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Local self-government in India: A critical analysis through the lens of democratic decentralization
Local Self-Government (LSG) existed in a variety of forms throughout India. LSG was seen as an effective form of day-to-day management and administration in rural areas in India. This ensured a democratic form of administration even during the time of monarchs. Although it had a setback during the Muslim and British rulers period, it continued to exist. Gandhi raised his voice for increased decentralization and self-rule of the villages. Although the Constitution did not provide such an option, many committees opined that the local governance should be entrusted to the local people. Accordingly, LSG got constitutional recognition through the 73rd and 74th Amendments in 1992. It provided a three-tier system of governance at the regional level as well. Using analytical and critical lenses, this chapter examines the functioning of the constitutionally established LSG model through the lens of democratic decentralization to expose how far it has achieved its objective. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Persons With Disabilities: A Critical Analysis of India's Right-Based Approach
Disability is a challenging issue across the globe, as almost 16% of the global population has some kind of disability. India, the most populous country in the world, also faces the severity of disability issues as 2.2% of its population belongs to that group. For a good period, Indian society considered disability as a curse in the context of karma theory. Accordingly, the disabled faced discrimination, marginalization, and social exclusion. Though the Constitution guaranteed equal rights, India's approach towards disabled was mostly based on charitable contributions for their rehabilitation rather than a rights-based approach. But in line with the paradigm shift in the global approach, the Indian perspective also changed, underlining the rights of the disabled. Many policies were designed to give them access to the mainstream of the society, but India lacks adequate strategies for implementing these policies. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Well- being and Happiness in the Garment Industrial Sector in Bangalore: A Qualitative Study
Well- being and happiness are essential attributes for a meaningful life. Well- being is the sum total of all positive emotions and satisfactions, whereas happiness is an emotional expression of a pleasant mental state. Well- being and happiness depend on many factors like education, skills, working space, interpersonal relationships, and family interactions. This chapter critically analyzes the parameters of well- being and happiness among the garment industrial workers in Bangalore Urban. Bangalore is the garment capital of India, which has many garment units and employs almost 0.3- 0.5 million people. Most of them are women and less educated, and come under the category of unorganized workers. The chapter follows the unstructured interview method of qualitative methodology for exploring the experiences of garment industry workers in relation to their well- being and happiness. Based on their narratives, the chapter enlists the drawbacks in the sector and gives specific policy guidelines to ensure their well- being and better productivity. 2025 by IGI Global Scientific Publishing. -
Green industrialization for the sustainable future of developing countries: A critical study
The 2015 United Nations conference on sustainable development advanced seventeen Sustainable Development Goals (SDGs) that are essential for a sustainable future. Most of these goals either directly or indirectly affirm the importance of environmental protection. They also emphasize the need for social and economic sustainability. The various UN conferences stated that sustainable development has three essential elements such as economic, social and environmental sustainability and they are interconnected. Economic sustainability is achievable only through economic growth and the developed counties are in that high position. But the developing countries are still trying to make a potential stand. In the absence of economic growth, social inequalities are predominant in the Global South. Besides, they also face severe environmental insecurities. In order to achieve all these essentials, green industrialization was suggested. In this perspective, this chapter critically analyzes the feasibility of green industrialization to achieve sustainable future for the developing countries. 2025, IGI Global Scientific Publishing. All rights reserved. -
Human-AI collaborative intelligence: Ethical and legal considerations
The present globe benefits from the unprecedented growth of science and technology. The invention of Artificial Intelligence (AI) has opened a vast horizon of possibilities, choices, and capabilities for humans and society. AI-powered human-like systems provide substantial interaction and collaboration for better results in many fields. The speed, efficiency, and effectiveness of AI systems prompted almost all sectors, like healthcare, education, transport, and communication to invest in them. This resulted in shifting attention from human-human collective intelligence to human-AI collaborative intelligence. This shift has significantly contributed to many fields and reduces the security risks to humans. However, there are also many ethical and legal concerns in this innovative area, like data privacy, transparency issues, liability, and accountability. This chapter, using analytical and critical methods, examines the functioning of collaborative intelligence and suggests the required ethical and legal principles for incorporation into national and international policy design. 2025, IGI Global Scientific Publishing. -
