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Characterizing Ultimatum Game responders: a scoping review of factors that influence decision-making through an evolutionary lens
The Ultimatum Game is a widely used tool for studying conflict resolution within a bargaining framework. This scoping review aims to comprehensively examine the various internal and external factors influencing the responders behavior in this game and compile the status quo of the knowledge space. 31 pertinent research articles were identified from databases like Google Scholar, PubMed and JStor, using the following keywords ultimatum game, responder behavior, emotions and the ultimatum game, fairness in the ultimatum game, social norms and the ultimatum game, punishment game, impunity game, outside options in the ultimatum game. An analysis of the same yielded two broad domains of influencing factors: internal and external. Internal factors encompassed emotions, personality traits, and cognitive capabilities, showcasing their significant influence on decision-making. External factors, including ownership, social norms, power dynamics, outside options, gender, and attraction, revealed how the context of the game shaped responder choices. This review investigates how internal and external factors influence bargaining behavior within the Ultimatum Game, distinguishing between typical and atypical responder behavior. Invoking Kahnemans dual system theory offer insights into the evolutionary roots and modern cognitive processes guiding decision-making. The interplay between these systems reveals nuanced responses to fairness, reciprocity, and self-interest, challenging traditional economic models. While acknowledging the oversimplification of brain dynamics in these studies and also the need for cultural integration, the current review compiles a framework that advances our understanding of human behavior across disciplines, particularly for economics, psychology, and evolutionary biology. Refining this model promises deeper insights into decision-making processes amidst societal complexities. Copyright 2026 Chowdhury, Rangaswamy and Kolte. -
Screens and scars: SEM analysis of the relationship between childhood trauma, emotion regulation, and social media addiction
Background: Addiction is an increasingly significant global public health concern, affecting individuals across diverse age groups and demographics. With the rapid rise of digital technology, social media addiction has emerged as a growing behavioral issue, impacting mental health, interpersonal relationships, and daily functioning. Methods: This study employed an online cross-sectional self-report questionnaire, with university students aged 1635?years as the target population. Data were collected using Google Forms questionnaires, accessible via the university registration system, and sent to the participating students smart phones. The data collection instruments included the Social Media Addiction Scale (SMAS), the Childhood Trauma Scale (CTS), and the Difficulty in Emotion Regulation Scale (DERS). Results: Data from 318 university students were analyzed. The analysis of sociodemographic data revealed a mean participant age of 21.2?years, with 87.3% being female. An analysis of the relationship between social media addiction and childhood trauma revealed that participants with childhood trauma had higher social media addiction. The linear regression model, including childhood traumas and emotion regulation difficulties for social media addiction scores, was statistically significant. A positive correlation was observed between social media addiction and difficulty in emotion regulation. Conclusion: These findings suggest that individuals who struggle with emotion regulation tend to use social media more frequently. Furthermore, the negative effects of childhood trauma on emotion regulation capabilities during adulthood contribute to the development of social media addiction. Copyright 2025 Elkin, Mohammed Ashraf, K?l?nl, K?l?nL, Ranganathan, Sakarya and Soydan. -
Cyber-victimizationinfluence of parental rules and impact on mental health among Indian adolescents
Introduction: In the contemporary digital age, cyberspace offers numerous benefits but also presents significant risks, including cyber-victimization. Adolescents, as frequent internet users, are particularly vulnerable to such experiences. This study examines the relationship between parental regulations on internet usage and the incidence of cyber-victimization among Indian adolescents, while also assessing the impact of cyber-victimization on mental health outcomes such as stress, anxiety, and depression. Methods: A sample of 224 adolescents (Mean age?=?16.5?years SD?=?2.34) was surveyed using standardized measures of cyber-victimization and mental health. Results: Multiple linear regression analyses revealed that written-verbal cyber-victimization was a significant predictor of stress (??=?0.18, p?<?0.05), while impersonation, written-verbal cyber-victimization, and online exclusion significantly predicted anxiety (p?