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Blockchain and the Evolving Internal Audit Function
Blockchain Technology indicates a transformative era for internal audit practices in the evolving digital finance and operations landscape. This research explores the internal audit function in a Blockchain-driven world, emphasizing the changing perspectives and methodologies necessitated by this disruptive technology. With its foundational principles of transparency, immutability, and decentralization, Blockchain presents challenges and opportunities for internal auditors. The paper delves into how Blockchain is poised to redefine traditional audit practices, moving towards more real-time and continuous auditing techniques. It examines the implications of Blockchain for risk assessment, fraud detection, and compliance, highlighting the shift towards proactive rather than reactive audit strategies. Furthermore, the research examines Blockchains opportunities and challenges to the internal audit function. This study provides insights into integrating Blockchain Technology in internal auditing through a comprehensive secondary data analysis. It proposes a roadmap for auditors to adapt and thrive in this new era. The findings underscore the importance of embracing technological advancements, advocating for a dynamic approach to audit practices that aligns with the complexities of a blockchain-driven world. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Nanomaterials Synthesized from Mangroves and Their Associates
Nanotechnology has great potential for developing nano-enabled equipment and products in a variety of industries, including personal care, medical, food, and agriculture. Despite the increasing use of metal nanoparticles in various domains, concerns concerning biological and environmental safety during manufacture remain. Traditional commercial methods for generating nanoparticles often entail chemical procedures and high-energy physical approaches that are both environmentally damaging and expensive. As an alternative, green synthesis employing plants has arisen, which reduces the requirement for toxic chemicals and severe reaction conditions in nanoparticle synthesis. The utilization of mangrove plants for nanoparticle synthesis has recently gained popularity due to their abundance of unique phytochemicals that aid in nanoparticle synthesis. Microorganisms in mangroves and enzymatic activities in plants can be utilized for a range of biotechnological and environmental uses. Bioactive compounds from mangrove resources show potential for creating bionanomaterials that can be utilized in environmental and biomedical fields. Bionanomaterials created from mangroves are incredibly effective in medical uses and cleaning up the environment. Bionanomaterials are produced by utilizing mangrove and various biomolecules obtained from mangrove plants as substances for the creation of nanoparticles. Bionanomaterials made from biomolecules offer benefits for the sustainable use of mangroves because of their large surface area, biocompatibility, and minimal toxicity. Here focuses on the potential of mangroves as a natural resource for producing bionanomaterials in various applications, promoting an eco-friendly approach. This chapter investigates various types of mangrove species and their elements utilized in creating nanoparticles, as well as the applications of the nanoparticles in therapy, agriculture, and industry. It also investigates the obstacles hindering the extensive utilization of plant-based nanoparticle synthesis. Springer Nature Switzerland AG 2025. -
Bioactive Compounds and Biological Activities of Mangrove-Associated Bacteria
Mangroves are used by folklore in indigenous medicine for the treatment of diseases. They contain an array of pharmacologically significant bioactive compounds. The endophytes of the mangroves have the capability of producing biologically active compounds which may be similar to their host plant. They are also able to produce novel and unique bioactive compounds which can be used in therapeutics. Bacillus and Streptomyces are the major genera of bacterial endophytes found in the mangroves. The major groups of bioactive compounds produced by the bacterial endophytes of mangroves include terpenoids, alkaloids, polyketides, etc. The bioactive compounds produced by the endophytes possesses biological activities such as antibacterial, cytotoxic, antioxidant activity, etc. These compounds have profound applications in the discovery of drugs. The present chapter focuses on the bacterial endophytes found in the mangroves, the bioactive molecules produced by them, and the pharmacological activities associated with these endophytes. Springer Nature Switzerland AG 2025. -
Specialized Metabolites of Mangroves and Their Biological Activities
Mangroves are woody plants that are found in intertidal zones, where land meets the sea, especially in the tropical and subtropical regions of the world. They synthesize and accumulate diverse specialized metabolites that fall into major categories such as phenolics, terpenes, and alkaloids. Mangrove-derived chemical compounds have also been shown to exhibit a variety of biological properties including anticancer, antidiabetic, anti-inflammatory, antibacterial, antioxidant, and neuroprotective activities. In this chapter, we present the chemistry and biological activities of the mangrove-specialized metabolites. Springer Nature Switzerland AG 2025. -
Phytochemicals and Biological Activities of Ceriops tagal (Perr.). C. B. Rob.