Expansion of BRICS Countries Stimulating Multipolar World Order: A Critical Study in the Context of Russia-Ukraine Crisis
The 21st century formation of BRICs grouping, consisting of Brazil, Russia, India, and China, provided a platform for emerging economies to collectively work for the required position in international scenario. With the two expansions in 2011 and 2023 more developing countries became its members. Such a coalition devised a strategical move from unipolarity to multipolarity in global order. However, no proper attention is given to this grouping considering it as a "loose association. " The main objective of this chapter is thus to explore the evolution of BRICS+ countries, its various interactions within the group and with other international bodies, and its role in the context of conflicts of interests and Russia-Ukraine Crisis. Using doctrinal methodology's analytical and critical methods, the chapter explains the significance of this grouping. The study finds that BRICS+ is an effective body for the Global South in order to make a strong stance in the global scenario. 2025, IGI Global Scientific Publishing. All rights reserved. -
Democracy in the age of AI: Ethical and legal considerations
Democracy is an age-old idea. Although it originated in Ancient Greek Polis Athens, it took almost 20 centuries to become a globally preferred political system of governance. In the aftermath of the Second World War, many countries became independent and democratic affirming the role and strength of people in the governance of country. Democracy revolves around the values like human rights, free choice, freedom, equality, and decision-making. However, with the latest technological advancements in the area of artificial intelligence (AI), there are serious concerns with regard to the smooth functioning of democracy as many biased involvements are officially reported. The virtual world and AI systems are used for targeting the efficiency of democracy. The chapter, in this perspective, critically examines the role of AI in democracy and enlists certain ethical values and legal principles for AI's effective incorporation into the dynamics of politics and democracy. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Cybercrimes in Bharatiya Nyaya Sanhita: A Critical Study on Indian Legal Scenario
Cybersecurity is a significant concern in the present digital world. The increase in cybercrimes attracts attention of the whole globe. India is one of the top countries on the list of cybercrimes and cyberattacks. More than 1 billion people use smartphones in India and the focus on digital economy has also attracted many cyberattacks. This necessitates the need for a specific legal framework. Indias Penal Code was almost 160 years old, and its provisions were not adequate to address the growing nature of cybercrime. Though the provisions of Information Technology Act, 2000 can be applied, India needed a criminal code addressing the latest trends of crimes. Many considered that the enactment of Bharatiya Nyaya Sanhita (BNS) will provide this required framework. In making a critical analysis the chapter tries to evaluate the provisions of BNS to examine whether it provided due protection to Indias cyberspace. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Globalization, Transnational Actors, and Questions on State Sovereignty: Prospects and Challenges
The two consecutive world wars and the subsequent economic recession significantly challenged the global socioeconomic and political landscape. The postwar society thus concentrated on improving economic growth. To energize this inspirational project, the globe promoted the widespread development of transnational actors. They include international institutions such as the UN, multinational and transnational corporations, Nongovernmental Organizations, and private actors. They are supposed to prioritize human rights, human security, and sustainable development. However, experiences affirm that they prioritize profit over protection and personal gains over sustainability. Furthermore, the unnecessary involvement of international organizations and corporations from developed countries in the affairs of developing countries creates complications and confusion regarding state sovereignty. From this perspective, this chapter uses qualitative methodology's analytical and critical methods to examine and evaluate the impact of globalization and transnational actors on state sovereignty. 2026 by IGI Global Scientific Publishing. All rights reserved. -
A novel discrete slash family of distributions with application to epidemiology informatics data
