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NEXT-GEN SUSTAINABILITY: ANALYSING ATTITUDES AND ACTIONS OF GEN Z TOWARDS CIRCULAR ECONOMY AND ECO-FRIENDLY PRACTICES
Generation Zs (Gen Z) role in the creation in maintenance of the circular economy is very important, as they have the potential to shape sustainable practices for future generations. This study aims to comprehend Gen Zs role in promoting environmental sustainability within the framework of the circular economy. An explanatory sequential research design has been adopted in order to achieve the objectives of this research article. The researchers have initially collected quantitative data from 941 respondents using a questionnaire. The respondents were selected based on a stratified random sampling approach. Following the quantitative analysis, qualitative data was collected via interviews with 18 Gen Z participants. Based on the quantitative data analysis, the study found that Gen Z exhibits a strong commitment to promoting circular economy. The results of the Structural Equation Modelling (SEM) shows that recycling activity has the highest impact on achieving the principles of circular economy. Based on the qualitative analysis, this study discovered four main themes. The first theme was centred on Awareness of Circular Economy. The second theme explored the Integration of the Circular Economy on Personal Life. The third theme, probed into the Impact of the Circular Economy on Peoples Lives. While the final theme addressed Steps Towards Building an Active Circular Economy. UMT Press -
COVID-19 COMICS AS GRAPHIC NETWORKS OF NON-EMERGENT HEALTHCARE: A MULTIMODAL DISCOURSE ANALYSIS OF PANDEMIC COMICS
COVID-19 comic discourses articulating lived experiences during lockdown, isolation, and quarantine constructed a creative space of self and collective care. This research article explores how the multimodality within COVID-19 comic discourses aids in constructing a networked public of graphic care. Resorting to Dannah Boyds (2008; 2011) methodological framework of networks of graphic care, comics on the themes of self-care, coping mechanisms, and mental well-being from the work COVID Chronicles: A Comics Anthology (Boileau & Johnson, 2021) is analysed. A Multimodal Discourse Analysis (MDA) is performed to decipher the visual and verbal comic devices employed in constructing this graphic network of care using Thierry Groensteen (2007) and Scott McCloud's (2008) comic theories. The analysis highlights the various visual and linguistic techniques that enhance the communicative effectiveness of COVID-19 comics as self-care tools. By intervening in the visuality of COVID-19 comics as a tool of mental healthcare on individual and collective levels, this study illustrates the potential of comic narratives as a sustainable mode of sustenance and care in times of adversity and uncertainty. Furthermore, drawing from the results, the article also proposes the potentiality of comic discourses as non-emergent healthcare tools and a pedagogical tool for the successive policy implementation of mental healthcare measures. Copyright 2025 Albeena Stephen, Reshma Jacob. -
Electromagnetic Radiation-Driven Plastic Degradation and Energy Recovery for Sustainable Waste Management
The persistent accumulation of plastic waste presents a severe global environmental challenge. This study presents a non-thermal photodegradation and energy-recovery system that selectively cleaves 82 5% of CC/CH bonds in polyethene (PE), polypropylene (PP), and polystyrene (PS) within 30 min of UVC (254 nm) exposure. The bond-dissociation energy is harvested via thermoelectric generators (TEGs), delivering 10 W, and via photoelectric cells, yielding 5 W (10 mA.cm- at ? < 2 eV), for a combined recovery of 15 W. Emissions are held below 0.5 ppm VOCs and 0.1 mg.m- microplastics. A lab-scale prototype processes 0.5 kg.h-1 of mixed plastic per 0.1 m reaction area equivalent to 30 Wh.kg-1 of electrical energy and is scalable to 5 kg.h-1 in a pilot module. Real-time FTIR, Raman, and UV-VIS spectroscopy, integrated with an IoT-PID feedback loop, ensures autonomous optimization. Life-cycle assessment indicates a 25% reduction in greenhouse gas emissions compared to conventional recycling methods. A circular-economy framework envisions recovering oligomeric and monomeric fragments for direct reintegration into polymer production. Feature work will implement digital-twin simulations to refine process control, maximize throughput, and ensure long-term system reliability. 2026 by the authors Licensee: Technoscience Publications. -
Land Use/Land Cover (LULC) Change Classification for Change Detection Analysis of Remotely Sensed Data Using Machine Learning-Based Random Forest Classifier