Plants have been used for medicines since ancient times as they serve critical needs and are easily accessible. In recent years, various nations have seen a major increase in the use of plant-based treatments, resulting in a significant rise in the global demand for herbal products. This chapter describes Ceriops tagal, a mangrove species with excellent potential for bioactive components and biological activity. The majority of the distinctive secondary metabolites and their analogs reported in this plant are di-, tri-, and tetra-terpenoids (dolabrane, lupane, oleanane, dammarane, and pimarane), phenolics, and steroids from the hypocotyls, roots, and aerial parts. Various studies reported 97 terpenoids and 14 other metabolites. Many biological activities have already been identified from various extracts, including anticancer, antidiabetic, antioxidant, anti-inflammatory, antibacterial, and neurotrophic activities. In this chapter, we explored the biological potential of C. tagal, particularly its anticancer and neuroprotective activities, and it may be valuable for young researchers looking into the potential drug for chemotherapeutic and neurotrophic properties for the treatment and prevention of cancerous and neurological disorders. Springer Nature Switzerland AG 2025. -
Fruit Peel Waste: A Potential Substrate for Production of Value-Added Products
Fruit wastes are considered as a major class of food processing waste that has turned to be a global crisis due to issues associated with its disposal and treatment. It majorly consists of large fractions of solid or semi-solid waste generated during the separation of desired products from undesired ones in early stages of processing. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Microalgae as Biorefineries for Biofuel and Bioenergy Production: Recent Developments and Future Prospects
Microalgae boasts unique advantages regarding biofuel production, where researchers have made significant strides in increasing biofuel yields while reducing costs by improving lipid profiles in various microalgal strains, incorporating nano-additives, and improving extraction techniques. They have achieved this through genetic engineering, nanotechnology, and innovative cultivation techniques, optimizing the entire process. Moreover, microalgae are rich in bioactive compounds, and this chapter emphasizes advanced methods for extracting and purifying compounds like carotenoids, phycobiliproteins, polysaccharides, and omega-3 fatty acids, which have broad applications in food, medicine, and various industries. In energy production, microalgae generate renewable and eco-friendly energy through microbial fuel cells, employing techniques such as thermochemical liquefaction and producing energy from fermentation processes. Advancements in microalgae-based photobioreactors and strategies to improve photosynthetic efficiency further contribute to the efficiency and scalability of energy production. The book chapter highlights the importance and sustainability of microalgae in addressing energy and environmental challenges. By harnessing the latest advancements in biofuel production, valuable product synthesis, and renewable energy generation, microalgae have the potential to steer in a greener and brighter future. Their rapid growth, carbon dioxide absorption, and valuable compound synthesis make them a powerful tool in our pursuit of sustainable solutions. Embracing the potential of microalgae can lead us to an environmentally friendly and economically prosperous future. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Immobilization of TiO2 on Various Substrates
Recovery of photocatalytic materials after the degradation of organic pollutants remains a challenge. To address this issue, immobilizing the material on a suitable substrate presents a viable solution. Immobilization of the commonly used titanium dioxide (TiO2) photocatalyst onto various substrates is typically achieved through adsorption, hydrogen bonding, or chemical bonding. Coating TiO2 onto different substrates is a common approach to enhance its durability, reusability, and catalytic efficiency across multiple applications, such as photocatalysis, sensors, and heterogeneous catalysis. The choice of substrate depends on the specific application, desired properties, and its ability to improve the photocatalytic performance. Substrates such as glass/quartz, polymeric materials, metal oxides, carbon-based materials, textiles, and cellulose each offer unique characteristics that enhance the potential of the photocatalytic material. 2026 WILEY-VCH GmbH. -
Impactful Micro-moments for Deep Learning in Higher Education Classrooms: A Whole-person Education Perspective
The context within which higher education operates has undergone rapid changes in the past few decades. These changes, necessitated by a brittle, anxious, non-linear and incomprehensible (BANI) world, have made the inculcation of 21st-century skills and adoption of a competency-based curriculum increasingly relevant. This chapter addresses these shifts in higher education and their challenges for faculty members and students. The authors focus on in-class pedagogical practices which can be adopted in light of the changes in what is learnt and how it is learnt. The best teacherstudent learning sessions are those that create lasting learning outcomes. This chapter draws from positive psychology concepts and highlights the importance of creating intentional macro- and micro-moments in learning spaces. As educators, crafting deliberately planned moments can make learning more experiential, quick and long-lasting. Though micro-moments can be unstructured and unscripted, the authors focus on those micro-moments that are deliberate and carefully planned to help nurture creativity, mindfulness and organisational commitment. They can be used to echo and reinforce the larger vision of the programme or the institution. By leveraging micro-moments, educators can create opportunities for continuous learning, self-reflection and personal growth beyond the traditional classroom setting. This chapter examines the role of micro-moments in enhancing cognitive, emotional, social and ethical dimensions of student development through deep learning. 2026 by John Wiley & Sons, Ltd. All rights reserved. -
