Fake news research trends, linkages to generative artificial intelligence and sustainable development goals

Analyzing the contributions of biofuels, biomass, and bioenergy to sustainable development goals

Biofuels, biomass, and bioenergy are pivotal in transitioning to sustainable energy systems while addressing global energy demands and supporting the UN sustainable development goals (SDGs). This study synthesizes research on biofuels, from first-to fourth-generation technologies, highlighting their potential to reduce greenhouse gas emissions, enhance energy security, and foster economic growth. Using the PRISMA framework, machine learning-based SDG mapping and BERTopic modeling, the analysis identifies two thematic clusters: one focused on sustainable energy and climate resilience (SDGs 7, 12, and 13) and the other on socioeconomic development and equity (SDGs 1, 8, and 15). Topics such as bioeconomic development and supply chain optimization emphasize systemic innovation and process efficiency. The study underscores the role of policy, international collaboration, and emerging technologies like AI in advancing biofuel systems. Investments in infrastructure and capacity building are vital to aligning bioenergy development with global sustainability goals.

Advancing cybersecurity and privacy with artificial intelligence: current trends and future research directions

Introduction

The rapid escalation of cyber threats necessitates innovative strategies to enhance cybersecurity and privacy measures. Artificial Intelligence (AI) has emerged as a promising tool poised to enhance the effectiveness of cybersecurity strategies by offering advanced capabilities for intrusion detection, malware classification, and privacy preservation. However, this work addresses the significant lack of a comprehensive synthesis of AI's use in cybersecurity and privacy across the vast literature, aiming to identify existing gaps and guide further progress.

Methods

This study employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework for a comprehensive literature review, analyzing over 9,350 publications from 2004 to 2023. Utilizing BERTopic modeling, 14 key themes in AI-driven cybersecurity were identified. Topics were clustered and validated through a combination of algorithmic and expert-driven evaluations, focusing on semantic relationships and coherence scores.

Results

AI applications in cybersecurity are concentrated around intrusion detection, malware classification, federated learning in privacy, IoT security, UAV systems and DDoS mitigation. Emerging fields such as adversarial machine learning, blockchain and deep learning are gaining traction. Analysis reveals that AI's adaptability and scalability are critical for addressing evolving threats. Global trends indicate significant contributions from the US, India, UK, and China, highlighting geographical diversity in research priorities.

Discussion

While AI enhances cybersecurity efficacy, challenges such as computational resource demands, adversarial vulnerabilities, and ethical concerns persist. More research in trustworthy AI, standardizing AI-driven methods, legislations for robust privacy protection amongst others is emphasized. The study also highlights key current and future areas of focus, including quantum machine learning, explainable AI, integrating humanized AI and deepfakes.

Possible Health Benefits and Risks of DeepFake Videos: A Qualitative Study in Nursing Students

BACKGROUND

"DeepFakes" are synthetic performances created by AI, using neural networks to exchange faces in images and modify voices.

OBJECTIVE

Due to the novelty and limited literature on its risks/benefits, this paper aims to determine how young nursing students perceive DeepFake technology, its ethical implications, and its potential benefits in nursing.

METHODS

This qualitative study used thematic content analysis (the Braun and Clarke method) with videos recorded by 50 third-year nursing students, who answered three questions about DeepFake technology. The data were analyzed using ATLAS.ti (version 22), and the project was approved by the Ethics Committee (code UCV/2021-2022/116).

RESULTS

Data analysis identified 21 descriptive codes, classified into four main themes: advantages, disadvantages, health applications, and ethical dilemmas. Benefits noted by students include use in diagnosis, patient accompaniment, training, and learning. Perceived risks include cyberbullying, loss of identity, and negative psychological impacts from unreal memories.

CONCLUSIONS

Nursing students see both pros and cons in DeepFake technology and are aware of the ethical dilemmas it poses. They also identified promising healthcare applications that could enhance nurses' leadership in digital health, stressing the importance of regulation and education to fully leverage its potential.

