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Feature films as pedagogy in higher education: A case study of Christ University, Bengaluru
Contemporary education system in India was initiated by the British for the maintenance of their imperial administration. After India became an independent country, conscious efforts were made to overhaul the educational system to produce proper administrators and contributors for Indian polity, economy and culture. To assess dynamics of Indian education, various committees and commissions were formed. It also meant change in education programs, curricula and syllabi to meet national needs and global challenges. Most universities in India have limited infrastructure, thus the role of private or deemed to be university becomes crucial. Christ University attending to the social structure, internationalization and employability demands, offers a number of quality educational programs to ensure employable graduates. This has led the way in devising pedagogy and curricula to align with the global higher education practices. Here we discuss the use of commercial feature film as a pedagogical tool in the classrooms within the Deanery of Humanities and Social Sciences and its implication. 2018, IGI Global. -
The reality of distribution faced by SMEs: A UK perspective
[No abstract available] -
Bioactive Compounds and Biological Activities of Ensete Species
Ensete, commonly known as the false banana, is a plant of the subtropical and tropical regions of Asia and Africa. Ensete has received global attention in the past decade. The various parts of the plant, such as the fruits, fruit peel, corm, pseudostem, seed, leaves, flowers, sap, and roots, have been used in traditional medicine to treat various ailments. Starch and other minor/trace components found in Ensete plants have been used as tablet binders, disintegrants, pharmaceutical gelling agents, and sustained release agents in pharmaceuticals and nutraceuticals. Ensete has been used as a staple and co-staple food by Ethiopians and has many ethnomedicinal uses. The present chapter validates the historic use of various parts of Ensete in treating ailments by providing detailed information on the phytochemicals present in the plant and discussing various biological properties such as antioxidant, antimicrobial, antidiabetic, immunomodulatory, hypolipidemic, cytotoxic, antiurolithiatic, antiestrogenic, nephroprotective, and hepatoprotective properties. Springer Nature Switzerland AG 2024. -
Green space and mental well-being research in India: An urgent need for intervention
In recent years, numerous studies have highlighted the positive impact of green spaces on mental health and overall well-being. However, a closer examination reveals a skewed green space research contribution, with developed countries taking the lead. Despite substantial burden of mental health issues, there is a noticeable dearth of green space research within India's academic landscape. In the current paper, we address this gap through a brief review that positions the scope of green space psychology (GSP) in India. We conducted the literature review using a machine learning tool called Crawling Scholar. Our review comprised 325 studies, focusing on five key parameters: the year of publication, geographical context, research design, psychological variables examined, and study population. Our findings indicate a significant body of global research on GSP, while the contribution from Indian scholarship remains negligible. Based on this discrepancy, we propose that incorporating GSP as an intervention and preventive measure could play a crucial role in addressing India's mental health challenges. By integrating traditional practices with the emerging field of GSP, we can harness the potential of green spaces to promote mental well-being. Our findings further underscore the importance of expanding research on GSP within the Indian context and emphasize the need for further investigations into its efficiency. By shedding light on the current status of GSP research in India, we aim to raise awareness among researchers, policymakers, and mental health professionals, fostering a collaborative effort to leverage the benefits of green spaces for the betterment of mental health infrastructure in India. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Affiliate Marketing and the Symbiotic Relationship in the Pharma Industry