Land Use and Land Cover (LULC) classification is critical for monitoring and managing natural resources and urban development. This study focuses on LULC classification for change detection analysis of remotely sensed data using a machine learning-based Random Forest classifier. The research aims to provide a detailed analysis of LULC changes between 2010 and 2020. The Random Forest classifier is chosen for its robustness and high accuracy in handling complex datasets. The classifier achieved a classification accuracy of 86.56% for the 2010 data and 88.42% for the 2020 data, demonstrating an improvement in classification performance over the decade. The results indicate significant LULC changes, highlighting areas of urban expansion, deforestation, and agricultural transformation. These findings highlight the importance of continuous monitoring and provide valuable insights for policymakers and environmental managers. The study demonstrates the effectiveness of using advanced machine-learning techniques for accurate LULC classification and change detection in remotely sensed data. 2025 by the authors. -
Classification of irreducible Harish-Chandra modules over full toroidal Lie algebras and higher-dimensional Virasoro algebras
In this paper, we classify the irreducible Harish-Chandra modules over the full toroidal Lie algebra, which is a natural higherdimensional analogue of the affine-Virasoro algebra. In particular, we complete the classification of irreducible bounded modules studied by Billig for non-zero level modules [Int. Math. Res. Not. 2006]. As a by-product, we also obtain the classification of irreducible Harish-Chandra modules over the higher-dimensional Virasoro algebra, which was introduced by RaoMoody [Comm. Math. Phys. 1994], thereby generalizing the well-known result of O. Mathieu [Invent. Math. 1992] for the classical Virasoro algebra. More precisely, we show that any irreducible Harish-Chandra module over the higher-dimensional Virasoro algebra turns out to be either a quotient of a module of tensor fields on a torus or a highest weight type module up to a twist of an automorphism, as conjectured by Eswara Rao in 2004. 2025, International Press, Inc. All rights reserved. -
Identification of Dynamics of Tractor Chassis Structure through Ground Vibration Testing
This study investigates the vibrations arising from mass imbalance and variable inertia forces within dynamic systems, specifically focusing on agricultural tractors. Impulse test method is used to determine the modal characteristics of the tractors structure, including its frequencies, damping and mode shapes. The random responses of various components, such as the chassis, bonnet, muffler, seat and axle, were measured at engine speeds of 800, 1500 and 2500 rpm. The results indicate that the vibration amplitude depends on material properties and operational conditions, with the maximum random vibration response observed at the highest engine speed of 2500rpm. The overall root-mean-square acceleration (grms) was used to quantify vibration levels, revealing significant acceleration values of 2-4 grms across the entire tractor structure. Increased vibrations, particularly at high engine speeds, lead to amplified noise, dynamic stresses and accelerated wear on the chassis and subsystems, necessitating periodic maintenance and part replacements. The study also assessed the impact of road and field surface conditions on the vibration levels. The dynamic modes identified provide insights into potential improvements in tractor performance by implementing semiactive or active vibration control mechanisms utilizing smart materials without changing the existing engine dynamics. 2025. Carbon Magics Ltd. -
Investigation of Diesel Engine Performance, Emissions and Combustion Characteristics Utilizing Emulsified Biodiesel at Varied CRs
In this experimental investigation, a varied CR (CR) diesel engine is fuelled with palmyra biodiesel B20 (20% palmyra methyl ester + 80% diesel) and emulsified palmyra biodiesel (85% B20 + 10% water + 5% surfactant), with span 80 and tween 80 (hlb of 6.43) used as surfactants. The study aims to evaluate the performance, emissions and combustion characteristics of the engine at varying CR of 17, 17.5 and 18 with the standard CR set at 17.5. Results show that increasing the CR leads to an improvement in Brake Thermal Efficiency (BTE), with a 3.89% higher BTE observed at a CR of 18 compared to 17. Additionally, higher CRs result in significant reductions in emissions, including hydrocarbons by 25.49%, carbon monoxide by 28.35% and smoke by 11.82% compared to running on neat diesel. These findings highlight the potential of emulsified palmyra biodiesel at higher CRs to improve the engine efficiency and reduce emissions, emphasizing its viability as a sustainable alternative fuel. 2025. Carbon Magics Ltd. -