<?0.05). However, none of the cyber-victimization subtypes significantly predicted depression, and the overall model accounted for only 4% of its variance. Discussion: These findings suggest that while cyber-victimization is linked to stress and anxiety, its influence on depression may be more complex. Furthermore, the Pearson correlation analysis indicated a negligible association between cyber-victimization and parental rules on internet usage (r?=?0.039), suggesting that parental regulations alone may not effectively mitigate cyber-victimization risks. Given these findings, interventions focusing on resilience-building, digital literacy, and peer support may be more effective in protecting adolescents from the adverse effects of cyber-victimization. Future research should explore alternative protective factors and preventive strategies to promote adolescent well-being in digital spaces. Copyright 2025 Tamarana, Mathur, Madhusudan and Annapurna Kiranmai. -
Signal-aware deep learningbased respiratory motion prediction for lung tumor management
Introduction: Respiratory motion management in radiotherapy for lung cancer patients remains a significant challenge, as it directly affects accurate tumor targeting. Furthermore, unaccounted tumor motion during treatment planning and delivery can lead to imaging artifacts and biased dose distributions, which compromises the accuracy of image-guided radiotherapy. This issue places clinicians in a dilemma between expanding treatment margins, which increases radiation exposure to healthy tissue or risking reduced targeting precision. Methods: In this work, a hybrid deep learning model composed of dilated convolutional layers, bidirectional long-short term memory layers, and a generative autoencoder module is proposed to jointly model the spatial and temporal characteristics of respiratory motion, while enabling reconstruction of the physiologically coherent respiratory signals. Each architectural component learns complementary motion-related patterns from respiratory signals to support tumor motion prediction. The model performs motion-range classification, captures abnormal breathing patterns across spatial and temporal domains, reconstructs physiologically coherent respiratory cycles, and predicts tumor motion within an algorithmic validation framework. Results: Experimental evaluation demonstrates high motion-range classification performance of 98.37%, including low root-mean square error in motion prediction, while maintaining stable performance across long and complex respiratory signals over multiple breathing cycles. Discussion: This study focuses on algorithmic feasibility and establishes a computational foundation for future clinically calibrated and dosimetrically validated models. The findings indicate that the proposed approach can support future motion-aware radiotherapy planning strategies by improving motion characterization at the algorithmic level. Copyright 2026 Das, J. and Medhi. -
Development and validation of screening tool for excessive and problematic use of internet and digital devices (STEPS-IDD) based on the WHO framework (ICD-11) for addictive behaviours
Background: The widespread use of internet and digital devices has been accompanied by growing concern regarding harms associated with their excessive or problematic use. The World Health Organization has also formally included some of these in its latest classificatory system (ICD-11) under the category of disorders due to addictive behaviours. However, a validated, comprehensive screening tool aligned with ICD-11 that screens for these potentially addictive behaviours is lacking. This study aimed to develop and validate the Screening Tool for Excessive and Problematic use of Internet and Digital Devices (STEPS-IDD), designed to assess multiple addictive behaviours based on ICD-11 criteria. Methods: STEPS-IDD was developed based on the ICD-11 framework for disorders due to addictive behaviours It was applied to assess well-established behavioural addictions like gaming and gambling disorder, as well as less-established but widely researched ones such as problematic use of social media, online shopping/buying, OTT content watching, and pornography watching. Face validity was established through expert review and feedback. Construct validity was evaluated through exploratory factor analysis (EFA), and Cronbach's alpha coefficients were estimated to assess internal consistency. To examine concurrent validity, correlations between scores obtained on the newly developed STEPS-IDD sub-sections and the previously validated Gaming Disorder and Hazardous Gaming Scale (GDHGS) and modified GDHGS for other behaviours were assessed. Receiver Operating Characteristic (ROC) analyses were conducted to determine optimal STEPS-IDD cut-off scores for different behaviours. Results: Data from a total of 112 college students (64.3% female) with a mean age of 20.5 years were analyzed. STEPS-IDD demonstrated good construct validity, with EFA revealing predominantly unidimensional factor structure for most behavioural domains. Internal consistency was excellent (Cronbach's ? = 0.860.91 across sub-sections). Concurrent validity was supported by moderate to strong positive correlations (r = 0.440.76) of STEPS-IDD sub-sections with corresponding GDHGS and modified GDHGS scores. ROC analyses yielded optimal cut-off scores with high sensitivity and acceptable specificity for different behaviours, and fair to excellent overall diagnostic accuracy. Conclusion: STEPS-IDD is a psychometrically robust, brief yet comprehensive screening tool grounded in the ICD-11 framework, for the risk stratification in the context of addictive behaviours related to the use of the internet and digital devices. 2026 Balhara, Singh, Majumdar, Ayoob and Singh. -
