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Spatiotemporal analysis and intensity prediction of forest fires using cuckoo search hybrid models
Forest fire forecasting is a critical aspect of environmental conservation and ecological risk management, particularly in biodiversitysensitive areas like Uttara Kannada, India. In this research, this article suggests a new hybrid modeling ap-proach that combines Cuckoo Search Optimization (CSO) with ensemble machine learning techniques, namely Random Forest (RF) and XGBoost (XGB), for forecasting fire intensity levels. Known as CSORF and CS-XGB, the hybrid models were trained and validated against a spatiotemporally dense dataset from 2009 to 2024, with primary environmental, topographic, and anthropogenic predictors. Aside from classification modeling, spatiotemporal analyses such as Kernel Density Estimation (KDE), seasonal fire patterns, and influence studies on features were performed to determine high-risk seasons and areas. CSO was used to automate the hyperparameter tuning process for both classifiers, yielding a significant boost in performance. The CS-XGB model registered the top accuracy of 99.49%, better than CSORF's 98.99%. Feature importance testing confirmed ecological significance, and humidity, temperature, and rainfall were the top-ranked variables. The work adds a scalable and precise prediction model that can assist in early warning systems and forest manage-ment practices. Kamal Upreti et al. -
Mapping Road Traffic Injury in India: Causes, Prevention, Economic Impact, and Role of Public Health Governance
Road Traffic Injuries (RTIs) represent the main reason for fatalities globally and are acknowledged as a significant national health problem. RTIs affect the victims and also have a profound impact on the family and relations. The socio-economic conditions of families, and consequently society and the nation, are negatively influenced by these incidents. A significant number of deaths on the roads involve cyclists, motorcyclists, and pedestrians. The prevalence of RTIs is particularly high in African and other middle-income countries, while developed nations experience comparatively fewer incidents. Each year, RTIs result in approximately 1.2 million deaths worldwide (WHO, 2018), marking them as a primary, preventable cause of mortality. Global attention has shifted towards the critical need for road safety, particularly with the endorsement of the 2030 Agenda for Sustainable Development Goals (SDGs). Implementing robust legal enforcement could lead to behavioural changes among road users. India ranks among the highest in the world for road accident-related fatalities. Ad-hering to safety measures such as using helmets, wearing seat belts, maintaining appropriate speeds, and following traffic regulations would significantly reduce Road Traffic Injuries. Stakeholders in road safety must be made aware of the economic costs, Disability Adjusted Life Year (DALY), and human losses associated with RTIs and their repercussions. This paper aims to outline the existing RTI situation, its causes, preventive strategies, magnitude of economic burden, costs involved in RTI, catastrophic health expenditure, Return on Investment (RoI) in Trauma Care Systems, Financing mechanisms, Governance, and the Health sector's role in addressing RTIs. The findings indicate that road accidents are the predominant reason for mortality in India (with many incidents being underreported or undocumented), and the state must take a proactive approach to tackle this issue by fostering strong connections among various stakeholders, while the health sector should implement a multifaceted strategy to manage RTIs. Authors. -
Enhanced Wavelet Block Shrinkage Technique For Mammogram Denoising Using K-Means Clustering And Neural Networks
The proposed research study introduces a novel approach for denoising digital mammograms by improving the existing wavelet block shrinkage filtering method with K-Means clustering and a convolutional neural network. This approach involves decomposing both the original and noisy mammograms into frequency subbands using 2D discrete wavelet transformation. The resulting subbands are then grouped into multiple clusters based on similar features of the wavelet coefficients, employing K-Means clustering. This represents an improvement over the traditional block shrinkage method, which uses fixed-size blocks. These clusters from the original and noisy mammograms are paired to train a convolutional neural network, which serves as an optimal shrinkage function. This neural network-based thresholding mechanism replaces traditional hard and soft thresholding methods that rely on a universal threshold. Test results demonstrate that the proposed enhanced wavelet block shrinkage mechanism achieves a 20% improvement in peak signal-to-noise ratio and a 5% increase in structural similarity index score compared to traditional wavelet block shrinkage. Authors. -