Mindfulness in treatment-seeking adults with comorbid obsessive-compulsive and major depressive disorders: Mediating effects of obsessive beliefs and mental well-being
Background: Mindfulness-based interventions have shown promise in alleviating symptoms associated with obsessive?compulsive disorder (OCD) and major depressive disorder (MDD). However, the specific mechanisms that drive these effects, mainly through obsessive beliefs and mental well?being, are seldom examined. Aim: To explore the mechanisms by which mindfulness influences symptom severity in adults with comorbid OCD and MDD, focusing on the mediating roles of obsessive beliefs and mental well-being. Methods: Primary data from 60 treatment-seeking adults with comorbid OCD and MDD were analyzed. Ordinary least-squares path analysis was employed to examine the mediating roles of obsessive beliefs and mental well-being in the relationship between mindfulness and the severity of OCD and MDD symptoms. Results: Mindfulness was significantly associated with reduced symptom severity for both OCD (? = ? 0.40, P < 0.001) and MDD (? = ? 0.49, P < 0.001). For MDD, obsessive beliefs (? = ? 0.20, P < 0.001) and mental well?being (? = ? 0.33, P < 0.001) significantly mediated the relationship. In contrast, no significant indirect effects were observed for OCD symptoms through obsessive beliefs (? = ? 0.10, P = 0.16) or mental well?being (? = ? 0.08, P = 0.20). Conclusion: These findings highlight the distinct mechanisms of mindfulness in comorbid OCD and MDD, underscoring the importance of customized interventions based on specific pathways. 2025 Indian Journal of Psychiatry. -
Breaking down Vicarious Trauma: Supporting Trauma Workers Who Work among Survivors of Sex Trafficking in India
Trauma workers who work at the grassroots levels of sex trafficking rehabilitation are face to face with the survivors struggle. Their roles are essential to lay the foundations of recovery and reintegration for the survivors. This article focuses on what vicarious trauma means and how acknowledging its presence as an occupational hazard will help shape organization policies and structures in a way that empowers trauma workers to continue to bring quality work from an intentional, supported, and grounded space. 2025 Indian Journal of Social Psychiatry. -
Adherence to the WHO Guidelines on Suicide Reporting: A Content Analysis from Bengaluru, India
Background: Media, with its power to influence the masses, is found to have an impact on how the readers perceive suicide, and evidence suggest that suicidal behavior is contagious. However, studies have shown that it is possible to intervene by implementing media guidelines for suicide reporting. Unfortunately, the guidelines are mostly not being adhered to by the media. The current study attempts to assess if there has been any change in reporting after the Press Council of India issued guidelines on suicide reporting in 2019. Methodology: Content analysis of the newspaper articles reporting on suicide was done for 3 months (October 1, 2019, to December 31, 2019). Nineteen newspapers published in Bengaluru, Karnataka, were selected for the study based on the language and readership. These included six English, five Kannada, two Malayalam, two Hindi, two Tamil, and two Telugu newspapers. A total of 1198 reports were found and analyzed. Results: The study found that the majority of the reports did not adhere to the guidelines. It was observed that the news reports on suicide mostly resorted to sensationalization. Majority of the reports portrayed suicide in a harmful manner by mentioning the suicide method and the site in detail and focused on monocausal explanations. The significant connection between suicide and mental illness was also overlooked. Conclusion: Irresponsible reporting of suicide creates risks for the public and collaborative efforts should be designed to decrease the negative impact media can have on suicide prevention initiatives. 2025 Indian Journal of Social Psychiatry. -
The Psychosocial Experiences of Family Caregivers of Cancer Patients
