores the major technological advancements in education and the ethical issues they raise. In this research, we use the systematic literature mapping method. The study follows the research methodology outlined by Kabudi, Pappas, and Olsen, with guidance from Petersen, Vakkalanka, and Kuzniarz. The methodology applied in both studies is as follows: (i) search and selection, (ii) data extraction, (iii) classification and analysis, and (iv) evaluation of validity. The PRISMA approach, or Preferred Reporting Items for Systematic Reviews and Meta-Analyses, was used as a framework for the search and selection phase. Key findings reveal that AI can automate grading and provide personalized feedback to students, while also reducing cheating. It also helps in predictive analytics by predicting learning outcomes and identifying at-risk students. AI also evaluates non-cognitive traits like emotional states and collaborative skills. However, the study also highlights ethical issues in AI-based assessments, such as inclusivity, fairness, accountability, accuracy, explanation, auditability, security, privacy, autonomy, consent, and sustainability. The research identifies five key thematic areas: AI system design, AI-driven assessment rollout, data stewardship, assessment administration, and grading and evaluation. The study concludes that while AI presents transformative opportunities for educational assessments, it also introduces complex ethical challenges that must be carefully managed.

Water Sector 5.0: Harnessing Digital Transformation Opportunities and Mitigating Risks

Water Sector 5.0: Harnessing Digital Transformation Opportunities and Mitigating Risks

IBC Oxford University Oral Abstract 49 - AI-assisted surgical fellowship training assessment through laparoscopic sleeve gastrectomy video analytics

Abstract Background The advent of artificial intelligence (AI) in surgical training presents a transformative opportunity to enhance the assessment and education of surgical fellows. This study investigates the application of AI in evaluating the performance of surgeons by analyzing videos of laparoscopic sleeve gastrectomy procedures uploaded to a specialized platform, Surgeryview.ai. Methods Three surgeons contributed to this study: two were professor bariatric surgeons and one was a fellow bariatric surgeon in training. A total of 466 videos of gastric sleeve surgeries were analyzed. Of these, 413 videos were performed by the professor surgeons (Surgeon 1: 180, Surgeon 2: 233) between September 2022 and May 2024, and 53 surgeries were performed by the fellow surgeon in training over a period of 10 months (August 2023–May 2024). The analyzed videos were chosen randomly, and any surgeries Involving an additional procedure to the gastric sleeve (for example hiatal hernia repair) were excluded. Patient data, including gender, age, and initial BMI, were recorded, ensuring anonymity. Results The AI platform provided comprehensive longitudinal analytics, detailing the time taken to complete each surgical step: access to the abdominal cavity, greater curvature dissection, stapling, specimen removal, oversewing, and leak test. The platform also analyzed the impact of patient demographics on surgery time. Professors showed consistent efficiency, while fellows demonstrated significant improvement over time. Notably, surgery duration was influenced by patient-specific factors such as BMI and age. The fellow bariatric surgeon in training showed significant improvement across all metrics over the trimesters, with overall surgery time reduced by approximately 23.83%, greater curvature dissection (step 2) time by 28.37%, and oversuture of the staple line (step 5) time by 28.74%. When broken down by BMI, age, and gender, indicate that improvements are generally consistent across these variables, with the most significant improvements seen in lower BMI and younger age groups. These advancements indicate that the fellow has substantially closed the performance gap, particularly in the critical surgical steps. Conclusion AI assisted platforms like Surgeryview.ai offer valuable insights into surgical performance, enabling objective assessment and personalized feedback for fellows. This technology can enhance surgical training programs by identifying specific areas for improvement and tracking progress over time, ultimately aiming to standardize surgical education and improve patient outcomes.