Recentring Personal Development in Counsellor Education: Integrating Self-compassion, Meaning and Self-care in Training
Personal development (PD) was once the cornerstone of counsellor preparation. However, competency-driven reforms of the late-20th century relegated introspective work to the curricular margins. This chapter argues for a systematic reintegration of PD within counsellor education, contending that self-compassion, meaning in life and holistic self-care are pedagogically indispensable for fostering counselling self-efficacy and sustaining the professional quality of life (ProQOL). After tracing the historical displacement of reflective practice, we differentiate PD from the broader notion of personal growth and technically oriented professional development. Synthesising evidence from counselling, health and educational psychology, we demonstrate that trainees who cultivate self-compassion, meaning-making in life and intentional holistic self-care show greater empathic resonance, lower burnout indicators and more ethical decision-making. The chapter offers concrete strategies such as reflective writing, development labs, mindfulness exercises and scaffolded peer-support structures, which educators can embed within diverse regulatory contexts. By restoring PD to the centre of counsellor training, programmes can prepare practitioners who work competently and congruently, safeguarding client welfare and well-being. 2026 by John Wiley & Sons, Ltd. All rights reserved. -
Experiential Learning: Benefits, Challenges and Pedagogical Insights for Students Performance at Workplace: Effective Teaching Methods for Students in Organisational Psychology
In an era of rapid technological disruption, today's world of work is driven by these advancements, resulting in business uncertainties and a demand for project-ready recruits. Organisations now require role-ready hires, rendering extended training periods obsolete. Eligibility exams post job offer have replaced this, with successful candidates placed directly into projects. Hence, this study argues the pedagogy of human resource (HR), organisational behaviour, organisational development (OD), and Business Psychology at the master's level needs to be experiential so that students transition seamlessly into jobs with industry-aligned competencies. while existing research evaluates teaching methods such as case studies and lectures in academic settings, few examine their workplace applicability. This qualitative study fills this gap by investigating how pedagogical approachesspecifically continual assignments, case studies, presentations, OD activities deployed in the classroom and the internship experience gear them up to secure jobs and perform efficiently. The study implies that these methods cultivate systems thinking, equipping students to diagnose and address organisational disparities. It calls for curriculum redesign to integrate such practices, supported by heuristic evidence from OD practitioners. 2026 by John Wiley & Sons, Ltd. All rights reserved. -
Contextualising Pedagogy: The Sociocultural Revision of Psychology Education
Pedagogical considerations play a vital role in shaping the development of individuals, especially in the context of rapid technological advancements. There is a growing understanding that the multidirectional teaching-learning process extends beyond cognitive processes to include social and cultural dimensions. In psychology education, it becomes an imminent necessity to adapt to pedagogical advances to fulfil diverse student needs and to balance between the academic and practitioner approaches. This chapter explores the importance of contextualising psychology pedagogy within specific cultural and Indigenous frameworks, presenting contextualisation as a dynamic process that requires ongoing adaptation by educators to promote inclusive and effective learning for all students. The discussion begins by outlining the need to contextualise pedagogy, exploring how learning environments are influenced by cultural, political and social factors, supported by theoretical frameworks like classical approaches of Vygotsky, and more recent ones like Melanie Walker's critical capability approach. The chapter will explore the diverse contexts that could be considered for localised, context-sensitive equity and justice-oriented pedagogies, such as the digital age, multicultural classrooms, Indigenous settings and other diverse learning environments. It will also explore challenges to contextualising pedagogy, including reconciling Western models with specific cultural values and managing the discord between standardisation and localisation. The chapter concludes with strategies for contextualising, underscoring the importance of balancing international educational standards with the realities and needs of local contexts. 2026 by John Wiley & Sons, Ltd. All rights reserved. -
Addressing Security Challenges in AI-Driven Cyber Security: Enhancing Resilience While Fostering Sustainable Practices with Green Computing
