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A qualitative exploration of mental health experiences among IBDP students
The burgeoning concern surrounding mental health has become a prevailing issue. Considering the education sector, cut-throat competition among students has led them to experience concerns with their mental health. Although ample research exists on mental health awareness, escalating academic competition has impacted the holistic well-being of students. Research elucidates that the education sector beckons urgent attention to address the emerging mental health needs of the high school students. Thus, this study aims to probe the specific mental health requirements of students enrolled in the International Baccalaureate Diploma Program (IBDP) in Jaipur, Rajasthan. Conducted using a qualitative research paradigm, this study entailed in-depth interviews of 25 IBDP students. Subsequently, a thematic content analysis was deployed to interpret the emerging themes from the data gathered. The findings illustrated numerous themes such as mental health concerns, self-management, professional development, and other related themes discussed in the paper. This research seeks to enhance the awareness of the IBDP community regarding the mental health challenges experienced by the students. Additionally, it serves as an essential resource for educators, parents and students themselves, empowering them to acknowledge and address these challenges effectively. Furthermore, the results from this study can be utilized to develop a mental health framework tailor made to the needs of IBDP students. The Author(s) 2026. -
Indias credit growth and asset prices movements; Does the global financial cycle have a moderating role to play?; [Evoluci del crecimiento del crito y de los precios de los activos en la India; Desempe el ciclo financiero mundial un papel moderador?]
This study examines the effect of the global financial cycle on different financial indicators of the Indian economy through experimental analysis. It detects evidence of a connection between contemporaneous changes in capital flows, asset prices, and credit growth, which are related to the Global Financial Cycle (GFCy). The evolution of the cycle is largely driven by the monetary policy decisions of the Federal Reserve, and existing studies have examined the influence of these decisions in different contexts. The current study experimentally examines the effect of the global financial cycle on credit growth and asset prices in India during the period 2010-2023. For the purpose of achieving its goals, the study utilizes advanced time-series econometric techniques, such as the Granger Causality Test, Vector Autoregression (VAR) methodology, and the Impulse Response Function (IRF) test. The outcomes show that the global financial cycle has significant effects on the stock market, as confirmed by the Granger causality and IRF findings. 2019 Universidad Nacional Automa de Mico, Facultad de Contadur y Administraci. This is an open access article under the CC BY-NC-SA (https://creativecommons.org/licenses/by-nc-sa/4.0/) -
Global Financial Cycle and Its Determinants: A VECM Approach
The determinants of the global financial cycle are empirically investigated in this study report. The presence of concurrent changes in capital flows, asset prices, and global bank leverage is associated with the Global Financial Cycle (GFCy). According to the research now in publication, the Chicago Board of Exchange's VIX (Volatility Index), which gauges market uncertainty and risk aversion, indicates this cycle. The Federal Reserve's monetary policy decisions are the driving force behind this cycle, and the literature already in existence has examined the ramifications of these decisions. The GFCy and, thus, the financial circumstances of emerging market economies (EMEs) could be impacted by additional global shocks. Other global shocks have the potential to impact the global financial cycle and analysis of the same is required to make the existing literature more robust. Our analysis, which includes a study of identifying the potential global shocks for a period of 23 years data (quarterly), indicates that the global financial cycle is driven by global liquidity and global economic policy uncertainty. VECM, Granger Causality, Impulse Response functions were applied. There is a unidirectional causal relationship between the global financial cycle and global liquidity, as well as a unidirectional relationship between the global financial cycle and global economic policy uncertainty. 2025, Iquz Galaxy Publisher. All rights reserved. -
AI-Driven Credit Assessment in Banks and Non-Banking Finance Companies (NBFCs) in India: A Comprehensive Analysis
This study examines the application of AI frameworks in real- world scenarios, including regulatory compliance, fraud detection, credit scoring, default prediction, and portfolio management (Moscato et al., 2020). By leveraging AI to gain deeper insights into borrower creditworthiness, financial institutions can enhance decision- making, streamline processes, and foster a more stable financial environment. However, alongside its transformative potential, the implementation of AI presents significant challenges. Ensuring data quality, improving model interpretability, adhering to regulatory compliance, and addressing ethical considerations are crucial to achieving fair and unbiased outcomes. This paper highlights both the opportunities and complexities associated with integrating AI into financial systems, emphasizing the need for balanced and responsible adoption. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Managing Climate Risk in Indian Banking: Regulatory Shifts and Institutional Responses