Gen AI Gen Z: understanding Gen Zs emotional responses and brand experiences with Gen AI-driven, hyper-personalized advertising
Introduction: Gen Z, a tech-savvy consumer group, has highly evolved in its approach to new-age advertising. The rise of Generative Artificial Intelligence (Gen AI) has revolutionized advertising by enabling hyper-personalized content, making it essential to understand its influence on Generation Z (Gen Z) population. This study explores the responses of Gen Z participants in India to Generative Artificial Intelligence based, hyper-personalized advertisements, with a specific focus on emotional responses and brand interactions which are significant predictors of advertisement success. Methods: Using qualitative research methods, semi-structured interviews were conducted with 40 Gen Z participants. Thematic analysis of the data was performed to understand the major themes pertaining to emotional responses and brand interactions to this form of Gen AI-driven advertising. Results: Two major themes and five sub-themes were revealed through thematic analysis. The first theme, diverse emotional responses, encompassed two sub-themes, curiosity and interest as well as fear and suspicion. The second major theme, enhanced brand experience, encompassed three sub-themes of advanced targeted marketing; initial attraction and brand engagement; and brand connection and loyalty, as perceived by the participants. Discussion: Findings imply that brands can harness Gen AI-driven, hyper-personalized advertisements to evoke meaningful emotions, enhancing consumer loyalty and building stronger, more personal connections with their audience. Copyright 2025 Peter, Roshith, Lawrence, Mona, Narayanan and Yusaira. -
Heavy metal contaminants in eggs and hatchlings of olive ridley turtles (Lepidochelys olivacea) at a mass nesting rookery in India
Heavy metal pollution has emerged as a prominent threat in recent times with high metal levels widely reported in species across ecosystems. The threat of rapid biomagnification is particularly enhanced in species such as olive ridley turtles, which occupy a higher trophic position, increasing their exposure to heavy metals. In the current study, we examine the presence of heavy metals in adults, in-utero and oviposited eggs, hatchlings as well as the nesting beach at two important olive ridley rookeries in India Devi and Rushikulya. We collected muscle and in-utero egg samples from stranded adult olive ridleys at the two rookeries, while oviposited eggs, hatchling and sand samples were obtained from hatchery nests at Rushikulya. We compared concentrations of 9 heavy metals (Cr, Mn, Ni, Co, Cu, As, Se, Cd, and Pb) across different sample types in an Inductively Coupled Plasma Mass Spectrometer (ICP-MS). We found mean metal concentrations of sand to be highest among all samples analysed, followed by muscle tissue. Arsenic was the most prominent metal in adult turtles suggesting bioaccumulation, while Selenium was found to be higher in egg components. Heavy metals (HM) were found in-utero eggs, providing evidence of maternal transfer. Most HMs were similar for in-utero and oviposited eggs, though a few metals were higher in in-utero eggs suggesting potential leaching out during development. Sand and hatchling samples show a high correlation for Mn suggesting potential environmental transfer. These findings emphasise the risk posed by heavy metals to adult and early life stages of olive ridleys and highlight the urgent need for mitigation of these threats. Copyright 2026 Pradhan, Pusapati and Shanker. -
Mediating Role of Mathematics and Science Engagement in the Relationship between Attitude toward STEM Education and Subjective Well-being of Adolescents
