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Enzyme-Assisted Wastewater Treatment in the Pharmaceutical Industry
No full textThe pharmaceutical industry is a significant source of environmental pollution; the main environmental concern being the presence of residues from pharmaceutical products within water bodies. Methods used to treat wastewater traditionally involve physical and chemical processes, which lack desirable characteristics since they result in high costs, consume large amounts of energy, and produce toxic byproducts. The use of enzymes in wastewater treatment appears as an effective and sustainable alternative. For instance, oxidoreductases, lipases, and proteases catalyze at mild conditions and could split pharmaceutical complex pollutants into less harmful forms. Enzymatic processes are friendly to the environment and may minimize the creation of toxic byproducts. An illustration is cases that have indicated successful pharmaceuticals, such as diclofenac and triclosan, could be degraded using laccase. Some technical difficulties in the process need to be overcome: complex techniques of enzyme immobilization, for instance, and high setup costs
Developing AI-Enhanced Task-Based Language Learning (TBLL) Activities
No full textThis chapter explores the integration of Artificial Intelligence (AI) into Task-Based Language Learning (TBLL) to create innovative, learner-centered language education experiences. It examines the theoretical foundations of TBLL and AI's transformative potential in language instruction, highlighting technologies such as adaptive learning platforms, natural language processing, and immersive virtual environments. By leveraging AI, educators can design dynamic, personalized tasks that foster meaningful communication, real-time feedback, and cultural relevance. The chapter also addresses challenges, including ethical considerations, algorithmic biases, and the digital divide, emphasizing the need for balanced implementation to maintain TBLL's communicative focus. Future directions include advanced personalization, multimodal interaction, and the incorporation of emerging technologies like augmented reality (AR) and virtual reality (VR)
Expectations vs Realities of Information Privacy and Data Protection Measures: A Machine-Generated Literature Overview
No full textThis book is a machine-generated literature overview of the legal and ethical debates over privacy and data protection measures in the last three decades, showcasing the expectations vis-à-vis realities of their presence and application in different sectors. The book identifies the role and application of consent in different situations. Over time, consent in its various forms and types, informed, explicit and otherwise, ensured data subjects have a measured understanding of the purpose of data processing. The idea of consent with time has been challenging to implement with the rapid advancement of research in different areas. It remains the most critical fulcrum, yet there are instances when the implementation continues to challenge
Forecasting the monthly tourist arrival from India to Nepal : an econometrics modeling approach
No full textTourism is a crucial component of the economy in developing countries like Nepal. Nepal is a popular tourist destination for India due to its proximity, shared cultural heritage, and affinities between the people and their respective religions. This study attempts to develop an econometric forecasting model to predict the monthly arrivals from India to Nepal. The COVID-19 pandemic significantly impacted the travel and tourism industry, causing a structural break in the time series arrival data. Using monthly data from 2004 to 2034, the study applies time series models to address complexities such as seasonality, non-stationarity, and structural breaks (due to COVID-19). The findings reveal that an ARIMAX model incorporating Google search trends data performs better than traditional models based on several evaluative measures such as RMSE, MAPE, AIC, and Theil’s U. The proposed forecasting model can assist policymakers, hotel management, and event planners in estimating the level of tourism demand and making better managerial decisions
Effectiveness of AI-Powered Wellness in Promoting Employee Wellbeing and Happiness
No full textAI-powered wellness programs are revolutionizing employee health and wellbeing by offering personalized and data-driven solutions. These programs leverage advanced algorithms and machine learning to provide tailored recommendations, support mental health, and enhance overall workplace wellness. Despite their benefits, such as improved employee engagement and reduced healthcare costs, challenges persist, including privacy concerns, data security issues, and the risk of algorithmic bias. Future trends indicate a focus on integrating emerging technologies like virtual reality and IoT, expanding mental health support, and ensuring inclusivity and ethical practices. This abstract explores the current landscape, benefits, challenges, and future innovations in AI-powered wellness programs, emphasizing the need for a balanced approach that combines technological advancements with human touch to achieve sustainable employee wellbeing
Personal data protection in a world of artificial intelligence and Internet of Things: consent, transparency and accountability
