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Developing a global sustainable electricity use index using the pressure-state-response framework
This study analyse and compare the sustainable electricity usage in 60 countries listed on the official websites of World Energy Consumption Statistics and Climate Bond Initiative. The study also analyses the impact of increased usage of sustainable electricity on the economies' dependence on non-renewable energy sources in the evaluation system. We used a standard index system based on the Pressure-State Response (PSR) model to measure global sustainable electricity usage. Model results convey that Norway is the best performer in sustainable electricity usage, while several European countries display commendable scores, confirming their commitment to sustainable electricity practices. On the other hand, despite being the leading economies in terms of GDP, major economies such as the United States, China, Japan, and India have underperformed compared to others in the evaluation system. The study employs regression techniques to explain the relationship between sustainable electricity usage and non-renewable energy dependence. Results confirm a negative relationship between the variables, indicating the role of sustainable energy practices in reducing fossil fuel consumption. It emphasizes the urgency of a balanced approach to economic growth and natural resource usage to support a green future. 2024 Elsevier Ltd -
Phytochemicals in Lemongrass (Cymbopogon citratus) Contributing to Growth and Disease Resistance in Goldfish (Carassius auratus Linn. 1758): Integration of Molecular Docking and Statistical Analyses
The ornamental fish industry has experienced significant growth with species like goldfish (Carassius auratus) gaining popularity for their vibrant appearance and ease of care. However, bacterial infections, particularly those caused by Aeromonas hydrophila, pose a significant threat to fish health and market value. In this study, visibly diseased goldfish exhibiting symptoms such as fin rot, black spots, tail rotting and skin lesions were divided into control and treated groups. The treated group was fed lemongrass (Cymbopogon citratus)-coated pellets, while the control group received standard feed. Over a three-week trial, visual improvements, including the healing of fin rot were documented, demonstrating the effectiveness of lemongrass-enhanced feed in promoting recovery and growth. GC-MS analysis of fresh lemongrass leaves identified key bioactive compounds, including citral, tetra decanoic acid, trans-verbenol and 1-undecanol, known for their antimicrobial properties. These findings confirmed the presence of phytochemicals with potential therapeutic applications against bacterial infections. Molecular docking studies further evaluated the interactions of prominent lemongrass phytochemicals: Procyanidin B2, Diosmin, Catechin and Tricin, with A. hydrophila outer membrane protein (3OD9). The results demonstrated strong binding affinities with Procyanidin B2 showing the highest (-8.0 kcal/mol), followed by Diosmin (-7.8 kcal/mol), Catechin (-7.6 kcal/mol) and Tricin (-7.6 kcal/mol), indicating their potential to inhibit bacterial pathogenicity. This study highlights the dual role of lemongrass as a natural growth promoter and antibacterial agent, emphasizing its potential as a sustainable and eco-friendly alternative to antibiotics in aquaculture. By effectively managing bacterial infections and improving fish health, lemongrass offers a promising solution for enhancing sustainability in aquaculture. 2026, World Researchers Associations. All rights reserved. -
The role of psychological capital in shaping climate anxiety across generations
Background: Climate change has transitioned from a distant environmental issue to an immediate psychological reality that profoundly affects how individuals perceive their future and well-being. This study investigates generational differences in climate anxiety and examines the role of psychological capital (PsyCap) as a potential protective resource through the lens of Environmental Identity Theory (EIT). Methods: A cross-sectional survey was conducted among 384 participants in Kerala, India, comprising Generation X (33.6%), Millennials (29.9%), and Generation Z (36.5%). Climate anxiety was measured using the Climate Anxiety Scale (Clayton & Karazsia, 2020), and PsyCap was assessed through the PCQ-12, encompassing hope, efficacy, resilience, and optimism. Data were analyzed using ANOVA and multiple regression, with effect sizes and confidence intervals reported. Results: Significant generational differences emerged for both cognitiveemotional impairment (F(2,381) = 3.83, p =.023) and functional impairment (F(2,381) = 6.15, p =.002). Gen Z reported significantly higher anxiety levels than Millennials (p =.045, d = ? 0.29*) and Gen X (p =.011, d = ? 0.35*). Regression analyses indicated that PsyCap and generation jointly predicted cognitiveemotional (R = 0.04, p =.008) and functional impairments (R = 0.056, p =.001), with self-efficacy emerging as a significant negatively associated with functional impairment (B = ? 0.12, p =.043). Conclusion: Gen Z experiences greater emotional and functional impacts of climate anxiety compared to older cohorts, while self-efficacy offers a modest buffering effect for functional impairment. These findings underscore the need for interventions that strengthen psychological resources and adaptive coping to mitigate climate-related distress among younger populations. The Author(s) 2026. -
Market Trends in Quantum-Inspired Soft Computing for Intelligent Data Processing
Quantum-Inspired Soft Computing (QISC) is an advanced concept in computational intelligence in the current era of hi-technology, which has been adapted to principles underpinning quantum mechanics, including superposition and entanglement in the conven tional computing systems. The current chapter aims to identify the growing trends in the market environment concerning QISC for intelligence data processing, specifying the aspects of its applicability, costuse ratio, and adaptability among different industries. The increased need for the utilization of enhanced methods of data handling arising from big data and AI progress has made QISC viable for handling optimization problems, machine learning, and predictive modeling in addition to quantum computing. Major business sectors, such as finance, health care, supply chain, and energy sectors, have benefited from the use of QISC to enhance operational management, decision making, and system reliability. This chapter also discusses how leading players such as Microsoft, IBM, and DWave are in the course of incorporating QISC in cloud environments as well as in hybrid computing systems. Advancements in hardware, such as GPUs and quantum-inspired processors, and in algorithms, such as tensor networks and reinforcement learning, have further extended the usage of QISC. However, there are issues such as standardization, interdisciplinary qualified staff, and computational complexity, which remain important unsolved tasks for further investigation and cooperation. This chapter ends by briefly pointing out new directions for how QISC can work with AI for NLP and real-time analysis. Understanding QISC in terms of its current market and its positive impact on the future of computational intelligence is the focus of this chapter, which focuses on current market trends. Analyzing key trends and the degree of industry adoption, the research findings provide useful perspectives for academic, practical, and policy purposes. 2026 Scrivener Publishing LLC. -