Science, technology, engineering, and mathematics (STEM) education has become a focal point of global discussions in the field of education. It emphasizes an interdisciplinary approach to learning. Subjective well-being of adolescents is characterized as joy to learn, close connectedness in schools, perception of the purpose of education, and the estimation of academic efficiency. This study investigates the mediating role of mathematics and science engagement in the relationship between the attitude toward STEM education and subjective well-being of school students in Kerala. Drawing upon theoretical frameworks from psychology, education, and sociology, this study employs a quantitative approach to data collection and analysis. A sample of 363 secondary and senior secondary students was administered standardized survey tools, measuring attitudes toward STEM education, subjective well-being, and their engagement in mathematics and science classes. Regression and mediation analyses resulted in indicating the positive, mediating effect of mathematics and science engagement in the relationship between the attitude toward STEM education and subjective well-being. Practically, the study suggests that educators should foster positive STEM attitudes through engaging teaching techniques and hands-on activities. Cultivating a positive STEM culture in schools can contribute to students well-being and equip them for future success in STEM fields. 2025 International Council of Associations for Science Education (ICASE). All rights reserved. -
Impact of Endothelial Cell Repair Mechanisms on Doxorubicin-Induced Cardiomyopathy: Exploring Molecular Docking and Simulation studies of Angiogenic Factors
Doxorubicin (Dox), despite being an effective anti-cancer drug, also causes cytotoxicity to noncancerous tissues. ECs are highly abundant in the heart; thus, endothelial dysfunction is a major cause of doxorubicin-induced cardiomyopathy. The release of EPCs triggered by endothelial dysfunction, participates in the growth of new blood vessels and the repair of damaged endothelium to promote repair mechanism. The current study aimed to evaluate the effects of doxorubicin on SDF1/CXCR4 pathway via in silico molecular docking and simulation studies. Remarkably, heparin binding site of SDF1at LEU: 29 might be preoccupied by doxorubicin leads to poor expression because SDF1 activity heavily depends on its binding sites. On the other hand, active sites of CXCR4 at ASP: 171 and GLU: 288 also engaged by dox, leading to the assumption that doxorubicin restrict the receptor activity. Additionally, the interaction of doxorubicin at the proton acceptor site and ATP binding sites of VEGFR1, including ASP: 1022, GLY: 836, ALE: 837 and PHE: 838, suppresses the function of the receptor in the MAPK1/ERK2 and AKT1 signaling cascades. The co-expressing factor involved in SDF1/CXCR4 like VEGFR2, ANGPT1 and SHIP2 were also affected by specific amino acid interactions. This induces alterations in several vital biochemical pathways, leading to metabolic chaos. Taken together, it is hypothesize that doxorubicin-mediated functional inactivity of SDF1 via its receptor CXCR4 and VEGFR1 impaired the cardiac EPCs regulation on angiogenesis and vascularization. (2025), (DergiPark). All rights reserved. -
Tailored Optoelectronic Materials: DES-Modified MWCNTs in PVA Matrix for Advanced Polymeric Films
Integrating optoelectronic functionalities with advanced materials offers exciting potential for novel composite systems. This study investigates the synthesis, characterization, and optoelectronic applications of polyvinyl alcohol (PVA) films incorporating multi-walled carbon nanotubes (MWCNTs) surface-modified with choline chloride-urea (1:2) deep eutectic solvents (DES), known as Reline. Dispersion of Reline-enhanced MWCNT within the PVA matrix is meticulously described. DES-grafted MWCNTs demonstrate improved solubility, leading to superior dispersion within the polymer, confirmed by scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). The influence of Reline-grafted MWCNT loading on the films' optoelectronic properties, including optical absorbance, bandgap, and electrical conductivity, is systematically analyzed. Results show that DES-grafted MWCNTs significantly enhance these properties, indicating strong potential for these composites in optoelectronic devices such as solar cells, photovoltaics, photodetectors, and light-emitting devices. 2025 by the authors. -
Diet of the Dattatreya night frog Nyctibatrachus dattatreyaensis from the central Western Ghats, India
The Dattatreya night frog Nyctibatrachus dattatreyaensis, found in the Chandra Drona Parvatha massif, is a stream-dwelling, evolutionarily distinct and globally Endangered species threatened by increasing habitat loss and alteration. We examined the stomach contents of 104 individuals, from ten different streams, of which 42 had prey in their stomachs. The prey items were in 12 orders across 4 classes, mainly dipterans, hymenopterans and lepidopterans. The frog exhibits a passive foraging mode, has a moderate trophic niche breadth (Bst = 0.43), and may have a preference for agile prey. Apart from this, there were plant materials, sand grains and plastic debris found in the stomach contents, with 0.82 mm3 of plastic debris found in eight individuals across three streams. The presence of plastic debris indicates the impact of anthropogenic activities leading to a form of habitat degradation. The data presented indicates the need for immediate and efficient conservation strategies to be put in place for this understudied species. 2025 British Herpetological Society. All rights reserved. -
Immersive Virtual Learning Experiences of Senior Secondary School Students from India and Russia: A Mixed Method Study
