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                <text>Transformational innovation technologies for regenerative bioeconomy: Case study on green initiatives for tourism logistics service providers</text>
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                <text>The tourism industry has negative environmental consequences, overshadowing the regenerative bioeconomy. Climate change, land degradation, and resource depletion are significant challenges. Excessive use of non-biodegradable resources threatens the planet, requiring bio-based resources. It is critical to transition to and reuse bio-based resources. In this chapter, the regenerative bioeconomy has a wide- reaching impact on accomplishing SDG 6, 8, 11, and 12, with a focus on the circular economy's involvement in tourism logistics. Investments in talent development, digital technologies, and partnerships are needed to realise bioeconomy potential. Engaging local communities and implementing sustainable business practices can reduce energy use and environmental impact. Digital transformation requires technological advancements, foreign investment, and active participation from all stakeholders. This chapter tries to explain the complicated interplay between the regenerative bioeconomy, tourism logistics, and sustainable practises intertwining.  2023, IGI Global.</text>
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                <text>Sejana Jose V.; Varghese B.</text>
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                <text>Handbook of Research on Bioeconomy and Economic Ecosystems, pp. 353-367.</text>
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                <text>Ability; Benevolence; Integrity; Malaysia; Organizational citizenship behavior; Transformational leadership; Trust; Trustworthiness</text>
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                <text>This study investigates the pivotal role of trust in bridging the effects of transformational leadership on organizational citizenship behavior (OCB). The study was conducted using a multilevel longitudinal approach with 276 employees in 71 teams from private medium-sized organizations in Kuala Lumpur, Malaysia. Transformational leadership was found to be positively related to: (1) three facets of trustworthiness (ability, benevolence, and integrity); (2) trust in the leader; and (3) OCB. All three facets of trustworthiness mediated the relationship between transformational leadership and trust in leaders. In addition, trust in the leader mediated only the relationship between the benevolence facet of trustworthiness and OCB. As OCB is inherently benevolent, these findings not only are consistent with the principle of compatibility, but they also contribute to theorizing about how trust plays an important role in the influence of transformational leadership on employees.  The Author(s) 2023.</text>
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                <text>Current Psychology, Vol-43, No. 11, pp. 9567-9582.</text>
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                <text>Lee M.C.C., School of Psychology, Massey University, Auckland, Albany, 0745, New Zealand; Lin M.-H., Department of Psychology, Sunway University, Bandar Sunway, Selangor, Petaling Jaya, 47500, Malaysia; Srinivasan P.M., Department of Psychology, Christ University, Karnataka, Bengaluru, 560029, India; Carr S.C., School of Psychology, Massey University, Auckland, Albany, 0745, New Zealand</text>
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                <text>The critical shifts in the utility, implementation, and enforcement of human rights have been achieved as a result of the rise of cutting-edge technological innovation. As a result, there has been a plethora of research on the expansion of beneficiaries of the human rights and the subject matter of such rights. The authors of this chapter contend that in this era of technology, we need to reevaluate our approach to human rights, broaden the scope of those to whom obligations relating to human rights apply by including corporations and other organizations, and be ready to consider the possibility that artificial intelligence will become a topic of discussion in public relations and fundamental rights. In this chapter, a three-pronged approach to thinking about digital rights is presented. This method takes into consideration the subtle structural impact that considering human rights in the digital age has on the job that the courts do.  2024 by IGI Global. All rights reserved.</text>
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                <text>Disruptions to sleep have a substantial influence on people's overall health and quality of life. The conventional techniques for diagnosing and managing sleep disorders usually rely on subjective assessments and qualitative evaluations, that may have some accuracy and efficacy limitations. Nevertheless, recent developments in the field of artificial intelligence (AI) have presented new opportunities for better diagnosing and treating problems with insomnia. The paper reviews in depth the uses of AI in the domain of medical sleep medicine. We look at the use of algorithmic techniques for deep learning and machine learning for identifying indicators of sleep-related issues, the assessment of sleep quality, sleep tracking, and the establishment of individualized sleep therapeutics. We also discuss how AI is being used to construct forecasting models that may be used to identify individuals who are at risk of experiencing sleep issues and improve treatment strategies. In addition, we talk about the challenges and potential outcomes of incorporating AI-based techniques into clinical practice. Overall, our research highlights how AI has the potential to transform the field of sleeping medicine and improve outcomes for people with sleep-related conditions.  2023 IEEE.</text>
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                <text>Transformative Metamorphosis in Context to IoT in Education 4.0</text>