Financial Literacy and Fintech Exposure As Determinants of Investment Decisions: The Mediating Role of Investment Interests A Study of Individual Investors in Hyderabad, India
The evolution of the financial sector, particularly the rise of financial technologies (Fintech), has reshaped how individual investors make investment decisions. This study investigates the influence of financial literacy and fintech exposure on individual investment decisions in the underexplored emerging markets like Hyderabad, emphasising the mediating role of investment interest. Drawing on behavioural finance theory and empirical studies, the research explores how informed financial understanding and engagement with digital financial platforms shape investment behaviour. The data is collected using a structured survey method from 311 individual investors in Hyderabad, India. For the study, Structural Equation Modelling (SEM) was employed to test relationships among the constructs. Unlike prior studies that have often examined financial literacy or fintech exposure in isolation, this paper uniquely integrates these two determinants with the mediating mechanism of investment interest, providing a comprehensive model of investment decision-making in the Indian context. The study contributes to the understanding of investment psychology within the Indian context and offers insights for policy-makers and financial institutions aiming to foster inclusive and informed investment ecosystems. It can be concluded that financial literacy positively influences investment decisions by providing investors with the necessary knowledge and skills to evaluate options critically and confidently. Dr. Syed Jaffer et al. -
Strategic Decision-Making in The Era of Artificial Intelligence: A Multi-Dimensional Evaluation of Opportunities, Challenges and Ethical Concerns
This paper explores the impacts of Artificial Intelligence (AI) on strategic business decisions, focusing on the opportunities, hurdles, and ethical aspects associated with embedded AI in organizations. With a mixed-methodology, the study does not rely solely upon quantitative data to assess decision-making consequences influenced by AI and machine technologies, but includes qualitative feedback from business leaders on the ground. The findings imply that while AI significantly enhances data analysis and informs strategic decisions, it also raises issues about transparency, accountability, and whether there may be bias embedded in decisions driven by algorithms. Nowhere is this more apparent than in the healthcare sector, the implications of which are significant as greater reliance on AI can facilitate improving operational efficiencies and patient results, but it also demands robust frameworks to confront the ethical issues around patient privacy and informed consent. Ultimately, this work fuels the debate regarding the transformative effect of AI on business strategy and highlights that the incorporation of ethical considerations cannot be compromised if we are to develop guidelines in this area. These recommendations can help to mitigate AI-related risks and enable responsible AI adoption in the healthcare and other contexts, and pave the way for future research on the emergent technology-strategic management connection. Neeraj Kumar et al. -
Enhancing Mobile DeFi Transactions Through Blockchain Adoption: A Pythagorean Fuzzy AHP Study
Blockchain technology has emerged as a pivotal enabler for innovation in mobile decentralized finance (DeFi) ecosystems. This study ememploys the Pythagorean Fuzzy Analytic Hierarchy Process (PF-AHP) to identify and rank critical enablers driving blockchain adoption for enhancing mobile DeFi transactions. A structured three-stage methodology evaluates twenty-four sub-criteria across operational, managerial, and strategic dimensions. Results emphasize managerially focused factorssuch as reduced foreign exchange (FX) transfer costs and open-source adaptabilityas the most critical enablers, followed by operational drivers like transparency. Sensitivity analysis confirmed the ro-robustness of these findings. The results offer actionable insights for fintech practitioners, digital strategists, and policymakers seeking to optimize blockchain-based mobile financial platforms. By contributing to improved financial inclusion, operational efficiency, and regulatory alignment, the study supports broader welfare enhancement in the digital economy. The proposed PF-AHP framework provides an empirical decision-making tool to guide innovation and strategic planning in financial technology services. Yogesh Kumar Jain et al. -
Exploring The Dynamic Relationship between Macroeconomic Variables on Indias Premier Benchmark Sensex 30 Index