Introduction: This study explores the psychosocial experiences of family caregivers of cancer patients, focusing on changes in their lives postdiagnosis, motivations for caregiving, challenges faced, coping mechanisms, and perceptions of caregiving. Understanding these experiences is crucial for enhancing support services for caregivers. Methods: A qualitative, exploratory study employing interpretative phenomenological analysis was conducted with 10 family caregivers. In?depth interviews were used to gather data on their lived experiences, which were analyzed to identify key themes. Results: Findings revealed significant emotional shifts, lifestyle adjustments, and changes in caregivers perceptions of the patient following the cancer diagnosis. Motivations for caregiving stemmed from external influences and personal attributes. Caregivers encountered multiple challenges, including lifestyle disruptions, emotional strain, financial difficulties, and a lack of support. Coping strategies involved prioritization, reliance on personal strengths, spirituality, family support, and rationalization, highlighting resilience and adaptability. Conclusion: Despite the difficulties, caregivers viewed their role as noble and transformative, maintaining a positive outlook and a deep concern for their loved ones well?being. These insights emphasize the need for healthcare providers to develop targeted support interventions to assist family caregivers in managing their responsibilities effectively 2025 Indian Journal of Social Psychiatry. -
Social Media Addiction and ParentPeer Attachment in Telangana Adolescents: A Cross-sectional Investigation
Background: The ubiquity of social media in contemporary life has raised concerns about its potential negative impacts, particularly among adolescents. While the impact of attachment on adolescents social media use has been studied in Western and South Asian contexts, there is a paucity of research on this relationship in the Indian context. Aims: This study aimed to find the relationship between sociodemographic factors, attachment to parents and peers, and social media addiction among adolescents in Telangana, India. Methods: A random cluster sampling method was used to survey 264 6th to 12th grade students in two schools. Data was collected using the Parent and Peer Attachment Inventory and the Social Media Disorder Scale. Chi-square analysis, Pearsons correlation, and multiple regression analysis were done to achieve the research objective. Results: The study found no association between sociodemographic factors (age, gender, socioeconomic status, family type, and number of siblings) and social media addiction. However, significant negative correlations were found between social media addiction and dimensions of attachment to parents and peers, except for communication with friends. Multiple regression revealed that attachment dimensions explained 15.7% of the total variance. The variables, Trust in the father and Alienation from the mother independently and significantly predicted social media addiction. Conclusion: The findings underscore the importance of attachment relationships in understanding social media addiction among Indian adolescents. The results reveal that fathers and mothers attachments to adolescents predict adolescent social media addiction differentially. Further research, especially longitudinal studies, is needed to explore these relationships in greater depth. 2025 Indian Journal of Social Psychiatry. -
Empowering Adolescents and Communities: Integrating Mental Health Awareness and Destigmatisation into Curriculum and Building a Foundation for Life
Adolescence, a critical period of growth, has seen an increase in mental health issues. Despite some successes in government initiatives, stigma continues to hinder help?seeking. To address this, programs should focus on anti?stigma efforts and emerging needs. A comprehensive mental health curriculum can help normalize discussions, reduce stigma, and encourage help?seeking. However, overcoming challenges such as time constraints, parental resistance, and a shortage of trained educators is essential. Organizing awareness events and sharing recovery stories can help combat stigma. Although social media has its drawbacks, it offers accessible and anonymous outreach. A concerning trend is the romanticization of mental health, which can trivialize real struggles and potentially lead adolescents to pretend mental illness for attention. A two?tiered solution is necessary to address this issue, involving certified educators, first?aid responders, and curriculum integration. This system allows professionals to focus on prevention and promotion while specialists handle diagnosis and treatment, ultimately fostering a long?term, inclusive, and mentally healthy society. 2025 Indian Journal of Social Psychiatry. -
Stress and Decision-Making among Civil Aviation Pilots in India: Mediating Role of Cognitive Flexibility