Get PDFThe right to the protection of personal data, whether as a standalone right or as an extension of the right to privacy, has gained much significance with advancements in technology. Consent with regard to the collection and processing of one's personal data is a crucial aspect of data protection. Consent represents an agreement on the part of the data subject authorising the collection and processing of the subject's personal data. A necessary corollary to consent is transparency in how the data subject's personal data will be used and processed. Without transparency, consent cannot be obtained in any real sense. Importantly, laws that protect privacy and personal data must ensure that entities responsible for collecting and processing personal data are held accountable to meet the requisite consent and transparency standards. However, artificial intelligence (AI) and the Internet of Things (IoT) have rapidly shifted us away from a model of one-to-one transactions to a one-to-many model in a completely automated environment. This transformation has made it exceptionally challenging to maintain a clear understanding of consent and transparency within this new environment. In this chapter, we explore this challenge with the hope of suggesting how the design and use of products, services, and applications that communicate with one another, incorporating automated technologies that function with little or no human intervention, could better address our expectations of consent and transparency with regard to the collection and processing of personal data
Decoding of Restorative Justice Practices: evidence from Indian police stations
No full textThis research explores the application of restorative justice (RJ) practices by the Indian police, a pioneering study in this context. Despite the absence of separate legislation on victims of crime and formal RJ practices in India, the study investigates how police officers in Tamil Nadu utilise RJ for less serious offences and domestic violence. The qualitative research method involves in-depth interviews with 18 lower-ranking police officers from five police districts, exploring the nature of cases, profiles of victims and offenders, resolution methods at the police station level, and challenges faced. The study reveals that non-conventional and RJ-related methods including restitution, conferencing, peace-making circles are employed to settle issues, primarily addressing domestic violence, property disputes, caste and communal conflicts, minor interpersonal issues, and financial disputes. The research highlights challenges in obtaining permission and cooperation from police officers but emphasises the dedication of officers to achieve peaceful resolutions. Thematic analysis of interviews underscores the significance of RJ in the Indian legal system, showcasing its potential to address disputes. Implications of the present research are discussed at the end of the chapter
Adapting to sea level rise: is India on- or off-track?
Get PDFLike many other regions worldwide, rising sea levels threaten to inundate India’s coastal zones and resources, potentially leaving millions impoverished and displaced. India is set to be among the countries severely impacted by climate change and rising sea levels. Fortunately, India has an adaptation strategy that could mitigate some of these effects and help prolong its resilience. This strategy integrates the tools available through its coastal law, hard and soft engineering measures, and nature based adaptations. Additionally, India relies on Integrated Coastal Zone Management. This paper explores the challenges of rising seas and India’s responses to them. The primary argument is that the absence of coherent policies and laws integrating adaptation actions into a unified framework leads to suboptimal use of limited resources, frequently resulting in significant environmental issues, maladaptation and unsustainabilit
Investigating the influence of AI in social media governance
No full textWith advancement of technological tools, the role of Artificial Intelligence (AI) in maintaining and improving social media platforms is becoming intriguing by each passing day. From content moderation to sentiment analyzing the AI tools are integrated in the day-to-day operations of social media platforms to curate the customized experience to enhance the users' interaction on the platforms. The chapter explores the various AI tools and software understanding their models and functioning to regulate the social media governance. It aims to investigate the influence of AI tools from content creation, marketing advertisements to impact on users' behavior. While discussing the positives of the AI involvement, the chapter also discusses the possible challenges of maintaining user privacy, data security and regulation of fake news. Understanding the role of collaborating governance, the author analyzed various statutes around the world to deal with ethical and legal implications of the AI in social media governance to suggest amicable solutions and way forward
Legal frameworks surrounding the use of AI in online content moderation
No full textThe use of AI in online content moderation is a complex issue with significant ethical and legal implications. While AI offers the potential to efficiently identify and remove harmful content like hate speech and misinformation, it also raises concerns about censorship, biased algorithms, and the erosion of user trust. Striking a balance between free speech and user safety is crucial. Ethical frameworks and regulations are needed to guide the development and deployment of AI moderation tools, ensuring transparency, accountability, and fairness. However, the lack of global consensus and inconsistencies in national regulations hinder the development of a coherent international approach to AI governance. To address these challenges, this chapter will explore the legal framework and a global approach which is needed to establish standards for transparency, accountability, and fairness in AI-driven content moderation, ensuring that AI serves as a tool for good rather than harm