The purpose of the study is to examine the impact of macroeconomic indicators on the closing prices of the BSE Sensex 30, a key benchmark index in India known for its volatility in response to economic conditions. This research is particularly relevant in the context of economic shocks, as it aims to recommend the adoption of appropriate economic policies that could benefit the stock market index, ultimately advancing growth in the capital market. Using the ordinary least squares (OLS) method, the study analyzes the effect of various macroeconomic variables on the BSE Sensex. Additionally, the complex relationship between these variables is explored using the Johansen Cointegration test and evidenced through the Vector Error Correction (VECM) model. The findings reveal that GDP, the Index of Industrial Production (IIP), Indias foreign trade, gold prices, Foreign Direct Investment (FDI), and money supply significantly influence the BSE Sensex. However, External Commercial Borrowing, the Consumer Price Index (CPI), exchange rates, and foreign exchange, which showed the highest Variance Inflation Factors (VIF), were excluded from the study based on OLS results. In conclusion, the study advocates for the implementation of suitable economic policies that support the stock market, thereby aligning with investors interests and promoting capital market growth. Vishweswarsastry V. N. et al. -
Contextual Marketing Insights from Literature Review and Implications
The proliferation of new technologies, such as personal digital assistants, or PDAs, and interactive television, amongst other things, has opened a wealth of potential for effectively targeting customers in real time while they are present in a virtual environment. This opens a lot of opportunities for businesses. Customers have access to the World Wide Web and the Internet through their wireless devices, no matter where they are or when they want to use them. Contextual marketing, often referred to as CM and commonly abbreviated as CM, is a strategy that entails providing customers with information that is both individualized and pertinent to their present position at the precise moment when customers need such information. This strategy is essential for luring in new clients and keeping the ones you already have. Clients in an economy that is already oversaturated with information demand not only knowledge, but also products and services that are relevant, personalized, and contextual at the time of purchase. The purpose of this research is to conduct a comprehensive review of the existing literature on contextual marketing in the preceding 20 years, focusing on both the global and the Indian contexts. The development and expansion of contextual marketing, as well as its contemporary consequences regarding earlier published works, are investigated. In the study, the systematic literature review approach of searching for relevant material is used. This research was carried out with the intention of conducting a comprehensive assessment of the existing literature with the purpose of ensuring that the fullest possible list of relevant studies is taken into consideration. To compile the papers comprising the systematic review, an algorithmic search strategy was utilized. An analysis of the previous research was carried out with the use of online databases such as Elsevier, Routledge, Emerald Group, Springer Nature, Sage, Directory of Open Access Journals, Semantic Scholar, Wiley, Academia, JSTOR, and Guildford Press. The study reaches its conclusion by providing a tangible theoretical foundation for contextual marketing while also outlining the ramifications that contextual marketing has in the modern digital world. Authors. -
Mechanical Characterization of Cu-Al-based Shape Memory Alloys: Influence of Mn, Be and Fe on Tensile Strength, Yield Stress, Yield Strain, Ductility and Hardness
The pursuit of cost-effective and robust Shape Memory Alloys (SMAs) continues to expand, especially for applications in adaptive and smart structural systems, while Ni-Ti-based SMAs remain prevalent due to their superior pseudoelasticity and longevity. However, the limitations of NiTi alloys, including the high processing costs and fabrication difficulties, prompt the exploration of alternatives. This study investigates Cu-Al-based SMAs alloyed with Mn, Be, and Fe as cost-effective alternatives to NiTi systems. In the present work, Cu-Al-based alloy wires with Mn, Be, and Fe were betatized at 850 C and water-quenched to achieve martensitic structures, followed by evaluation of tensile strength, yield behavior, ductility, and hardness. Mn addition significantly enhanced tensile strength (up to 425 MPa), while Be and Fe improved ductility through grain refinement. Hardness increased with Mn due to solid solution strengthening. Thus, the current work provides a comparative analysis of Cu-Al-Mn, Cu-Al-Be-Mn, and Cu-Al-Fe-Mn alloys, linking alloying strategies to microstructural evolution and mechanical performance, demonstrating their potential for advanced engineering applications. 2025 King Mongkuts University of Technology North Bangkok. All Rights Reserved. -