Objective: The study aims to investigate the difference between stress, decision-making, and cognitive flexibility based on demographic factors and the mediating role of cognitive flexibility on the association of stress and decision-making among civil aviation pilots. Methods: Data was collected from 372 commercial pilots from India through an online survey. The survey comprises standardized tools, including perceived stress, decision-making, and cognitive flexibility. Results: No significant gender difference was found in stress, decision-making, and cognitive flexibility. Age and work experience influenced stress levels, with mid-career pilots reporting the highest stress. Stress has a negative impact on pilots' decision-making ability. Cognitive flexibility partially mediates this relationship. Conclusion: Integrating cognitive flexibility training and stress management interventions into pilot training programs could significantly improve decision-making under pressure for safer aviation practices. 2025 Indian Journal of Occupational and Environmental Medicine. -
Indias Recent Free Trade Agreements and Alcohol Control: Implications for Public Health and SDG Commitments
Background: India accounts for 20% of the worldwide deaths due to alcohol use, and alcohol use among adolescents and young adults is on the rise. In May 2025, the Government of India negotiated Free Trade Agreements (FTAs) with the United Kingdom (UK), the European Union (EU) and a proposed agreement with the United States of America (USA), stipulating sweeping reduction in alcohol tariffs. This paper reviews the public health implications of such reduced tariffs under the FTAs. Materials and Methods: Existing evidence on the public health burden of alcohol use, along with the World Health Organization (WHO) and Government of India policies on alcohol control, and published information on the proposed FTAs, is reviewed. Result: No level of alcohol consumption is safe. Alcohol use disorder affects roughly 9% of Indian men. Extensive legal and constitutional safeguards are available for alcohol control in India. Taxation is one of the most cost-effective interventions to reduce alcohol-related harm. Reduction in alcohol tariffs proposed under the recent FTAs is inconsistent with Sustainable Development Goal 3, WHO policy guidelines, and national legal and constitutional framework for public health and alcohol control. Conclusion: Given the public health burden of alcohol use and Indias commitment to domestic and international alcohol control policies, it must keep cheap imports of alcohol out of the FTAs with the UK, the EU, and the USA. 2026 Indian Journal of Community Medicine. -
Measuring employee attrition intention in an auto-component manufacturing organisation
Orientation: The auto-component manufacturing sector, a critical contributor to industrial growth, faces persistent challenges related to employee attrition, affecting operational efficiency and workforce stability. This study examines the influence of job satisfaction, work-life balance, and job stress on attrition intention among employees in Indian auto-component manufacturing organisations. Research purpose: To identify the key factors contributing to employee turnover and evaluate their relative impact on attrition intention. Motivation for the study: Amid rising concerns over attrition in the manufacturing industry, this research aims to explore how work-life balance and job stress influence employees intentions to leave their organisations. Research approach/design and method: Data were collected from 192 employees across 10 auto-component manufacturing companies in Pune, Maharashtra, India, using a structured questionnaire. The responses were analysed through structural equation modelling (SEM) using SPSS and AMOS. Main findings: The study reveals that work-life balance and job stress significantly impact attrition intention. Employees with poor work-life balance and high job stress are more likely to consider leaving. However, job satisfaction does not have a direct effect on attrition intention. Practical/managerial implications: Organisations should prioritise improving work-life balance and managing job stress by implementing flexible work policies, wellness programmes, and realistic workload distribution. Contribution/value-add: This study underscores the importance of addressing work-life balance and job stress in retention strategies, offering actionable insights for HR managers to mitigate attrition in the auto-component manufacturing sector. 2025. The Authors. -
The Metaverse Marketplace: Exploring the Drivers of Consumer Purchase Behavior in Metaverse