THE POTENTIAL AND ETHICAL ISSUES OF ARTIFICIAL INTELLIGENCE IN IMPROVING ACADEMIC WRITING

Artificial intelligence (AI) has brought about transformative opportunities and has attracted the attention of many international organisations to the intent that UNESCO has held two international conferences on it. including (i) International Conference on Artificial Intelligence and Education in 2019 in Beijing, focusing on leveraging AI to advance education and sustainable development. This conference resulted in the Beijing Consensus on Artificial Intelligence and Education, outlining strategies for AI integration in educational policies and systems (ii) Forum on AI and Education 2022, emphasising the use of AI to empower teachers and transform teaching practices globally. Meanwhile, there was a regional forum led by UNESCO which examined AI in the context of ethics and societal impact, contributing to frameworks like the Recommendation on the Ethics of Artificial Intelligence in 2021. This paper focused on ethical challenges in academic writing and examines the growing significance of AI-powered tools for improving academic writing with an emphasis on how these innovations expedite research procedures raise writing standards and increase output. Artificial intelligence (AI) tools that save time and effort during drafting and editing include content generators citation managers and grammar checkers. These tools are very helpful for researchers and writers. The preservation of human creativity authorship plagiarism and intellectual integrity are some of the issues brought up by this growing reliance on AI. A number of ethical issues are looked at including who owns content created by AI the possibility of losing one’s ability to think critically and the possibility of idea misattribution. Though AI has the potential to completely transform academic writing the paper contends that in order to ensure that these technologies are used responsibly and enhance rather than replace human intellect and creativity a careful balance must be struck. There are suggestions given for preserving academic integrity and encouraging moral application of AI in research projects.

The Intersection of Health and Planet: Why Food Choices Matter.

Objective: To explore the interconnected crises of chronic disease, environmental degradation, and social inequity through the lens of food systems and to highlight the potential of plant-based dietary patterns to mitigate these challenges. Main Outcomes and Measures: Evidence demonstrates that plant-based diets reduce the prevalence of chronic diseases, including heart disease and type 2 diabetes, alleviate environmental harm by reducing greenhouse gas emissions and water usage, and promote health equity by increasing access to affordable, nutritious foods. Quantitative outcomes include projected savings of trillions of dollars in health care and climate-related costs and the prevention of millions of premature deaths globally. Results: Transitioning to plant-forward food systems has been associated with a reduction in chronic disease risk by up to 90%, a significant decrease in health care expenditures, and a 75% reduction in agricultural land use. Key interventions, such as produce prescriptions and plant-based meal programs, demonstrate the effectiveness of systemic solutions in improving health outcomes while addressing structural inequities. Conclusion: Aligning individual and collective efforts toward sustainable, health-focused food systems presents a transformative opportunity to improve global health, conserve natural resources, and foster social equity. By adopting plant-based diets and supporting equitable food policies, individuals, health care professionals, and policymakers can collaboratively create a more resilient, sustainable, and just future for generations to come.

The Role of Artificial Intelligence in Developing the Tall Buildings of Tomorrow

The application of artificial intelligence (AI) in tall buildings’ development provides transformative opportunities for facing population growth pressures and sustainability challenges in cities. This study presents a comprehensive review of both the current literature and the theoretical framework of AI and its role in construction, specifically analyzing the convergence of AI and skyscraper development. The research methodology combines scholarly sources, AI image generation techniques, an analytical approach, and a comparative analysis of traditional versus AI-enhanced approaches. This study identifies key domains where AI significantly impacts skyscraper evolution, including design optimization, energy management, construction processes, and operational efficiencies. It highlights short-term benefits like enhanced architectural design through rapid generative design iterations and material optimization, alongside long-term implications involving adaptive building technologies and sustainability enhancements. Additionally, it addresses the advantages and challenges of adopting AI in architecture, considering various factors (e.g., sustainability, security, and occupant well-being), as well as the impact of different climates on AI in architecture and construction. It also explores transformative applications across diverse skyscraper functions and how AI can bridge different cultures and technologies. The findings reveal AI’s substantial potential in TBs’ design and management, (i.e., structural optimization, energy saving, safety protocols, and operational efficiency) by leveraging innovative technologies such as machine learning, computer vision, and predictive modeling. In conclusion, AI’s dual role as both a revolutionary tool that enhances traditional architectural methods and a catalyst for new design paradigms prioritizing sustainability and resilience has been reflected. Ultimately, this research underscores the importance of balancing AI innovation with established architectural principles to foster a favorable urban future that embraces both technological advancement and foundational design values. This study serves as a base for future research in the AI field.