The modern cyber security environment changed through increased sophistication and complexity of cyber threats that requires organizations to use artificial intelligence (AI) technologies for strengthened security frameworks. It also limits the adverse impact within the populace by a decrease in carbon dioxide emissions, energy conservation, decrease wastage of electronic gadgets and assistance to sustainability with renewable resources. Among the practices of creating the green environment are the measures of virtualization, improving the quality of the hardware to increase the energy efficiency and using the cooling technologies efficiently. The Sustainable Cyber security practices are examining the measures and innovation for minimizing energy usage by integrated cyber security tools/infrastructure, green data center/network, and practicing green software engineering. In this domain, Sustainability Cyber security employs energy conservative cryptographic algorithms and software architecture, low energy cryptographic physical devices, power-conscious security protocols; efficient virtualization by integrating these approaches, they can advance sustainability into higher security statures. Besides, the enforcement of those security practices will help to address green data center objectives like server virtualization, and other efficiency data storage products. Cyber Security algorithms will act to lessen the time construct of cryptographic operations to less computational power, and hence less energy consumption. It also looks at the direction that sustainability is likely to take in the future, which may include such policies and structures as are likely to promote green computing in cyber security. Also through this case study, we have been able to incorporate green computing into its cyber security programs for a better and environmentally friendly future. The advanced strategic planning through automation enables organizations to develop stronger defense capabilities as they adjust to security threats which keep evolving in the present-day landscape. 2026 Scrivener Publishing LLC. -
AI in Financial Fraud Detection and Prevention
Fraud has always posed problems to financial institutions and with the rapid growth of digital transactions, and its complexity has increased beyond detection. Normal methods of fraud detection that depend on rules only are severely outdated and ineffective against newer types of schemes. It is now imperative to employ more sophisticated mechanisms for fraud detection considering the evolvement of financial crimes. The massive amounts of transnational data that need to be analyzed to detect fraudulent patterns can now be processed with medium to high levels of accuracy using AI with the help of machine learning, deep learning, and natural language processing (NLP), and fraud detection and prevention have been transformed for the better. Algorithms of machine learning like supervised, unsupervised, and reinforcement learning are central to the features of fraud detection. Suspicious transactions are detected during supervised learning by using already existing fraudulent data, whereas unsupervised learning detects all anomalies without any prior defined labels. Through real-time data input, reinforcement learning adjusts its detection methodologies. Deep learning models such as convolutional neural networks and recurrent neural networks identify and process fraud indicators hidden within messages or intricate datasets. Moreover, through intricate analysis of customer interactions, NLP techniques detect fraudulent activities by identifying phishing attempts and deceptive communications. The chapter touches upon the issues of implementing AI oriented fraud detection in realms like e-commerce and entertainment. Identifying fraud from e-commerce is complicated by factors like high volume of transactions, false positives, privacy issues, and the endless frameworks of fraud. Finally, the chapter provides a summary of the main insights and makes recommendations for further investigation like incorporating blockchain, federated learning, and higher explainability to bolster AI powered fraud detection systems. 2026 Scrivener Publishing LLC. -
Adaptive AI: Transforming Natural Language Processing and Industry Applications
Adaptive Artificial Intelligence (AI) is an innovative development in the domain of intelligent systems because machines have attained the ability to independently learn, modify, and optimize their operations based on experience and other real-time information. While traditional artificial intelligence (AI) is programmed to follow a certain set of algorithms and rules step-by-step, adaptive AI systems have a level of independence that affords them the flexibility to change their actions. As a result, healthcare, finance, education, manufacturing, and many other industries can now employ AI, which was formerly not possible due to its inflexible nature, for enhanced and efficient decision-making, improved consumer practice, and effective working processes. There is significant scope for adaptive AI to transform Natural Language Processing (NLP) as well as business practices and solve complex problems. On the other hand, there is also the advancement of dependency on data, algorithmic perception, and ethical inquiries concerning the application of these technologies which pose a challenge. This proposed chapter emphasizes the techniques and applications of Adaptive AI in NLP and the ethical challenges that make it authoritative to adopt responsible development of artificial intelligence. 2025 Scrivener Publishing LLC. -
Data Driven Emergency Response Management for UAV-Based Future Transportation A Case Study