This research explores factors influencing consumer intention to shop in Metaverse E-commerce, an area with limited existing research despite its potential for novel consumer experiences. A quantitative study involving 1,070 respondents used PLS-SEM to analyze a model based on technology readiness dimensions and Metaverse-specific variables. Key findings indicate that optimism and innovativeness are positively associated with consumer shopping intention in Metaverse E-commerce. Conversely, discomfort and insecurity show a negative association. Additionally, a sense of immersion, perceived interactivity, perceived personalization, perceived enjoyment, and perceived serendipity were found to significantly influence shopping intention within Metaverse E-commerce. This study enhances the academic literature on Metaverse shopping by integrating technology readiness dimensions and Metaverse-related constructs. The findings also offer practical insights for managers and marketers in developing effective Metaverse E-commerce strategies. 2025 IGI Global. All rights reserved. -
Enhancing English Learning Through Digital Storytelling in Indian Schools
This study examines the effectiveness of the Digital Storytelling (DST) teaching approach in improving English learning among ninth graders in four schools in Bengaluru, India. Using a sequential mixed-methods design, the quantitative phase included a non-randomized, post-test-only quasi-experimental design with 200 students divided into a DST-based experimental group and a traditional control group of 100 students each. Quantitative data were collected using a 12-item survey questionnaire, while qualitative data included self-reflection logs from 100 and interviews with 20 students from the experimental group. The results show that DST significantly improves language development and student satisfaction. This is evidenced by higher and more consistent post-test scores in the experimental group, with statistical significance confirmed by the Wilcoxon test. Increased engagement, understanding, and motivation reported by students are consistent with the quantitative improvements. 2025 IGI Global. All rights reserved. -
Early CKD Prediction Using Ensemble and Basic Machine Learning Models
Chronic kidney disease (CKD) is a progressive illness that often remains undiagnosed until advanced stages and represents a significant global health burden. Proper and timely diagnosis of CKD can significantly improve patient prognosis and reduce treatment costs. This study evaluates several machine learning (ML) models, including support vector machine (SVM), random forest (RF), gradient boosting (GB), Nae Bayes (NB), AdaBoost, and a multilayer perceptron (MLP) neural network. Additionally, it proposes a stacking ensemble model combining RF and GB for accurate CKD prediction using a publicly available Kaggle dataset. Missing value handling and feature normalisation are performed during data preprocessing, and model performance is evaluated using an 80:20 traintest split with metrics such as the area under the curve (AUC), classification accuracy (CA), F1-score, precision, recall, and Matthews Correlation Coefficient (MCC). Experimental results indicate that RF and GB achieve the strongest individual performance, while the proposed stacking ensemble attains the highest CA of 99.4%. These findings highlight the potential of artificial intelligence (AI)-driven predictive models to support proactive CKD diagnosis and enhance clinical decision-making in healthcare systems. 2026 by the authors of this article. Published under CC-BY. -
Federated Learning with Adaptive Intermediate Model Selection for Predicting IVIG Resistance in Kawasaki Disease
Kawasaki disease (KD), a rare pediatric illness affecting children under five, is treated with intravenous immunoglobulin (IVIG). But 1020% of patients are resistant to IVIG, and these resistant kids face a higher risk of coronary artery abnormalities. Identifying resistance early is vital, yet data scarcity, class imbalance, and the diseases rarity necessitate nationwide collaboration, which is often hindered by country-specific privacy policies. Federated learning (FL) provides a practical way for different parties to collaborate on training a model while keeping their raw data private and secure. To enhance model adaptability across diverse clinical populations, we propose an adaptive intermediate model selection strategy in federated learning. Each client retains the versionglobal or locally fine-tunedthat performs best on its own data, using customizable performance metrics such as F1-score or recall. The system was implemented using the Flower FL framework, with three simulated clients and a shared convolutional neural network (CNN) architecture. Experiments demonstrated that the global model achieved stronger performance than conventional models, and several clients obtained further gains by selecting intermediate models aligned with their data. This approach introduces a novel balance between worldwide collaboration and local personalization in FL, offering a flexible and clinically meaningful solution for IVIG resistance prediction. 2026 by the authors of this article.