The objective of the study is to understand the dynamic relationship between customers and the healthcare industry giants in the Indian context. The purpose revolves around how the consumer is benefitting and at the same time, how the indirect third-party affiliates also earn marginal profits along with serving the customers. The study is backed by both primary and secondary data, which were collected from 173 individuals from various fields through a questionnaire. The convenience sampling method was used to select the respondents, and the Technology Acceptance Model (TAM) was used to propose the model for the study. There exists a parallel symbiotic relationship between consumers, pharmaceutical companies, and affiliates. The application of this research can be put to use for the startups, which want to explore and excel in this industry along with the future researchers who want to forecast and study the progress of the pharma companies in the long run. The empirical evidence of this paper highlights a unique relationship between affiliates, the pharma sector, and customers, which drives customer buying behavior and a combination that has not been explored yet. The study provides a unique understanding of how feedback from customers in third-party applications can benefit and produce huge profit margins down the line. 2025 Apple Academic Press, Inc. -
The Shame of Ageing During Fourth Industrial Revolution: A Thematic Analysis of Indian Adults
The Fourth Industrial Revolution (4IR), a term popularised by Klaus Schwab in 2016, connected the physical-biological and the digital world. This is an era of artificial intelligence and computational technologies suited to satiate the needs of the human race. The emphasis is also on a digital identity we have developed alongside our physical and psychological entities. Millennials and Gen Z have a cognizant grip on their digital identity and are known to use the fruits of 4IR in their everyday livelihood. However, with the advent of Industry 4.0, the generation of Baby Boomers and Gen X have had to undergo much re-learning and accommodate the newer ways of integrating digitalization in their lives. The process has brought about occupational threats and shaming related to failure to upgradation and flexibility. This article explores the influences of these social experiences on the identity and self-concept of the quinquagenarians and the sexagenarians. The article follows a qualitative method where using a thematic approach, the emerging themes from the in-depth interviews will be analyzed in detail to form a theoretical framework for shaming among the Indian Baby Boomers and Gen X. The variables in focus are adjustment, coping styles, resilience, the purpose of life, and Self-Image. The study explores the themes of Indian adults, which emerge from interviewing 46 participants, who have been associated with full-time employment and are between 77 and 59 years of age, representing the Baby Boomers, and those between 43 and 58 years of age, representing Gen X. The analysis adopts a psychoanalytic approach, where the data is interpreted using an Eriksonian lens. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Suicide and Youth: Positive Psychology Perspective
Suicidality and self-harm among adolescents and young adults need immediate attention and support. This is often seen as a cry for help where a feeling of entrapment experienced by individuals pushes them to see self-harm as a coping mechanism. Lack of social support and co-morbid emotional disorders influences suicidal ideation into planning and action. A general feeling of helplessness that gets triggered often leads to anguish. These emotions get internalized and directed inwards leading to self-directed anger which facilitates a suicidal act. Early detection and identification can prevent the loss of lives and help individuals to learn effective ways of coping. Gatekeeper Training for caregivers, teachers, and their peers will help in detecting the early signs of suicide risk. Intervention based on positive psychology will help not only in crisis management but also as preventive and maintenance therapy in holistic mental health. The concepts of hope, forgiveness, self-compassion, gratitude, and resilience can be incorporated into the intervention programs to build a better therapeutic system for youths dealing with suicidality. Practicing effective coping mechanisms every day and making it a ritual of ones daily life is the need of the hour. Integrating adaptive ways of emotional expression and learning matured means to deal with painful emotions and trauma is what needs to be incorporated into the intervention plan. The chapter focuses on these aspects and aims to make a connection between assessing and easy identification of youths in distress related to suicidality and providing a holistic intervention to help them cope with the situation. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Fraud detection in the era of AI: Harnessing technology for a safer digital economy
Fraudulent activities have increased along with the new prospects of the digital economy's quick growth for both consumers and enterprises. Conventional techniques of fraud detection are insufficient to keep up with these ever-evolving fraudulent strategies. In this sense, machine learning (ML) and artificial intelligence (AI) have become potent instruments to prevent and detect fraud and guarantee the safety of online transactions. This study examines the function of AI and ML and shows how these technologies can spot irregularities and intricate patterns that would be challenging to find with conventional methods. The study includes various methods of AI-based fraud detection and analyses important ethical issues related to these practices. Furthermore, the study looks at developing technology and trends that will probably influence fraud detection in the future. In conclusion, the revolutionary potential of AI and ML in building a safer digital economy is analysed. 2024, IGI Global. All rights reserved. -