Mapping biomimicry research to sustainable development goals

This study systematically evaluates biomimicry research within the context of sustainable development goals (SDGs) to discern the interdisciplinary interplay between biomimicry and SDGs. The alignment of biomimicry with key SDGs showcases its interdisciplinary nature and potential to offer solutions across the health, sustainability, and energy sectors. This study identified two primary thematic clusters. The first thematic cluster focused on health, partnership, and life on land (SDGs 3, 17, and 15), highlighting biomimicry's role in healthcare innovations, sustainable collaboration, and land management. This cluster demonstrates the potential of biomimicry to contribute to medical technologies, emphasizing the need for cross-sectoral partnerships and ecosystem preservation. The second thematic cluster revolves around clean water, energy, infrastructure, and marine life (SDGs 6, 7, 9, and 14), showcasing nature-inspired solutions for sustainable development challenges, including energy generation and water purification. The prominence of SDG 7 within this cluster indicates that biomimicry significantly contributes to sustainable energy practices. The analysis of thematic clusters further revealed the broad applicability of biomimicry and its role in enhancing sustainable energy access and promoting ecosystem conservation. Emerging research topics, such as metaheuristics, nanogenerators, exosomes, and bioprinting, indicate a dynamic field poised for significant advancements. By mapping the connections between biomimicry and SDGs, this study provides a comprehensive overview of the field's trajectory, emphasizing its importance in advancing global sustainability efforts.

Cybersecurity in the generative artificial intelligence era

Generative Artificial Intelligence (GenAI) are algorithms capable of generating original content. The ability of GenAI to learn and generate novel outputs alike human cognition has taken the world by storm and ushered in a new era. In this review, we explore the role of GenAI in healthcare, including clinical, operational, and research applications, and delve into the cybersecurity risks of this technology. We discuss risks such as data privacy risks, data poisoning attacks, the propagation of bias, and hallucinations. In this review, we recommend risk mitigation strategies to enhance cybersecurity in GenAI technologies and further explore the use of GenAI as a tool in itself to enhance cybersecurity across the various AI algorithms. GenAI is emerging as a pivotal catalyst across various industries including the healthcare domain. Comprehending the intricacies of this technology and its potential risks will be imperative for us to fully capitalise on the benefits that GenAI can bring.

Top 100 highly cited sustainability researchers

The announcement of the UN Sustainable Development Goals (SDGs) provided a fresh direction to sustainability research that spans different disciplines. Consequently, scholarly databases made available the mapping of research publications to different SDGs, unleashing many opportunities for analysis. In this work, the top 100 Highly Cited Sustainability Researchers (HCSRs) and information related to them, such as the institutions they belong to, the type of these institutions, the geographical diversity of these researchers, and gender representation patterns, are analyzed. Also, from their publications, their publication pattern, including (i) the least and most researched SDGs, (ii) their Open Access publishing pattern, (iii) their collaboration pattern (iv) the pattern of their research impact, are analyzed. The most sought thematic areas of their research, top journals in which they publish, important research categories handled by these journals, etc., are also investigated. The most significant contribution of these researchers and their recent contributions are also discussed. The data indicates a significant disparity in research focus among the top 100 HCSRs, with most concentrating on "Good Health and Well Being," "Zero Hunger," and "Quality Education," while notably fewer researchers focus on "Decent Work and Economic Growth" and "No Poverty," underscoring the need for a more balanced research agenda across all SDGs. The study reveals that the United States, China, and the United Kingdom are the leading contributors to the top 100 HCSRs, suggesting that these countries are predominant in global sustainability research output, while nations like Iran and Saudi Arabia also make notable, albeit smaller, contributions. The institutional affiliations of HCSRs show a significant imbalance, with only 16 from private institutions compared to 84 from public ones. Specifically, it shows that out of the top 100 researchers, 93 are men, while only 7 are women. The analysis of authorship in publications by HCSRs reveals a tendency towards middle and last author positions, underscoring their collaborative and leadership roles within the research community. All these analyses can inform academia, industry, and policymakers about the most significant developments in research regarding SDGs.