Optimising Education for Sustainable Development through Secondary School Teachers with Relevant Subjects, Standards and Training: Quantitative Review
India aims to become a developed nation by 2047, emphasizing the role of Education for Sustainable Development (ESD) in achieving Sustainable Development Goals. This study examines the beliefs of Kerala secondary school teachers regarding ESD, investigating how teaching standards, subjects, and prior ESD training shape their perspectives. A survey of 400 teachers utilized the revised ESD Belief Scale, incorporating demographic considerations. The research examined demographic variables, including teaching level, subject specialization, and previous ESD training. Quantitative analysis encompassed descriptive statistics, t-tests, and ANOVA to evaluate beliefs across various groupings. Findings reveal that educators predominantly recognise the significance of ESD in fostering sustainable decision-making and lifelong learning. The discipline taught, especially social sciences in contrast to science, technology, engineering, and mathematics, is the primary determinant of educators' beliefs towards ESD. Teachers recognise the benefits of ESD, although they encounter obstacles, including restricted curricular integration and implementation. This research addresses ESD within the secondary curriculum in a unique manner, filling a notable gap in both theoretical and empirical literature. The implementation of an updated belief scale and subgroup analyses provides policymakers and curriculum developers with novel perspectives. It is recommended that curriculum reform incorporate ESD throughout all courses, accompanied by specialized teacher training to enhance awareness, skills, and pedagogical techniques for the effective implementation of ESD. Secondary educators in Kerala predominantly advocate for the integration of ESD, particularly within the social sciences. Future policy and research must emphasise curricular innovation and longitudinal assessment to further Indias sustainable development objectives. 2026 Sijo VARGHESE & P.M. MATHEW. Published by the Asian Society of Human Services (ASHS). -
Navigating the Metaverse: TCCM Approach for Comprehensive Review of Avatar Marketing Strategies
Despite the growing importance of avatars in reshaping consumer interactions, there remains a discernible gap in the literature necessitating a comprehensive synthesis of existing knowledge. In response, this study conducts a systematic-literature-review employing the Theory-Context-Characteristics-Methodology (TCCM) framework. Study aims to delineate the current state of the field by addressing key research foci and conducting a meticulous TCCM analysis. Drawing from the TCCM-framework, our investigation encompasses an exploration of (1) dominant theories guiding research endeavours, (2) contexts within which avatar marketing is situated, (3) key characteristics characterizing the studies, (4) diverse study methodologies employed, and (5) the overall trajectory of research in this domain. Study unfolds a panoramic view of avatar marketing in the metaverse, synthesizing existing knowledge, and illuminating the key dimensions that shape this dynamic field. Insights gained from systematic-literature-review contribute to a deeper understanding of the theories, contexts, characteristics, and methodologies that have underpinned research endeavours thus far. 2013 The Korean Society of Management Information Systems. All rights reserved. -
IoT-Based Emergency Vehicle Detection Using YOLOv8
The rapid response of emergency services plays a critical role in saving lives and minimizing the impact of emergencies. However, identifying and locating emergency vehicles in real-Time can be challenging, especially in congested urban areas. This paper focuses on the emergency vehicle identification using the You Only Look Once version 8 (YOLOv8) algorithm and is focused on Internet of Things (IoT). The goal of this research is to develop a real-Time and precise emergency vehicle detection system using You Only Look Once version 8 (YOLOv8) algorithm, trained and tested with a dataset from a camera placed on a busy road, to enhance emergency service response times. The findings demonstrate the suggested system's ability to recognize emergency vehicles at a speed of 31 frames per second and with a 95% accuracy rate. Modern object identification algorithms include the You Only Look Once version 8 (YOLOv8) algorithm, which has shown promising results in various applications. The