Climate change is widely discussed as a prominent risk aspect which can pose financial risks to financial entities. The risks may range from physical risks and transition risks and impact can be evident across all the global economies. In India, the banking sector is the most important component of its financial system and is entrusted with managing various financial risks and mobilizing funds for sustainable development. The timely guidance of the Reserve Bank of India (the apex regulatory body) has made Indian Banks factor in climate risk factor into their internal control, risk assessment and disclosure processes. This chapter examines the changing role of risk management practices in Indian Banking Sector, where climate change also has a key role now. This study also focusses on new policies, practices and response of individual banks. The large banks of India have set a path of climate risk management by starting a separate ESG and Climate Finance Unit, laying down an ESG financing framework, and adding climate scenario analysis in its risk assessment. Banks such as HDFC Bank, Yes Bank, Kotak Mahindra Bank, and Federal Bank have also advanced through financed emissions reporting, net-zero commitments, climate stress tests, and coal policy exclusions. In spite of these steps, the overall preparedness of the Indian banking sector is still limited, with most institutions still in the process of defining climate risk strategies. The key issues are availability of data, absence of uniform ESG metrics, and dearth of internal expertise. Institutional responses are compared and explained in this chapter and policy gaps that must be addressed in the short run. Through the presentation of regulatory changes and best practices, it emphasizes the importance of Indian banks moving away from reaction-driven risk management to proactive climate leadership and thus contributing to Indias larger environmental and economic objectives. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Effect of Microbial Consortium on Biodegradation Process of Organic Waste Materials
Solid waste generation has significantly increased in tandem with population growth, presenting substantial challenges to human health and environmental sustainability. In developing nations such as India, traditional management practices, including incineration and open dumping, continue to prevail despite their detrimental environmental effects. There is a paucity of research focusing on microbial consortia specifically engineered for the accelerated biodegradation of heterogeneous organic waste under local conditions. This study addressed the microbial consortium isolated from waste-associated environments enhancing the rate of organic waste degradation and effect of consortium for improving compost nutrient quality compared to natural decomposition. Microbial strains were isolated from a soil sample obtained from a vegetable and fruit waste disposal site in Bengaluru, Karnataka, India. Among the 50 isolates, five exhibiting strong hydrolytic activity were selected and identified through 16S rRNA sequencing as Cronobacter sakazakii LMSC, Stutzerimonas xanthomarina LMSA, Cronobacter sakazakii LMSPR, Pseudomonas pseudoalcaligenes LMSPE, and Staphylococcus sp. LMSL. A consortium was prepared by inoculating equal proportions of each culture, incubating for 48 hours, and applied it to waste degradation. During composting, temperature (2832 C), pH (neutral to alkaline), and moisture (68.44% in treated vs. 18% in control) were monitored. Nutrient analysis revealed higher values in the treated compost compared to the controls, contributing to enhanced soil quality and plant growth. The novelty of this study resides in the formulation of a native microbial consortium from waste-associated bacteria, which demonstrated superior biodegradation efficiency and compost quality compared to natural decomposition. 2026 Widener University School of Civil Engineering. All rights reserved. -
Emotional Abuse and the Pandemic in India: Implications for Policy, Research, and Practice
During the COVID-19 outbreak, cases of violence and abuse have increased significantly around the world, necessitating a reevaluation of our relation-ships. Both violence and abuse seek to control and instill fear in the individ-ual, gradually disrupting their overall well-being. Emotional abuse does not receive the same level of attention and social response as other forms of abuse due to its subtle nature. Its effects are as harmful as physical and sexual abuse, with serious consequences for the mental health of individual and their families. The COVID-19 pandemic has brought to light the importance of mental health. With the imposition of lockdown in India, the number of helplines for domestic violence and abuse has skyrocketed. Abuse experien-ces can be seen to be bidirectional; women are not alone in such instances. Many cases, however, go unreported and never reach formal institutions. The National Family Health Survey (2019-2021) reveals the current state of Indian health and nutrition, but emotional abuse (also referred to inter-changeably in this article as emotional violence) only includes responses from women and is no longer included under spousal violence in the most recent edition. This article also includes recommendations and attempts to highlight existing shortcomings in addressing the issue of emotional violence. The articles cited in this article were obtained from electronic databases. Other secondary data sources mentioned include newspaper articles, magazines, census reports, and periodicals. 2024 Springer Publishing Company. -