Virtual Reality (VR) provides an immersive learning (IL) experience by simulating real-world scenarios that bridge the gap between theory and application. VR simulations are interactive and enhance student engagement across a range of concepts, from simple to complex. India and Russia share similar cultural and historical backgrounds, and both are committed to creating a multipolar world. Both are large developing countries with several strategic partnerships and international cooperation. Hence, this study aims to capture the learning experiences of internationally paired students in an IL environment and their attitudes towards IL environments, to mutually contribute to teaching and learn in these countries. Students experienced immersive learning through stand-alone head-mounted virtual reality cameras with a controller. The study employed a mixed-methods research design involving a quantitative and qualitative explanatory approach. Researchers paired 100 senior secondary school students from Russia (n = 50) and India (n = 50) and exposed them to virtual IL experiences. Researchers used the user-experience IL environment scale, the VR-IL environment attitude scale, and an interview guide to collect the data of the study. Quantitative data were analyzed using descriptive statistics, a correlation test, and regression. Qualitative data were analyzed through narrative thematic analysis. Researchers triangulated the IL experiences measured through quantitative and qualitative methods. The study found a positive correlation between IL experiences and attitude towards the IL environment. Further, IL experiences accounted for 43.5% of positive attitudes towards the IL environment. The qualitative analysis revealed both positive and negative aspects of VR-IL environment experiences. The study's findings add value to the cognitive-affective theory of learning with media, as it includes knowledge construction, emotional connection, and motivation for learning. Future studies may explore the benefits of the IL environment with artificial intelligence (AI) and generative AI towards teaching and learning. (2024), (California State University). All Rights Reserved. -
Thermodynamic Analysis of Marangoni Convection in Magnetized Nanofluid
This article explores the optimization of heat transport in a magnetohydrodynamic nanofluid flow with mixed Marangoni convection by using the Response Surface Methodology. The convective flow is studied with external magnetism, radiative heat flux, and buoyancy. An internal heat absorption through the permeable surface is also taken into account. The governing system includes the continuity equation, Navier-Stokes momentum equation, and the conservation of energy equations, approximated by the Prandtl boundary layer theory. The entropy generation in the thermodynamic system is evaluated. Experimental data (Corcione models) is used to model the single-phase alumina-water nanofluid. The numerical solution for the highly nonlinear differential system is obtained via Ralstons algorithm. It is observed that the applied magnetic field leads to a higher entropy generation which is engendered by the Lorentz force within the fluid system. The thermal radiation leads to a higher Bejan number, indicating the importance of the irreversibility of heat transport. Also, the heat absorption process via a permeable surface can be employed to regulate the thermal field. An optimized Nusselt number of 13.4 is obtained at the high levels of radiation, injection, and heat sink parameters. The modelled fluid flow scenario is often seen in drying, coating,and heat exchange processes, especially in microgravity environments. 2025 The Authors. -
Development and Validation of a Framework to Identify High Potential Employees in Organizations
The present study aimed to develop and validate a multidimensional framework for identifying high-potential employees (hi-pots) to support succession planning and leadership development in organizations. A sequential exploratory mixed-methods approach was employed. In the qualitative phase, semi-structured interviews with seven organizational leaders were conducted to identify key traits and behaviors of hi-pots. The subsequent quantitative phase involved 276 managerial employees who responded to a newly developed measurement scale. The data were subjected to statistical validation to reinforce the proposed model. The validated framework comprises three dimensions: Foundation, growth, and career. The foundation dimension includes inherent traits such as optimism and sociability. The growth dimension, encompassing promotability, adaptability, and proactiveness, showed the strongest predictive power for leadership readiness. The career dimension involves performance-based competencies like technical proficiency and time management. Among these, the growth dimension emerged as the most influential for leadership potential. Organizations can utilize this framework for structured talent identification, improving leadership pipelines, and strategic HR planning. 2026 Econjournals. All rights reserved. -
Do Investors Tend to Overreact when Investing in Clean Energy Stock Indices?