proposed system is built on a Raspberry Pi, which acts as an edge device and processes the video stream in realtime. The system consists of an Internet of Things (IoT) device with a camera that captures the live video stream, which is then fed into the algorithm for object detection. Once an emergency vehicle is detected, the system sends an email notification to the nearby emergency services, like a police station, using Simple Mail Transfer Protocol (SMTP), who can then take appropriate action. The results of this investigation show that the Internet of Things and You Only Look Once version 8 (YOLOv8) algorithms have great promise for creating effective and dependable emergency vehicle detection systems. The proposed system possesses the capacity to save lives and improve the effectiveness of emergency response by speeding up response times for emergency services. The suggested solution is also inexpensive, simple to implement, and adaptable to existing infrastructure. Through the development of intelligent transportation systems, emergency services can operate more safely and effectively. More sophisticated machine learning algorithms may be incorporated into the proposed system, and further sensors can be added to utilize alternative methods beyond camera-based detection to identify emergency vehicles. Overall, this research shows the potential of Internet of Things (IoT) and machine learning in creating creative emergency services solutions. 2025 Syed Suhana et al.Published by Sciendo. -
Exploring the Pharmaceutical Potential of Meretrix casta (Gmelin, 1791) (Mollusca: Bivalvia)
Meretrix casta, a marine mollusk, has been recognized traditionally for its nutritional and medicinal properties. This study aims to investigate the pharmacological potential of M. casta extracts, specifically focusing on the antioxidant, hemolytic, anti-inflammatory and antimicrobial activities. The antioxidant activity, assessed via hydrogen peroxide scavenging and phosphomolybdate assays, revealed concentration-dependent inhibition, with the methanol extract showing 61.04% inhibition at 100 g/mL compared to 61.19% for ethyl acetate, while the standard ascorbic acid exhibited 87.80%. Anti-inflammatory activity was evaluated using heat-induced hemolysis, hypotonicity-induced hemolysis and protein denaturation assays. Both extracts demonstrated significant anti-inflammatory effects, with the ethyl acetate extract achieving 85.40% inhibition of hemolysis, closely matching acetylsalicylic acids 90.50% and methanol extract showing 87.60% at 100 g/mL. Antibacterial and antifungal assays demonstrated significant inhibitory effects against pathogenic bacteria and fungi, with the methanolic extract frequently exhibiting higher efficacy. These findings highlight the therapeutic potential of M. casta extracts as natural bioactive agents. Future investigations should aim to isolate and characterize the specific bioactive compounds underlying these pharmacological effects and to explore their mechanisms of action in detail. Such studies could pave the way for new therapies derived from marine biodiversity, addressing various health challenges. 2025 Asian Publication Corporation. All rights reserved. -
Biochemical and Rapid Paper Sensory Detection of Heavy Metals in Milk Based on Biosynthesized Silver Nanoparticles
Milk is an emulsion of proteins and fats in water that contributes to a nutritious diet and enhances our immune system. However, contamination of heavy metals in milk due to an increase in industrialization and urbanization can be a serious threat to human health. This study focused on the rapid detection of heavy metals particularly lead and mercury in milk using biochemical assays as well as paper-based colorimetric sensor based on green synthesized silver nanoparticles (AgNPs) from leaf extract of Hemigraphis colorata. Biochemical assays such as the lead chromate test and sodium hydroxide test were employed to detect lead and mercury in milk samples. The biogenic AgNPs were characterized by UVVis spectroscopy, scanning electron microscope, Fourier transform infrared spectroscopy, energy dispersive X-ray analysis (EDX) and X-ray diffraction. The unique properties of silver nanoparticles (AgNPs) like surface plasma resonance (SPR), large surface area and visible colour change upon aggregation when metal ions interact, enable them to detect heavy metals. This is a portable and affordable method of detection that ensures safer milk consumption and sustainable environmental practices. 2025 Asian Publication Corporation. All rights reserved. -
Decoding impermanent narratives: A study of transient migrants as digital influencers on YouTube