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                <text>In the modern technology-driven era, it is important to consider a new model of education to keep pace with Industry 4.0. In view of this, the present paper critically explores the issues, discusses potential solutions along with a comprehensive analysis of the applications of technologies such as Internet of Things (IoT) in modern education specially Education 4.0, and examines the potential of these technologies to transform the education sector. The challenges faced by previous education models are analysed along with how they pave the way to the inclusion of IoT in education, leading to Education 4.0. The potential benefits of IoT in improving learning outcomes, enhancing student engagement and retention, and supporting teachers are also highlighted. In addition, it addresses the ethical and privacy concerns associated with the use of these technologies and suggests areas for future research.  2023 A. K. Biswal et al.</text>
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                <text>Biswal A.K.; Avtaran D.; Sharma V.; Grover V.; Mishra S.; Alkhayyat A.</text>
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                <text>Biswal A.K., School of Computer Engineering, Kalinga Institute of Industrial Technology (Deemed to be University), Bhubaneswar, India; Avtaran D., School of Computer Engineering, Kalinga Institute of Industrial Technology (Deemed to be University), Bhubaneswar, India; Sharma V., CHRIST (Deemed to be University), NCR, Delhi, India; Grover V., Noida Institute of Engineering &amp;amp; Technology, Greater Noida, India; Mishra S., School of Computer Engineering, Kalinga Institute of Industrial Technology (Deemed to be University), Bhubaneswar, India; Alkhayyat A., College of Technical Engineering, The Islamic University, Najaf, Iraq</text>
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                <text>An application of Kolb's experiential learning theory (ELT) in real situations as a blend of Bloom's taxonomy of education is given as a case study conducted about more than 15 years ago. The world has changed since then with revolutionary developments in the techno-world. Student portfolio is regarded as the documentary evidence created by the student to diagnose the student's strengths and weaknesses to assist him or her in learning. In light of this case study and developments in technology, further scope in the application of the ELT model is discussed. It is also recognised that technology to facilitate experiential learning using virtual reality or augmented reality tools is to be made more user-friendly in terms of affordability and that neuroplasticity has an important role to play in this. A case for more research in neuroscience to analyse learning styles is raised.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved.</text>
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                <text>Neuro-Systemic Applications in Learning, pp. 3-25.</text>
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                <text>Dixit G.N.M., SMS Foundation, Aundh, Pune, Maharashtra, India; Thomas K.A., School of Education, Centre for Education Beyond Curriculum (CEDBEC), CHRIST (Deemed to be University), Bengaluru, Karnataka, India</text>
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                <text>Leena Sri, R.; Vetriveeran, Divya; Sambandam, Rakoth Kandan; Jenefa, J.; Thangavel, Karthikeyan</text>
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                <text>Leena Sri R., Thiagarajar College of Engineering, Madurai, India; Vetriveeran D., Thiagarajar College of Engineering, Madurai, India; Sambandam R.K., CHRIST (Deemed to be) University, Kengeri, Bangalore, India; Jenefa J., CHRIST (Deemed to be) University, Kengeri, Bangalore, India; Thangavel K., University of Technology and Applied Sciences, Al Khuwair, Muscat, Oman</text>
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                <text>The integration of artificial intelligence (AI) and machine learning (ML) is reshaping environmental monitoring, responding to the escalating complexities of issues like climate change and pollution. This article presents a comprehensive overview of current trends, challenges, and applications in AI-driven environmental monitoring. While technologies like remote sensing and Internet of Things (IoT) have improved data resolution, the sheer volume necessitates AI for efficient processing. The review emphasizes the role of AI in real-time monitoring, providing timely insights critical for addressing natural disasters and pollution. Exploring various environmental monitoring verticals-air and water quality, climate change modeling, biodiversity, and disaster prediction-the article highlights AIs versatility in addressing diverse concerns. Challenges such as data quality, bias, interpretability, and privacy are examined, underlining ethical considerations in biased models impacting marginalized communities. This chapter discusses common environmental modeling methodologies, ranging from empirical to geospatial modeling, elucidating their advantages and challenges.  2025 Scrivener Publishing LLC.</text>
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                <text>AI challenges; Artificial intelligence; deep learning models; environment monitoring and modeling; research directions</text>
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                <text>Transformer performance enhancement by optimized charging strategy for electric vehicles</text>
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                <text>charging stations; e-mobility; electric vehicle; optimization; transformer efficiency; transformer regulation</text>