This study puts forward a new class of discrete distribution that can be used by the epidemiologists and medical scientists to model data relating to epidemiology informatics. The proposed distribution is superior to traditional discrete modeling alternatives, viz., discrete Weibull and geometric distributions in terms of its model fit and flexibility to handle heavy-tailed dataset. It is a flexible three-parameter discrete distribution, grounded in the slash family and can be considered as a refined extension to the geometric distribution. We explored the diverse properties of this novel distribution thoroughly by evaluating the mathematical properties. The models parameters are estimated using the maximum likelihood estimation method, where the methodology validity is confirmed through an extensive simulation study. Furthermore, the practical utility of the distribution to model epidemiology informatics was examined with the help of eight different datasets representing three different dimensions of the epidemiology informatics, viz., mortality, infection and medication statistics. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. -
Revisiting the PushPull Tourist Motivation Model: A Theoretical and Empirical Justification for a ReflectiveFormative Structure
This study introduces a novel reflectiveformative hierarchical model specification for the classic pushpull tourist motivation construct, aligning its measurement with the theoretical distinction between intrinsic push drives and external pull attributes. Unlike the traditional reflective-reflective structuring of tourist motivation we defied the higher order factors (novelty, knowledge and facilities as formative. Using partial least squares structural equation modeling (PLS-SEM) on a purposive sample of 319 international tourists, we empirically validate the reflectiveformative (reflective first-order, formative second-order) model. The reflectiveformative model showed a superior fit and predictive power: it explained substantially more variance in key outcome constructs (social motives (R2 = 53.60) and self-actualization (R2 = 23.10)) than the traditional reflectivereflective specification (social motives (R2 = 49.30) and self-actualization (R2 = 21.70)), which is consistent with best-practice guidelines for theoretically grounded models. In contrast, the incorrectly specified reflectivereflective model showed stronger effects between unrelated constructs, supporting concerns that choosing the wrong type of measurement model can lead to incorrect conclusions. By reconciling the pushpull theory with measurement design, this works main contributions are a theoretically justified reflectiveformative model for tourist motivation, and evidence of its empirical benefits. These findings highlight a methodological innovation in motivation modeling and underscore that modeling pushpull motives formatively yields more accurate insights for theory and practice. 2025 by the authors. -
Alcohol and social drinking norms as a catalyst between tourist motivation and tourist satisfaction
This article aims to understand the influence of alcohol availability, ethnicity, anti-alcohol enforcement at tourist destinations, social norms of drinking among tourists and relationships with tourist motivation and tourist satisfaction. A cross-cultural empirical study was conducted using purposive sampling of 476 tourists with partial least squaresstructural equation modelling (PLS-SEM). The results suggest that tourists perceive social norms of drinking and the availability of alcohol at destinations, when coupled with ethnicity, influence the dynamics of the relationship between tourist motivation and tourist satisfaction. The availability of alcohol at tourist destinations alone does not have any relationship either with tourist motivation or with tourist satisfaction. Based on the findings, tourist service providers and facilitators can design drinkscapes specifically based on tourists ethnic background and social norms of drinking to rejuvenate tourist destinations and make them more attractive and inclusive. As the current research considers the tourists ethnic background from a general perspective, future research may investigate the impact of subcultures to understand how ethnicity effects drinkscapes and tourist behaviours. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Curiosity in calamity: How personal schadenfreude shapes disaster-tourism intentions
Tourism to sites of recent disaster, a form of dark tourism has raised questions about whether visitors are driven by typical travel motivations or by morbid impulses. This study examines how conventional tourist motives and the personality trait of benign schadenfreude (pleasure at others misfortune) jointly influence peoples intentions to visit a recent disaster site. By surveying 438 tourists to Kerala, four months after the July 2024 Wayanad landslides, we measured four common travel motives (novelty seeking, fun/entertainment, knowledge/learning, and relationship bonding) alongside a benign schadenfreude scale and visit intention. Partial least squares structural equation modelling (PLS-SEM) was employed for modeling. The model explained 58.80 percent of the variance in visit intention. Three motives viz., novelty, knowledge, and relationship had significant positive associations with intention, whereas the fun motive showed a negative effect. Schadenfreude emerged as the strongest predictor of disaster-site visit intention. Moreover, schadenfreude significantly moderated the influence of novelty seeking: respondents high in schadenfreude exhibited especially strong curiosity-driven intent to visit. These findings suggest that interest in post-disaster tourism often stems from ordinary travel drivers (curiosity, learning, social bonding), but a disposition to enjoy others misfortune can intensify the appeal when novel experiences are involved. The research highlights the need for ethical considerations to be followed by the destination managers and authorities in managing dark tourism destinations. Key limitations include the use of a cross-sectional data, region-specific sample and the focus on benign dimension (versus malicious) of schadenfreude. Future research should validate these results in other cultural and disaster contexts, establish causal relationships, and examine additional personal factors as well as dimensions of schadenfreude. 2026 Joseph et al. -