From bean to brain: Coffee, gray matter, and neuroprotection in neurological disorders spectrum
Coffee is a popular drink enjoyed around the world, and scientists are very interested in studying how it affects the human brain. This chapter looks at lots of different studies to understand how drinking coffee might change the brain and help protect it from neurodegenerative disorders especially like schizophrenia. With the help of available literature a link between the coffee mechanism and neurodegenerative disorders is established in this chapter. Researchers have found that drinking coffee can change the size of certain parts of the brain that control things like thinking and mood. Scientists also study how coffee's ingredients, especially caffeine, can change how the brain works. They think these changes could help protect the brain from diseases. This chapter focuses on how coffee might affect people with schizophrenia as hallucination is caused during and after excess consumption of caffeine. There's still a lot we don't know, but researchers are learning more by studying how different people's brains respond to coffee over time. Overall, this chapter shows that studying coffee and the brain could lead to new ways to help people with brain disorders. This study also draws ideas for future research and ways to help people stay healthy. 2024 Elsevier B.V. -
Diabetic Retinopathy Detection Using Various Machine Learning Algorithms
The advances in technologies have paved the way to generate huge amounts of data in a variety of forms. Machine learning techniques, accompanied by Artificial Intelligence with its challenging nature help in extracting meaningful information from such data. This will have a great impact on many sectors, such as social media analytics, construction and healthcare, etc. Computer-aided clinical decision-making plays a vital role in todays medical field. Hence, a high degree of accuracy with which machine learning algorithms can detect diabetic retinopathy is really in demand. Convolutional neural networks, a deep learning technique, have been used to recognize pathological lesions from images. Image processing and analytics methods are used and have been trained to recognize the significant complications of diabetes, which cause damage to the retina, diabetic retinopathy (DR). Though this condition does not show any symptoms in its early stages, it has to be screened, diagnosed and treated at the earliest or it may lead to blindness. Deep neural networks have proved successful in screening DR from retinal images and handling the risks that may arise due to the disease. This chapter focuses on detecting diabetic retinopathy in retinal images by using efficient image processing and deep learning techniques. It also attempts to investigate the requirements of image pre-processing techniques for diabetic retinopathy. Experiments are carried out by taking a set of retinal images and predicting the level of diabetic retinopathy on a scale of 0 to 4. Deep learning techniques like CNN and DenseNet are applied and tested. 2024 Taylor & Francis Group, LLC. -
Investor behaviour, market efficiency, and regulatory challenges in digital currency investments: A comprehensive literature review
The rapid proliferation of digital currencies has ignited significant interest in understanding investor behaviour and the regulatory challenges within this evolving financial landscape. The study seeks to elucidate the factors that influence investor behaviour in the cryptocurrency/digital currency market and explore the regulatory implications associated with digital currency investments. A systematic approach was adopted to identify, review, and analyze relevant scholarly articles from reputable databases. The selected articles span various dimensions of the cryptocurrency/digital currency ecosystem, including investor behaviour, market efficiency, technological innovation, and regulatory measures. It reveals that investor behaviour in the digital currency market is influenced by a complex interplay of emotions, market sentiment, and information asymmetry. Additionally, market efficiency theories are being reconsidered in light of the highly volatile nature of cryptocurrencies. Regulatory challenges encompass issues related to fraud, pump-and-dump schemes, and legal ambiguity. 2024, IGI Global. All rights reserved. -
Initial coin offerings as a form of alternative financing for start-ups: A systematic literature review and bibliometric analysis