Separated/Divorced Individuals Experiences with the Legal System in India: A Qualitative Inquiry
This study identifies systemic flaws and biases in the Indian judicial system, highlighting areas for reform. Through purposive sampling, 15 separated/divorced participants (nine male, six female) were analyzed via semi-structured interviews and Interpretative Phenomenological Analysis (IPA) using Atlas.ti 23 software. Analysis derived one group experiential theme: Judicial Process and Law Enforcement, with four sub-themes: The Contradictory Positions of the Court, Nonchalance toward False Accusations, Encounter with Legal Professionals, and Two Sides of Law Enforcement. Participants revealed conflicting experiences, with few achieving justice while others faced substantial delays. Male participants often encountered allegations without evidence. Regardless of gender, feelings of distress and helplessness were prevalent due to court procedures. The findings highlight the urgent need for reforms like procedural transparency to mitigate the trauma of divorce in India and emphasize a gap in existing literature on judicial effects in separation cases. Recommendations for future research are suggested. 2025 Taylor & Francis Group, LLC. -
Predictive Analysis of Sleep Disorders Using Machine Learning: A Comprehensive Analysis
The diagnosis of sleep disorders often relies on subjective patient reports, sleep diaries, and potentially cumbersome polysomnography (PSG) tests. However, these methods have limitations such as subjectivity, sleep diaries require meticulous effort, and expensive PSG tests are expensive, resource-intensive, and may not accurately capture sleep patterns in a non-clinical setting. Sleep disorders pose significant health risks and can impair overall well-being. Predictive analysis plays a crucial role in identifying individuals at risk of developing sleep disorders, enabling timely interventions and personalized treatment plans. In this paper, a comparative analysis of regression and classification models for sleep disorders prediction using machine learning (ML) techniques on insomnia and sleep apnea are discussed. Through extensive experimentation and comparative analysis, XGBoost and AdaBoost demonstrated as the most effective predictive models for insomnia and sleep apnea. AdaBoost and XGBoost classifiers are displaying 93.49% and 92.73% respectively. It is therefore possible to draw the conclusion that AdaBoost and XGBoost are doing well based on the findings as a whole, as indicated by the results. Our findings contribute to advancing the understanding and application of ML techniques in sleep disorder prediction, paving the way for more accurate and timely diagnosis based on ML techniques and personalized interventions in clinical practices. 2024 IEEE. -
Enhancing Security and Resource Optimization in IoT Applications with Blockchain Inclusion
The rapid proliferation of Internet of Things (IoT) devices has ushered in a new era of connectivity and data-driven applications. However, optimizing the allocation of resources within IoT networks is a pressing challenge. This research explores a novel approach to resource optimization, combining blockchain technology with enhanced security measures, while addressing the critical concerns of time and energy consumption. In this study, we propose a resource allocation framework that leverages the transparency and immutability of blockchain to enhance data integrity and security in IoT applications. The blockchain-based method is utilized to identify the malicious users in the IoT applications. The proposed method is implemented in MATLAB and performance is evaluated by performance metrics such as the probability of detection, false alarm probability, average network throughput, and energy efficiency. The proposed method is compared by existing methods such as Friend or Foe and Tidal Trust Algorithm. To further optimize this process, we introduce a Hybrid Artificial Bee Colony-Whale Optimization Algorithm (ABC-WOA), a powerful optimization technique designed to minimize time delays and energy consumption in IoT environments. Our findings demonstrate the effectiveness of the proposed approach in achieving resource efficiency, reducing time and conserving energy within IoT networks. 2023 IEEE. -
STOCHASTIC BEHAVIOUR OF AN ELECTRONIC SYSTEM SUBJECT TO MACHINE AND OPERATOR FAILURE
A stochastic model is developed by assuming the human (operator) redundancy in cold standby. For constructing this model, one unit is taken as electronic system which consists of hardware and software components and another unit is operator (human being). The system can be failed due to hardware failure, software failure and human failure. The failed hardware component goes under repair immediately and software goes for upgradation. The operator is subjected to failure during the manual operation. There are two separate service facilities in which one repairs/upgrades the hardware/software component of the electronic system and other gives the treatment to operator. The failure rates of components and operator are considered as constant. The repair rates of hardware/software components and human treatment rate follow arbitrary distributions with different pdfs. The state transition diagram and transition probabilities of the model are constructed by using the concepts of semi-Markov process (SMP) and regenerative point technique (RPT). These same concepts have been used for deriving the expressions (in steady state) for reliability measures or indices. The behavior of some important measures has been shown graphically by taking the particular values of the parameters. 2024, Gnedenko Forum. All rights reserved. -