Due to climate change, investors are increasingly interested in clean energy stocks attracting many investors due to clean energy prospects. This paper analyses investor overreactions to long-term prices in various clean energy stock indices, such as Clean Energy Fuels (CLNE), Global Clean Energy (GCEI), as well as the Dow Jones Industrials (DJI) stock index, over the period from 24 February 2022 to 23 May 2024. The results show that the Global Clean Energy (GCEI) clean energy stock index rejects H0 at the 16-day lag at a significance level of 1%; similarly, the Clean Energy Fuels (CLNE) index rejects the null hypothesis at lags 8, 9, 10, 11 and 12 days, both indices show negative serial autocorrelation, which means that price movements are not entirely random and are influenced by prior price movements. This evidence could mean that investors overreact to the information that reaches the market. On the other hand, the ETF (PWYF) and the Dow Jones Industrial Stock Index (DJI) show that the random walk hypothesis has not been rejected. In other words, these markets show that they are in equilibrium and that the existence of exaggerated reactions on the part of investors is not significant. The answer to the research question was partially accepted, so the Russian invasion of Ukraine in 2022 led to the partial presence of overreactions in these stock indices. In conclusion, investors operating in these markets should exercise caution and consider their risk tolerance before investing. Investors should, therefore, continue to monitor market trends and adjust their investment strategies accordingly. 2025, Econjournals. All rights reserved. -
Flexural performance of FDM-fabricated PLA composites reinforced with short carbon fiber
Adding short carbon fiber reinforcement to thermoplastic matrices can improve the mechanical performance of additively manufactured polymer-based composites. This work examines the flexural behavior of Fused Deposition Modeling (FDM)-produced polylactic acid (PLA)-based composites enhanced by short carbon fibers at 3 wt% and 6 wt%. For comparison, unreinforced PLA specimens were also fabricated under identical processing conditions. All the samples were tested for flexural strength using a three-point bend test, following the ASTM standards for polymer composites. The results showed a clear improvement in strength as the reinforcement content increased. The PLA composite with the 3% short carbon fiber reinforcement showed a noticeable increase in load-bearing ability, while the 6% reinforced composite had an impressive 88% higher flexural strength than the plain PLA. To examine how the materials failed, SEM has been utilized to assess the samples' fractured surfaces. 2026, Gruppo Italiano Frattura. All rights reserved. -
Assessing the environmental consequences of artificial illumination on marine ecosystems: Legal and ecological perspectives
Fishing has been traditionally practiced using sustainable methods and eco- friendly techniques which ensured the conservation of fish diversity and its population. The traditional fishing techniques used were hand-lining, spearfishing, gleaming, harpoons and spears. However, with technological advancements LED fishing techniques has gained prevalence among fishermen due to their high-intensity LED lights (Light-Emitting Diodes) for fishing. This method enables them to catch fish in larger quantities. Such LED lights can penetrate deeper into the water and illuminate larger areas than traditional methods, disrupting the natural behavior of marine organisms. As a result, this practice leads to a significant decrease in fish populations, adversely affecting marine ecosystems. Although LED fishing offers certain advantages, such as improved efficiency and reduced fuel consumption, it raises serious concerns regarding its socio-legal and environmental impact and highlights the need for effective legal and regulatory frameworks. In this background, the current study explores the socio-economic impacts on fishing communities, which are disproportionately affected by the introduction of this technology. Further, the research delves into the ecological consequences of LED fishing, including its potential to disrupt fish behaviour, alter food chains, and damage sensitive marine ecosystems. It will also analyze the legal and regulatory challenges associated with managing LED fishing and examine the existing Legal framework that is applicable in international and national Contexts. Finally, the paper will propose a framework for sustainable LED fishing. Copyright (c) 2026 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. -
Cultural resonance in the brain: EEG-Based insights into emotional engagement with festive imagery