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                <text>Transformer efficiency and regulation, are to be maintained at maximum and minimum respectively by optimal loading, control, and compensation. Charging of electric vehicles at random charging stations will result in uncertain loading on the distribution transformer. The efficiency reduces and regulation increases as a consequence of this loading. In this work, a novel optimization strategy is proposed to map electric vehicles to a charging station, that is optimal with respect to the physical distance, traveling time, charging cost, the effect on transformer efficiency and regulation. Consumer and utility factors are considered for mapping electric vehicles to charging stations. An Internet of Things platform is used to fetch the dynamic location of electric vehicles. The dynamic locations are fed to a binary optimization problem to find an optimal routing table that maps electric vehicles to a charging station. A comparative study is carried out, with and without optimization, to validate the proposed methodology.  2022. The Author(s)</text>
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                <text>Venkataswamy R.; Rao K.U.; Meena P.</text>
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                <text>Archives of Electrical Engineering, Vol-71, No. 1, pp. 37-56.</text>
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                <text>Polska Akademia Nauk</text>
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                <text>The financial function within organizations is evolving from a traditional cost-center role to a strategic partner powered by artificial intelligence (AI), data analytics, and advanced technologies. This transformation is reshaping how financial professionals analyze data, predict trends, and support decision-making. By leveraging AI, finance teams can automate repetitive tasks, enhance data accuracy, and deliver actionable insights in real-time. Integrating predictive and prescriptive analytics further empowers organizations to forecast financial outcomes, optimize resource allocation, and mitigate risks with precision. This shift to an AI-driven, data-centric finance model fosters agility, innovation, and enhanced collaboration across departments. It aligns financial strategies with organizational goals, improving operational efficiency and driving sustainable growth. However, the transition demands investments in digital infrastructure, a redefinition of roles, and an upskilling of personnel to handle complex analytics tools. The implications for organizational impact include enhanced competitiveness, informed decision-making, and a stronger ability to navigate an increasingly volatile economic landscape. This chapter explores these transformations, their challenges, and the opportunities they unlock for organizations aiming to thrive in a data-dominated era.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.</text>
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                <text>Kumar B., Modern College of Business and Science, Muscat, Oman; Mohammed Mueen Pasha M., CHRIST University, Bengaluru, India; Sandeep J., CHRIST University, Bengaluru, India; Deepak Kumar B., St Josephs University, Bengaluru, India; Franklin Jerold F., St Josephs University, Bengaluru, India; Jassim H., Modern College of Business and Science, Muscat, Oman</text>
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                <text>Food waste management is a stern issue that is prevalent around the word, affecting multiple countries and cultures. In a technology driven era, blockchain has gained intense attention because of its various beneficial facets. Blockchain is defined as a technology with its features like security, transparency and immutability, where only the authorized members in a network are given access. The decentralized technology enables transparency and traceability which can be used in food supply chain in conjunction with the various consensus mechanisms to validate transactions. This would ensure consistency and reliability, ensuring the stakeholders to track vivid stages such as food production, processing and distribution. Wastage of food is a cosmopolitan issue conducive to social, economic and environmental challenges. Our proposed work provides substantial benefits in a way to tackle inefficiencies in the food supply chain, Blockchain based business process reengineering can further automate these processes. The paper presents five popular consensus mechanisms that can be used for a sustainable food waste management. The work focuses on providing a blockchain based solution that is low powered and scalable, which in turn increases sustainability and reduces global food waste.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.</text>
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                <text>This book chapter delves into the influence of servant leadership on the profitability of social entrepreneurship, a phenomenon widely recognized by thriving startups worldwide. It generates hypothesis about the effect of seven facets of servant leadership viz., empowerment, conceptualization, followers influence, emotional convalescence, follower's growth and succession, value-creation for the community, and ethical behavior on social entrepreneurship profitability. The data was received through e-mail survey from 158 entrepreneurs located in Bengaluru. Hypothesis testing was done using multi-regression analysis technique. Results of the study specify that the seven dimensions of servant leadership except conceptualization have significant impact on the social entrepreneurship profitability. Further, the study continues with discussion of the inferences for practice by the social entrepreneurship, suggestions for future studies, and the continuous advancement of leadership tactics as well as styles that support upcoming social entrepreneurship ventures.  2024, IGI Global. All rights reserved.</text>
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                <text>Raghavendra A.N.; Thalari S.K.; Chandrika N.</text>
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                <text>Fostering Global Entrepreneurship Through Business Model Innovation, pp. 206-216.</text>
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                <text>Raghavendra A.N., Christ University (Deemed), India; Thalari S.K., CMR Institute of Technology, India; Chandrika N., CMR Institute of Technology, India</text>
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