Crossing Worlds and Resisting Power: Fantasy and Metaphorical Borders in Srivatsa and Karunatilaka
The act of crossing and navigating physical, cultural, and symbolic borders has a profound impact on the shaping of identities, with a focus on the dynamics of resistance and power. By analyzing, through the lens of Critical Discourse Analysis (CDA), the experiences of characters portrayed in select Fantasy Fiction [The Spice Gate by Prashanth Srivatsa (2024); and The Seven Moons of Maali Almeida by Shehan Karunatilaka (2022)] in navigating borders-whether literal or metaphorical-the chapter studies how these crossings challenge fixed notions of identity and belonging. The protagonists of the chosen Fantasy works stem from both highly marginalized communities: the lower castes in India, and the more universally discriminated LGBTQIA+ people. Drawing on interdisciplinary perspectives pertaining to gender, sexuality, caste, oppression, and resistance, the chapter examines the act of border-crossing to illuminate the interplay between Self and Other, belonging and alienation, while confronting structures of power and oppression. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Exploring Music, Art, and Literature in Conflict Narratives Using Fantasy Fiction: War Through a Cultural Lens
The study of war has long been confined to disciplines such as history, political science, and journalism. However, with the evolution of modern conflicts and the shifting global landscape, it is imperative that scholars also explore more unconventional or often overlooked mediums, including literature, art, and music-not just to study how civilians respond to war and the trauma it leads to, but also the intricacies of war itself. This study examines war and conflict narratives through a cultural lens, using Critical Discourse Analysis of Letters of Enchantment (2023), a fantasy duology by Rebecca Ross. Fantasy fiction, once perceived as an escapist genre, has recently developed into a medium capable of exploring serious sociopolitical themes, including warfare, propaganda, and trauma. This study explores the ways in which the duology portrays war through themes of media influence, artistic expression, censorship, and music suppression, drawing parallels with real-world historical and contemporary conflicts. 2026, IGI Global Scientific Publishing. All rights reserved. -
A cyber-physical systems and the smart city vision: A comprehensive guide
The process of urban areas' transformation into smart cities with the help of Smart Cyber-Physical Systems (SCPS) is one of the most defining trends of modern urbanism. It requires a multifaceted perspective of smart cities, thereby evaluating the facets of SCPS intently concerning the complexities of their integration in urban structures while exploring their influence that transcends the domains of social sciences and economics, which has become crucial. In this context, smart cities are constructed as integrated systems at the crossroads of the digital and the physical: they sustain, facilitate, and improve the performance of the city's functions and living environment. The importance of technological environments in orientation and close consideration of SCPS reveals the functions in gathering data, immediate analysis, and decision-making processes of urban management. The interconnection of the Internet of Things (IoT), artificial intelligence (AI), and big data analytics considering their impact and the creation of sustainable enhancing the quality of public services. 2026 by IGI Global Scientific Publishing. All rights reserved. -
A cyber-physical systems and the smart city vision: A comprehensive guide
The process of urban areas' transformation into smart cities with the help of smart cyber-physical systems (SCPS) is one of the most defining trends of modern urbanism. It requires a multifaceted perspective of smart cities, thereby evaluating the facets of SCPS intently concerning the complexities of their integration in urban structures while exploring their influence that transcends the domains of social sciences and economics, which has become crucial. In this context, smart cities are constructed as integrated systems at the crossroads of the digital and the physical: they sustain, facilitate, and improve the performance of the city's functions and living environment. The importance of technological environments in orientation and close consideration of SCPS reveals the functions in gathering data, immediate analysis, and decision-making processes of urban management. 2025, IGI Global Scientific Publishing. -
From Belief to Bandwidth: Navigating Freedom of Religion or Belief in the Age of Algorithms