This chapter aims to provide a comprehensive overview of the field of initial coin offerings ICOs as a form of alternative financing for start-ups. Through a systematic literature review and bibliometric analysis, the study explores the current understanding of ICOs, the potential uses of fractional ownership of digital assets, and the opportunities and challenges associated with this form of fundraising. The study also highlights the importance of study, which provided the first comprehensive explanation of ICOs and their characteristics. The findings of the research suggest that ICOs have the potential to revolutionize the way start-ups raise funds, but they also present significant challenges and risks. The study encourages further research to continue exploring the opportunities and challenges presented by ICOs, as well as the potential impact of regulatory and legal frameworks on the ICO market. Overall, this chapter provides valuable insights into the complex and evolving topic of ICOs and their implications for start-ups, investors, and the broader economy. 2024, IGI Global. All rights reserved. -
A study of mediating factors influencing student motivation and behaviour: A literature review
This study aims to examine the mediating factors of learning environment, technology, good behaviour, and effective communication, sports, media, problem-based case study, and psychological influence on student motivation and behaviour. The study employs secondary data based on peer-reviewed articles, conference papers, and books collected from a variety of sources such as Scopus, WoS, J-Store, EBSCO, ProQuest, etc. between 1982 and 2022. The 103 articles have been selected based on the keywords which related to study. The results evidenced that the mediating factors have a significant positive impact on student motivation and behaviour. This study contributes to the existing literature by providing a com- prehensive understanding of the relationship between the mediating factors and student motivation and behaviour. The findings of this study have implications for educational institutions, policy makers, and educators in creating effective learning environments that can enhance student motivation and behaviour. 2023, IGI Global. All rights reserved. -
Driving sustainable development through climate finance in India: A case study of the National Clean Energy Fund (NCEF)
This case study examines the national clean energy fund (NCEF) as a climate finance policy in India. The NCEF was established with the objective of promoting renewable energy projects and sustainable development in the country. The study explores the background and context of climate finance, providing an overview of the NCEF's goals and implementation. The case study analyzes the impact of the NCEF by examining its funding allocations and utilization over the years. It highlights the challenges faced in effectively utilizing the funds, such as administrative hurdles, limited capacity, policy uncertainties, project development barriers, financial constraints, and governance issues. Furthermore, the case study discusses the socio-economic impacts of the NCEF, including job creation, clean energy adoption, and environmental benefits. It also explores the lessons learned from the NCEF implementation, identifying areas for improvement and providing recommendations for enhancing climate finance mechanisms in India. This chapter creates a contribution to renewable energy development in India. 2023, IGI Global. All rights reserved. -
Accounting fraud and bankruptcy: The case of wirecard AG
This chapter examines the scandal at Wirecard AG, a German payment processing and financial services company, that became one of the most valuable companies on the German stock exchange in the 2010s. From 2010 to 2018, Wirecard reported consistent revenue growth and profitability. In 2019, the company reported revenues of 2.8 billion ($3.2 billion). As of September 2018, its market capitalization was over 24 billion ($27 billion). In late 2019, the Wirecard scandal was discovered through investigative reports by the Financial Times, which raised questions about Wirecard's accounting practices. The company faced a major scandal in 2020 when it was revealed that 1.9 billion ($2.1 billion) was missing from its balance sheet. Subsequent investigations revealed a massive accounting fraud that had been going on for years. Subsequently, the company filed for bankruptcy. Multiple Wirecard executives, including its CEO, were charged with fraud and market manipulation. German regulators and auditors were criticized for failing to detect and prevent the fraud. 2023, IGI Global. -
Exploring the influence of emotional intelligence on decision-making across diverse domains: A systematic literature review