Students migrate from India annually for higher education in large numbers. Social media has become an essential network for disseminating information related to aspects of migration like student visas, college applications, residence and finances. YouTube engages vigorously in this dispersion of information. Many times, the sources of these kinds of information are found to be transient migrants themselves. YouTubers and influencers like Tushar Bareja, Nidhi Nagori, Gursahib Singh, Bani Singh and Saloni Verma, among others, have made a niche, creating content and sharing information about the experience of being a transient migrant. Much like the status of being transient, creating ones brand on social media is both dynamic and fleeting, which cannot be defined in a sense of permanence. The analysis of content created by YouTube influencers enables an insight into the definition of transient migrant identity. The topics that are covered in the content showcase the particular components of international student life that add to the concept of a transient migrant identity. The article attempts to ask the question of how the YouTube videos made by student migrants end up contributing to the transient migrant identity. It also attempts to decipher how the transient identity itself is packaged as a commodity to be monetized by these student migrant influencers on YouTube. Using theoretical frameworks of influencer culture, social media and migration, the article attempts to unravel the workings of YouTube in commodifying the transient migrant experience. 2025 Intellect Ltd. -
Design and experimental validation of multi-section directional coupler with arbitrary coupling and high directivity for sub-6 GHz UWB applications
This work presents a geometrically simple topology for developing an ultra-wideband directional coupler with improved coupling and directivity. A short-ended coupled-line structure is used to achieve an ultra-wideband, tightly coupled symmetric three-section coupler using the microstrip line technology. The proposed design demonstrates an explicit improvement of approximately 1.2 dB in coupling compared to conventional multi-section directional couplers. Calculated, simulated, and measured responses validate the effectiveness of the proposed configuration in terms of low-ripple coupling bandwidth, low insertion loss, and improved directivity performance compared to respective responses of the conventional structure. Couplers featuring a higher number of sections to implement different bandwidths and couplings can be fabricated using the presented structure due to its transmission line-based approach. A prototype of the three-section directional coupler with coupling of 7.6 dB, 8.1 dB, and 8.3 dB and corresponding bandwidths of 104%, 123% and 133% is designed, fabricated, and measured. The experimental results confirm that the coupler can reliably achieve higher coupling with ultra-wideband response from 0.75 GHz to 3.75 GHz (5:1) with 8.3 1.4 dB (ripple). Additionally, the design yields promising performance with return loss > 16 dB, isolation > 20 dB, a phase difference of 90 4, and directivity > 30 dB, and the maximum circuit size is 0.067?02. This work aligns with SDG 9: Industry, Innovation and Infrastructure by advancing high-performance microwave components that support efficient, reliable, and scalable communication infrastructure. 2026 Patel et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. -
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. -
Examining the impact of maternal experiences of domestic violence on the mental health of their adolescent children in India
Background Domestic violence (DV) is experienced by one in three women in India and is linked to poor mental health outcomes. We hypothesize that maternal experiences of DV can have negative impacts on the mental health of their children. Previous studies have demonstrated this link in Western countries, however culturally specific manifestations of DV and mental health disorders and socio-cultural differences in parent-child relationships and home environments necessitate deeper understanding of the impacts of maternal experiences of DV on children in the Indian context. Methods This study presents a secondary analysis of data collected from a seven-center study in urban and rural India examining mental health disorders among adolescents aged 1217 years and psychological, physical, and sexual abuse affecting their mothers. The Indian Family Violence and Control Scale (IFVCS) was used to examine experiences of DV among mothers and the Mini International Neuropsychiatric InterviewKid (MINI-Kid) was used to examine mental health outcomes among adolescents. Multivariate analyses examined the associations between maternal DV and adolescent mental disorders. Results Data from 2,784 adolescent-mother pairs were analyzed. In bivariate analyses, maternal experiences of physical, psychological, and sexual abuse were significantly associated with adolescent common mental disorders including anxiety and depression (p < 0.05). After adjusting for adolescent gender, site, and education status in the multivariate analysis, physical, sexual, and any DV were significantly associated with adolescent anxiety disorders and common mental disorders. Physical abuse was significantly associated with adolescent depressive disorders. Conclusions These results suggest that exposure to maternal DV significantly impacts adolescent mental health in India and underscore the need to develop trauma-informed school programs and enhance DV prevention for women in India. 2025 Gourisankar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. -