As our lives become increasingly intertwined with digital technology and way people experience and express religion is also continuously evolving. This one chapter explores how idea of FoRB is evolving in digital world over course of time, where smartphones, social media, algorithms have become everyday tools for faith, connection, control. While digital spaces can open up new opportunities for interfaith dialogue, spiritual exploration, community- building, they can also pose serious risks. Issues like online hate speech, digital surveillance, content moderation, algorithmic bias often challenge free expression of belief. This chapter will have a closer look at how FoRB operates in online environments by combining insights from international human rights law, digital sociology, case studies from around world. We here focus on examining how free belief truly is in age of internet, considering what it takes to protect that freedom when technology both connects and controls. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Blockchain-based node authentication algorithm for securing electronic health record data transmission
The advent of Internet of Things (IoT) technologies in healthcare has heightened risks to Electronic Health Records (EHRs), including authentication vulnerabilities and data privacy concerns. This study proposes a novel blockchain-based node authentication algorithm for IoT healthcare, integrating Hyperledger Fabric, Homomorphic Encryption, and Recurrent Neural Networks (RNN). Employing a dual-layer security approach, the methodology utilizes a challenge-response mechanism and dynamic key exchange to ensure tamper-proof data transmission. Encrypted processing preserves confidentiality, while machine learning enhances anomaly detection accuracy to 99.01%, achieving a security rate of 99%. Comprehensive evaluations demonstrate significant improvements in efficiency, scalability, and robustness, addressing latency and computational overhead challenges. By fusing blockchains immutability with intelligent encryption and authentication, this solution revolutionizes EHR protection in IoT environments and scalable healthcare data management. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025. -
A Novel Blockchain-Integrated Deep Learning Framework for Securing Smart Healthcare Communication Networks
With the rapid expansion of intelligent medical equipment and their interconnectedness through the Internet of Things (IoT), addressing safety issues in the communicating system has become increasingly critical. A learning mechanism is proposed for an intelligent healthcare-based communication system that uses blockchain for secure network communication and incorporates a data evaluation layer based on cloud which actively segregates and ranks transactions into three main categories: Good, Moderate, and Malware. Fog servers are utilized to route the communicating nodes via Rician and Rayleigh channels. The learning mechanism employs a deep neural network to instruct and classify categories, thereby improving the blockchain layer's decision-making process. This paper introduces several significant contributions, such as the development of a secure blockchain framework for user authentication and a protected digital ledger for communication. Additionally, it incorporates a cloud-driven data analysis layer combined with a neural network to improve training accuracy and category classification. The developed algorithm surpassed the existing works in terms of quality of service (QoS) parameters with low latency, bit error rate (BER), higher signal to inference plus noise ratio (SINR), packet delivery ratio (PDR), true detection rate (TDR), false detection rate (FDR), and throughput. Also, a thorough comparison of consensus mechanisms like practical Byzantine fault tolerance (pBFT), proof of work (PoW), Raft, and Paxos is done to ensure which consensus helps optimize the proposed system in terms of security and fault tolerance with low latency and energy-efficient operations. It also establishes a secure and efficient communication network for smart healthcare, aimed at enhancing the overall quality of life for individuals. 2025 Wiley Periodicals 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. -
Localizing and Classifying Kannada Texts Using a YOLO-Based Approach
Extracting handwritten characters from the scanned documents is a critical step due to the inherent complexities of various writing styles, inconsistent alignments, multi-touch scenarios, and overwriting characters. Expanding upon the real-time object detection capabilities of YOLOv8 (You Only Look Once), the current paper presents an experiment utilizing a dataset of 2000 handwritten images. This dataset combines the standard dataset (Chars74K) with the custom dataset featuring multi-touch handwritten text, encompassing both individual characters and character combinations that form words. The annotations were created using the Roboflow application and exported to a yaml (yet another markup language) file. The hybrid dataset was split into training, validation, and testing sets. The evaluation process yielded an accuracy of 96.8% at a threshold of 0.5 for recognizing and classifying the characters. The result suggests a positive correlation between training dataset size and model accuracy. Further, fine-tuning the hyperparameters could increase the accuracy upto 98.4%. Additional experiments were conducted to compare YOLOv8 and Detectron2 with Faster R-CNN. The results demonstrated that YOLOv8 offers substantially faster inference times, while Detectron2 with Faster R-CNN exhibited marginally higher accuracy in few classes. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.