Phytochemicals and Biological Activities of Flowers of Hibiscus x rosa-sinensis (Chinese Rose)
The flowers of Hibiscus rosa-sinensis L., are a flowering shrub of Malvaceae family. The plant is commonly known as a Chinese rose or shoe flower. The plant is distributed in the tropical and sub-tropical regions of the world and crossing has led to a large number of cultivars with varying patterns in size, shape, and colour. This chapter provides a comprehensive analysis of the distribution, traditional uses, phytochemical composition, and diverse biological activities associated with the flowers of this ornamental plant. The flowers have played a significant role in various traditions, as a remedy for various ailments and as a source of food. A rich profile of bioactive compounds was observed during phytochemical phytochemical investigations. These bioactive compounds included anthocyanins, flavonols, flavan-3-ols, flavanonols, flavanone, flavones, other phenolic compounds, essential oil, etc. which contributed to the medicinal properties of the flowers. The flower extracts demonstrated various biological activities like Hypolipidemic, Cardioprotective, Hypotensive, Anticancer, Antidiabetic, Cytotoxicity, Antimutagenic, Larvicidal, Anti-inflammatory, Anticonvulsive, Wound Healing, Hepatoprotective, Antioxidant, Antimicrobial, Antifertility, Antispermatogenic, antipyretic among other activities. This chapter bridges ethnopharmacological knowledge with scientific research, showcasing the potential of H. rosa-sinensis flowers in the development of novel therapeutic drugs as well as natural product development. 2026 Hosakatte Niranjana Murthy. -
Development of Green Synthesized Novel Carbon Dots from Ruta Graveolens L. for Fluorescent and Intracellular Sensing of Mercury Ions in Pico-molar (pm) Concentration
Green nanotechnology, which uses carbon nanomaterials for environmental remediation, is the pioneer among the prevailing approaches for the production and characterization. In the present study, highly fluorescent carbon dots (CDs) from Ruta Graveolens (ARH-CD) is developed, and its efficacy as a fluorescent sensor and biomarker is investigated. They act as a fluorescence sensor for Hg2+ over an extensive concentration range of 1 picomolar (pm) to 1 molar (m), with a detection limit as low as 26.75 pm. The studies reveal ARH-CD as an effective biomarker for intracellular toxicity analysis and a fluorescent probe for multi-colored (blue, green, and red) imaging of HEK293 cell lines. After 24 h of incubation, it is found that the ARH material reveals noticeable biocompatibility and visible fluorescence, with a viability of 98.88% at 5 gmL?1 and over 78.33% even at a concentration of 100 gmL?1. The IC50 value for the MTT assay for cell viability results is calculated to be 224.56 4.67 g, which further confirms the appreciable biocompatibility of the ARH-CD. The obtained samples are effective in being inspected for the intracellular detection of Hg2+ and serve as a possible candidate for cell imaging. 2024 Wiley-VCH GmbH. -
Hijab row verdict in India: A sentimental analysis of user responses on Facebook
The hijab controversy, a hot topic in India since January 2022, emerged from a clash between students and college authorities in Karnataka, a state in India. The dispute made its way to Karnatakas High Court, which, on 15 March 2022, ruled that the hijab was not mandatory for religious practices. This decision stirred widespread debates, especially on social media platforms like Facebook. This study is focused on user reactions in The Times of India Dailys official Facebook page, employing sentiment analysis to decipher public emotions, attitudes, and opinions. Nearly 200 comments posted on the verdict day were analyzed, utilizing the routine activity theory (RAT), spiral of silence theory, and online disinhibition effect. The research introduced a unique model, RAT+A, to enhance analysis. As a significant platform for public discourse, Facebook played a crucial role in capturing diverse societal sentiments and reactions regarding this social issue. 2025, First Monday. All rights reserved. -
UVIT data release version 7: Regenerated high-level UVIT data products