Festive imagery is fundamental in constructing cultural identity, affective resonance, and collective memory. The neural engagement patterns in Kolkata individuals, upon viewing familiar and unfamiliar festive images, have been studied by using electroencephalography (EEG) as an on-line, non-invasive indicator of neural activity. In particular, the study compares participants' neural reactions to images of the Onam festival of Keralaa culturally unfamiliar festivalto those of Durga Puja celebrations outside Kolkata, which, although culturally familiar, are not immediately geographically specific. The EEG parameters that were assessed were cognitive load, emotional arousal, neural stimulation, and frontal lobe activation linked to attention and affective processing. Results show that novel but colorful festive images like Onam had greater and longer-lasting cognitive and emotional activation than familiar Durga Puja images. Such increased activation was associated with augmented beta and gamma wave activity, reflecting high arousal and attention, as well as marked frontal lobe activation. The findings indicate that novelty, visual symbolism, and the richness of cultural representations have a central role to play in the modulation of cognitive processing and emotional resonance, even among culturally homogenous populations. The research adds to the growing body of literature in neuroaesthetics and cultural neuroscience by demonstrating how culturally unfamiliar but symbolically dense images can elicit profound cognitive and affective responses. These findings have implications for intercultural communication, visual media design, and festival tourism promotion, where strategic deployment of culturally diverse imagery can increase audience engagement and emotional resonance. Copyright (c) 2026 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. -
Neurocognitive modeling of emotional states using EEG and hidden markov models: A multidisciplinary approach
This interdisciplinary research cuts computational modeling and cognitive neuroscience approaches with the intention of studying dynamic emotional involvement with multimedia stimuli via HMM analysis of EEG data. In particular, the paper deals with advertisements that target excitement and love-type emotions, setting forth new paradigms for understanding the building and modulation of emotional experience across time in the human brain. EEG parameters such as amplitude, arousal, and frontal activation were studied as markers of neural reactions to emotionally arousing content. The neural markers are tracked over time to record the changes in emotional engagement. The HMMs use identifies hidden neural states and their probabilistic transitions, making the temporal description of neural dynamics during emotional processing rich and nuanced. The analytical approach provides identifiable neural patterns for excitement and love stimuli distinguished in terms of arousal, spectral amplitude, and hemispheric asymmetry in frontal activation. Due to these distinctions, we ascertain that the brain processes different affective tones distinctly, shedding light on the intricacies of emotion perception and its immediate brain counterpart. Using the results, a predictive HMM model is presented to model emotional changes when individuals are subjected to effective multimedia stimuli. The model serves as a bridge to further real-time developments in human-computer interaction, adaptive e-learning, immersive media conception, and affective UX (user experience) optimization. In other words, this enables the system to detect shifts in the user's emotions automatically and adapt content accordingly, representing truly affect-sensitive technologies. Amalgamating computational modeling with neurophysiological measurement, this study contributes to the birth of emotion-aware technology that can be dynamically responsive to the users' current affective state, thus harnessing engagement, personalization, and user satisfaction as opportunities. It builds on the interdisciplinary discourse between cognitive neuroscience, affective computing, and computational psychology to serve as a methodological guideline for future investigations into emotional dynamics and brain-computer interfaces (BCIs), as well as neuroadaptive technology. It makes a case for the relevance of temporal modeling in decoding emotional cognition and therefore advocates the continued employment of machine-learning approaches in brain activity and human affective behaviour studies. Copyright (c) 2025 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. -
Development of an integrated well-being programme for micro, small-and medium-sized enterprise workers in India: A technical note
Workers in Indias micro, small- and medium-sized enterprise (MSME) sector often face a convergence of occupational risks, including long working hours, physical strain, economic insecurity, and limited access to health resources. Despite the sectors critical contribution to national productivity, structured programs addressing the holistic well-being of MSME workers remain scarce. This technical note outlines the development of an integrated well-being intervention designed to enhance physical, psychological, and social health among MSME workers across diverse Indian contexts. Drawing on both indigenous and global practices, the program combines simple yoga-based movements, breathing exercises, and mindfulness techniques with Western approaches such as Jacobsons Progressive Muscular Relaxation (JPMR). The intervention is delivered over two phasesa 21-day facilitator-led group session followed by a 21-day self-practice period to support skill development and habit formation. Designed for scalability and accessibility, the content uses culturally relevant language and experiential activities to ensure engagement in low-literacy and resource-limited settings. This note details the theoretical grounding, content structure, and delivery framework of the program, offering a practical, context-sensitive model that can be adapted for workplace well-being initiatives within the Indian MSME sector. Copyright (c) 2025 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.