Fire Safety Challenges in Electrical Shafts: A Case of Fire Accident at High Rise Residential Building in Bengaluru, India
Fire safety in high-rise residential buildings is a complex issue, especially when it comes to electrical shaft fires. These enclosed vertical shafts help the rapid spread of smoke, toxic gases and heat across different floors and pose a high risk to the occupants and affect the evacuation process. However, the actual life fire outbreaks show that the existing measures are still wanting as far as evacuation safety is concerned. These issues are addressed in this research through the use of performance-based fire design (PBFD) to assess fire behaviour and evacuation patterns in high-rise buildings. The study then simulates using PyroSim and Pathfinder simulation software, the visibility of smoke, reduction of visibility, CO and CO2 levels, temperature changes, and congestion of the evacuation corridors. Unlike other studies, this paper combines both fire development and occupants response to give a holistic approach to the issue of evacuation challenges. One of the findings of this research is the analysis of the ASET and RSET whereby it was found that the current provisions in fire safety do not ensure a safe exit. It was established that RSET is much higher than ASET, which points to a severe lack in current fire safety solutions. Simulations incorporating NBC-2016 (National Building Code-2016) provisionssuch as fire-rated doors, sprinklers, and mechanical ventilationdemonstrate improved outcomes, reducing RSET from 1,272 seconds to 746 seconds. However, persistent challenges such as congestion, bottlenecks, and hazardous gas levels highlight the need for enhanced fire safety strategies. This research offers practical recommendations to improve evacuation effectiveness through better ventilation, compartmentalization, and advanced suppression systems. The findings contribute to risk mitigation strategies, expand the knowledge base for fire safety, and provide a foundation for improving fire safety regulations in high-rise buildings. 2025 by authors, all rights reserved. -
Landholding size, indebtedness, and crop insurance in India: A macro-level quantitative assessment
Keerthikumara SM, Saikia B, Hiremath C. 2025. Landholding size, indebtedness, and crop insurance in India: A macro-level quantitative assessment. Asian J Agric 9: 377-390. Indian farmers continue to face structural distress driven by low income, high indebtedness, and inadequate risk protection. This study investigates the interrelationship between landholding size, agricultural credit, indebtedness, and crop insurance uptake using state-level secondary data from 2016 to 2023, drawn from Agricultural Statistics at a Glance, PMFBY/RWBCIS dashboards, and NCRB reports. Using descriptive statistics, linear regression, and paired t-tests, we identify key macro-level trends across 20 major Indian states. Results show that marginal and small farmers (less than 2 hectares) account for over 62.7% of all indebted farm households, but receive only 38.5% of total institutional agricultural credit. A bivariate regression reveals that a ?1,000 increase in monthly farm income is associated with a reduction of 1,314 indebted households (?=-0.445, p=0.016). Despite substantial credit disbursal in high-debt states like Andhra Pradesh and Telangana, farmer debt remains elevated, underscoring that credit alone does not reduce vulnerability. Crop insurance enrollment increased after the 2020 policy shift from mandatory to optional participation among loanee farmers, yet the change was not statistically significant (p=0.099). Actuarial analysis reveals that in several states, claim settlement ratios remain below 50%, with high premiums and delayed payouts fueling distrust. The study recommends fully subsidized premiums for marginal farmers, region-specific pricing, improved claim transparency, and financial literacy integration with agricultural extension. Effective risk mitigation in agriculture must go beyond insurance and integrate income and credit reforms to ensure equitable protection for Indias most vulnerable farmers. 2025, Smujo International. All rights reserved.