Ultra-Violet Imaging Telescope (UVIT) on board AstroSat is an active telescope capable of high-resolution far-ultraviolet imaging (<1.5??) and low-resolution (?/???100) slitless spectroscopy with a field-of-view as large as ? 0.5?. Now almost a decade old, UVIT continues to be operational and generates valuable data for the scientific community. UVIT is also capable of near-ultraviolet imaging (<1.5??); however, the near-ultraviolet channel stopped working in August 2018 after providing data for nearly 3years. This paper gives an overview of the latest version (7.0.1) of the UVIT pipeline and UVIT data release version 7. The high-level products generated using pipeline versions having a major ver. no. 7 will be called UVIT data release version 7. The latest pipeline version overcomes two limitations of the previous version (6.3), namely: (a) inability to combine all episode-wise images; and (b) failure of the astrometry module in a large fraction of the observations. The procedures adopted to overcome these two limitations as well as a comparison of the performance of this new version over the previous one, are presented in this paper. The UVIT data release version 7 products are available at the Indian Space Science Data Center of the Indian Space Research Organization for archival and dissemination from 1 June 2024. New pipeline version is open source and made available on GitHub. Indian Academy of Sciences 2025. -
JivaCare: A Smart Health Care Application Integrating Home Remedies for Holistic Well-Being
JivaCare is a smart health care application that aims to diagnose common illnesses and recommend home remedies by leveraging advancements in Artificial Intelligence (AI) and Machine Learning (ML). Initially, a custom dataset of diseases and symptoms was used to develop a disease-diagnoses chatbot. However, challenges such as limited accuracy and rigid disease-symptom mapping were identified. To address these, GPT-3.5 API was integrated via RapidAPI, enhancing conversational quality without requiring extensive training while improving response quality. A MySQL database was implemented to store conversational history and session-based memory. Subsequently, the focus transitioned to a text classification approach using a 5,634-sample dataset from HuggingFace. This enabled flexible symptom-to-disease classification, overcoming the limitations of the initial dataset. Five machine learning models were evaluated, with Logistic Regression achieving the highest accuracie of 85 % after fine-tuning its hyperparameters. Additionally, neural network architectures such as GRU, RNN and CNN were also employed, achieving validation accuracies of 76%, 82% and 84%, respectively. The results demonstrate the effectiveness of integrating ML and deep learning techniques for accurate disease prediction and remedy recommendation. This work can establish the foundation for a scalable and user-friendly healthcare system, bridging the gap between AI and personalised natural health benefits. 2025 IEEE. -
JivaCare: A Smart Health Care Application Integrating Home Remedies for Holistic Well-Being
JivaCare is a smart health care application that aims to diagnose common illnesses and recommend home remedies by leveraging advancements in Artificial Intelligence (AI) and Machine Learning (ML). Initially, a custom dataset of diseases and symptoms was used to develop a disease-diagnoses chatbot. However, challenges such as limited accuracy and rigid disease-symptom mapping were identified. To address these, GPT-3.5 API was integrated via RapidAPI, enhancing conversational quality without requiring extensive training while improving response quality. A MySQL database was implemented to store conversational history and session-based memory. Subsequently, the focus transitioned to a text classification approach using a 5,634-sample dataset from HuggingFace. This enabled flexible symptom-to-disease classification, overcoming the limitations of the initial dataset. Five machine learning models were evaluated, with Logistic Regression achieving the highest accuracie of 85 % after fine-tuning its hyperparameters. Additionally, neural network architectures such as GRU, RNN and CNN were also employed, achieving validation accuracies of 76%, 82% and 84%, respectively. The results demonstrate the effectiveness of integrating ML and deep learning techniques for accurate disease prediction and remedy recommendation. This work can establish the foundation for a scalable and user-friendly healthcare system, bridging the gap between AI and personalised natural health benefits. 2025 IEEE. -
Predicting Stock Market Trends: Machine Learning Approaches of a Possible Uptrend or Downtrend
This paper delves into a statistical analysis of the stock market, emphasizing the significance of accuracy in stock predictions. Large data sets can be handled by machine learning algorithms, which can also forecast outcomes based on past data and spot intricate patterns in financial data. They assist control risks, automate decision-making procedures, and adjust to changing circumstances. Multi-source data can be combined by ML models to provide a comprehensive picture of market circumstances. They can manage intricate, nonlinear interactions, provide impartial analysis, and lessen human bias. Models are able to adjust to shifting market conditions through ongoing learning and retraining. They must, however, exercise caution when deploying models in real-world situations and ensure that they are validated. Although machine learning has advantages for stock market analysis, it must be carefully evaluated for dangers and validated before being used in practical situations. The traditional machine learning model, Logistic Regression has been used in order to predict stock prices. It focuses on binary classification based on the trend of the stock. Through the model training and evaluation and additional analysis done on the results, this research contributes towards obtaining predictions and studying reasons of a possible uptrend or downtrend to further assist companies. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.