The transportation sector plays a vital role and is heavily involved in emergency response and disaster relief because of the necessity for quick deployment, evacuation and rescue operations, supply chain support, infrastructure restoration, aerial support and surveillance, traffic management, and route optimization, among other things. All of these are areas that can greatly benefit from the use of drones. The capabilities of drones provide an efficient and speedy option for surveying impacted regions, spotting possible dangers, finding survivors, accessing dangerous or inaccessible locations, delivering supplies, and generally facilitating relief efforts with speed and minimal human risk. UAV (Unmanned aerial vehicle)-based transportation can become a precise substitute for time-sensitive items, emergency relief, medical supplies, and more by overcoming obstacles like traffic and geographical accessibility. The success of emergency response management for UAV-based transportation is dependent upon the quality of the data collected and the effectiveness of its analysis and interpretation. Hence, in this chapter, we propose to analyze and explore the challenges and issues involved in the design and implementation of a data-driven emergency response management system for UAV-based future transportation and its applications. 2026 Scrivener Publishing LLC. -
Journey to Transportation and Logistics Management Using Drone
The speedy adoption and amalgamation of drone technology in every sector of life have correlated environmental implications. It has come to reality due to revolutionization on the technology front and the movement for a digitized world by adopting digitization in the course of action. The drones have the capacity to decrease the rate of carbon emissions at significant levels in transportation and logistics management. So, this is becoming the need of an hour to apply the technology for the well-being of an individual. The comprehensive study and assessment in this chapter will address the implications of an environment connected to drone-based transportation and logistics operations. It will comprise the assessment based on academic studies, industry reports, and environmental assessments in terms of carbon emissions, energy consumption, and ecological footprint. The chapter will highlight the concerns and contributions in view of mitigating the environmental implications linked with the deployment of drones in transportation and logistics, enabling stakeholders to develop strategies that foster sustainability in the industry. 2026 Scrivener Publishing LLC. -
Enhancing the Operational Efficiency of FPOs by Using Predictive Model Building in Machine Learning Through Feature Selection Method
This study employs a machine learningbased feature selection approach to identify key factors that significantly enhance the predictive accuracy of models assessing farmer producer organization (FPO) performance. It focused on an FPO in the Anantapur and Kadapa districts of Andhra Pradesh, India; the research investigated the operational effectiveness of small and marginal farmers who are members by the end of 2022. The study reviewed existing shortcomings and proposed necessary policy amendments to ensure the sustainability of FPOs. The study utilized a survey design method, with the exploratory questionnaire through the field study. A sample of 73 small-scale producer farmers from the region was selected for the analysis. The result indicated that a) the reason for the operational efficiency of FPOs, b) the gradient boosting regressor achieved the highest testing accuracy of 0.78 to predict the best feature for FPO performance, and c) FPO insights for policy guidelines. 2025 Scrivener Publishing LLC. -
Role of Graph Convolutional Neural Networks (GCNN) in Computer Vision Applications
Graph Convolution Neural Networks (GCNNs) are an important concept in advancing computer vision by transforming the understanding and modeling of graph-structured data. They have a unique capability to capture intricate relations along with the visual content that goes beyond the traditional and usual convolutional neural networks, it also empowers computers to observe and interpret the complex interconnection between the elements in images, which enhances the depth and nuance of visual dentata analysis. As a revolutionary study in computer vision, GCNNs are poised to transform various industries by unleashing new frontiers in the visual information domains analysis and interpretation. Their multifaceted applications promise to reshape the landscape of computer vision. 2026 Scrivener Publishing LLC. -
Generative AI for Next-Generation Recommender Systems: Architectures, Applications, and Future Directions
The recommender systems have become a must in delivering personalized experiences across digital platforms. Still, traditional approaches, such as collaborative and content-based filtering, suffer from some inherent limitations: data sparsity, scalability, and dynamic user adaptation. In this context, generative AI emerges as a game-changing solution empowered by state-of-the-art models like variational autoencoders (VAEs), generative adversarial networks (GANs), and transformers to overcome the above-mentioned limitations. These models make possible the synthesis of user-item interaction data, uncovering latent patterns and providing context-aware recommendations, thereby redefining personalization in recommender systems. This chapter provides a detailed survey on the role of generative AI in recommender systems, their components, architectures, and applications. Case studies in e-commerce, entertainment, and education provide insights into how generative models help drive personalization, tackle the cold-start problem, and adapt dynamically to the evolution of user behaviors. Nevertheless, open issues regarding computational complexity, privacy protection, and ethical considerations remain. To address these, the chapter outlines the future enhancements in the areas of federated learning for privacy-preserving collaboration, multimodal data integration for holistic user profiling, and explainable AI frameworks to foster transparency and trust. Bridging these gaps would let generative AI-driven recommenders further revolutionize personalization, scalability, and inclusiveness, opening up a way to innovative solutions across the board in various industries. 2026 by John Wiley & Sons Inc. All rights reserved.