Emotional intelligence (EI) is increasingly recognized as a crucial factor in decisionmaking across various professional domains. This systematic literature review, covering the period from 2017 to 2023, explores the intricate relationship between EI and decision-making in healthcare, business, education, ethics, and the realms of neuroscience and artificial intelligence (AI). Employing a qualitative research design, the study systematically analyzes articles retrieved from renowned databases including Scopus, ProQuest, EBSCO, J Gate, and Google Scholar. The findings reveal that elevated EI levels among healthcare professionals lead to improved clinical decision-making, characterized by enhanced patient-centered care and ethical considerations. In business and legal contexts, EI competencies are associated with ethical decision-making, effective leadership, and strong client relationships. In education, emotionally intelligent educators create supportive learning environments conducive to better pedagogical decisions and student emotional well-being. 2024, IGI Global. All rights reserved. -
A case study on a beacon of hope transition: India's renewable energy integration and the Ujwal DISCOM assurance Yojana (UDAY)
This case study examines the transformative impact of the Ujwal DISCOM Assurance Yojana (UDAY) on India's energy landscape, focusing on its role in facilitating renewable energy integration. India's energy sector faced daunting challenges, including financially distressed power distribution companies (DISCOMs) and high aggregate technical and commercial (AT&C) losses. UDAY's financial restructuring and operational efficiency improvements led to remarkable reductions in DISCOMs' debt burdens and AT&C losses, respectively. The policy aligned with India's renewable energy goals, driving DISCOMs to procure renewable energy sources. Consequently, India witnessed significant growth in its renewable energy capacity, environmental benefits through reduced emissions, and economic growth via job creation. This case study offers insights into the challenges faced, technological advancements incentivized, and the long-term sustainability of these reforms. Moreover, it presents broader lessons for energy sector reform and renewable energy integration, both within India and globally. 2024, IGI Global. All rights reserved. -
Mapping the AI landscape in healthcare quality: A bibliometrics analysis
This study explores the application of Artificial Intelligence (AI) in healthcare quality improvement through a bibliometric analysis of 222 documents retrieved from the Scopus database using the keywords "healthcare," "quality," and "AI." By examining bibliographic coupling, citations, co-citations, author keywords, and co-occurrence networks, the research unveils the key themes, prominent authors, and emerging trends in this field. The analysis reveals a focus on areas like machine learning for disease prediction, clinical decision support systems, and patient safety improvement. Leading authors and research groups are identified, and promising future directions such as explainable AI and integration with electronic health records are highlighted. This study contributes to understanding the current landscape of AI in healthcare quality improvement and guiding future research for maximizing its impact. 2024, IGI Global. All rights reserved. -
Predicting cryptocurrency prices model using a stacked sparse autoencoder and Bayesian optimization
In recent years, digital currencies, also known as cybercash, digital money, and electronic money, have gained significant attention from researchers and investors alike. Cryptocurrency has emerged as a result of advancements in financial technology and has presented a unique opening for research in the field. However, predicting the prices of cryptocurrencies is a challenging task due to their dynamic and volatile nature. This study aims to address this challenge by introducing a new prediction model called Bayesian optimization with stacked sparse autoencoder-based cryptocurrency price prediction (BOSSAE-CPP). The main objective of this model is to effectively predict the prices of cryptocurrencies. To achieve this goal, the BOSSAE-CPP model employs a stacked sparse autoencoder (SSAE) for the prediction process and resulting in improved predictive outcomes. The results were compared to other models, and it was found that the BOSSAE-CPP model performed significantly better. 2023, IGI Global. -
Prediction and analysis of financial crises using machine learning
This study presents a comparative analysis of various machine learning algorithms for credit risk assessment. The algorithms were tested on two credit datasets: German Credit Dataset and Australian Credit Dataset. The performance of the algorithms was evaluated based on several metrics, including sensitivity, specificity, accuracy, F-score, and Kappa. The results showed that the FCPFS-QDNN algorithm outperformed other algorithms in both datasets, achieving high accuracy, sensitivity, specificity, and F-score. On the other hand, the ACO Algorithm and Multilayer Perceptron algorithms were found to perform poorly in both datasets. The findings of this study have significant implications for credit risk assessment in banking and financial institutions. The study recommends the use of the FCPFS-QDNN algorithm for credit risk assessment due to its superior performance compared to other algorithms. 2023, IGI Global. All rights reserved.