Integrating Explainability and Fairness in Credit Risk Prediction: A Hybrid Approach Using Tabnet, LightGBM, SHAP, and Counterfactual Explanations on the FICO Dataset
Transparent and fair credit risk assessment is essential for responsible lending in modern financial systems. This paper presents an interpretable and ethically grounded machine learning framework for loan default prediction using the FICO Explainability Challenge dataset. We combine LightGBM, a high-performing gradient boosting model for tabular data, with TabNet, a deep learning architecture that provides intrinsic interpretability through attentive feature selection. To enhance transparency, SHapley Additive exPlanations (SHAP) are employed for global and local feature attribution, while counterfactual explanations generated using the DiCE framework offer actionable recourse. Fairness is evaluated and mitigated using IBM's AI Fairness 360 toolkit. Experimental results demonstrate that the proposed hybrid approach achieves strong predictive performance while ensuring interpretability and fairness, making it suitable for trustworthy and regulation-compliant credit risk modeling. 2026 IEEE. -
FinTech for Sustainable Financial Market Innovation: The FinTech Transformation of Traditional Finance
Fintech is transforming the traditional banking industry, resulting in creative solutions that enhance financial market sustainability. This section examines how financial technologies like blockchain, AI, mobile banking, and digital payment systems are changing banking operations to make them more transparent, efficient, and accessible. It also examines how Fintech may drive long-term financial innovation by increasing financial inclusion, lowering operating costs, and encouraging green banking activities. This chapter uses case studies and practical examples to investigate the influence of Fintech on the banking system, emphasizing green lending, digital currencies, and sustainable investing platforms. Adopting new technology presents operational and regulatory problems for banks. The global financial system is becoming increasingly dependent on sustainability, as seen by how banks use Fintech to meet the growing demands of ESG standards. This section examines how digital banking platforms, AI risk assessment algorithms, and blockchain green bonds might help banks allocate resources more responsibly. By adopting these technologies, banks can reduce their environmental impact while meeting the rising demand for ethical and accountable financial services. 2026 Nova Science Publishers, Inc. -
Augmented Reality-Enabled Education for Middle Schools
Augmented reality acts as an add-on to teachers while teaching students, and this helps the teachers and students to have an interactive session. Augmented realitys usage in education is cited as one of the major changes in the educational sector. Thus, the work carried out makes a positive impact in the educational industry. Augmented reality provides features like image recogntion, motion tracking, facial recognition, plane detection, etc., to provide interactive sessions. Simultaneous localization and mapping and concurrent odometry and mapping have proved to be efficient algorithms for augmented reality on mobile devices. The work carried out allows students to view interactive newspapers while reading a specific article. It also allows them to view a dynamic three-dimensional model of the solar system on their smartphone using augmented reality. 2020, Springer Nature Singapore Pte Ltd. -
Measuring Financial Inclusion in India: An Approach
In light of the COVID-19-induced financial crisis, the need for robust financial services and networks has become more apparent than ever, which necessitated the accurate measurement of the breadth of financial inclusion in India. First, the study conducted a detailed critical review of the current indices and their construction methodology. Then, we created a financial inclusion index for India by accounting for the flaws existing in the current indices. The primary contribution of this study to the existing literature is the new approach it proposed for the assignment of weights in the financial inclusion index. Based on this new financial inclusion index, the study concluded that Indias Southern states and union territories showed better financial inclusion. In contrast, the traditionally backward BIMARU states of Bihar, Madhya Pradesh, Rajasthan, and Uttar Pradesh, and a few of the North Eastern states of India, lagged. The study also provided a refined and inclusive definition of financial inclusion based on its new approach to index creation. 2023, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Catalyzing Security and Efficiency: Blockchains Integration with IoT and Cloud Computing
Blockchain technology is a system that combines a number of computer technologies, encryption, shared storage, namely intelligent contracts, consensus processes, and peer-to-peer (P2P) networks. This research project begins with a description of the architecture of blockchains, followed by a comparison of the various consensus techniques used across various blockchain implementations. This studys scope includes a thorough analysis of the entire blockchain ecosystem. Our investigation also explores the complexity of the consensus models built into different blockchain platforms. This research painstakingly dissects these elements to pinpoint crucial elements that are essential for propelling the adoption and development of blockchain technology. In conclusion, our research corrects misconceptions about blockchains expansive potential and helps to direct the development of the technology across a wide range of industries. These results are significant for determining the future direction of blockchains enduring influence. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Unheard and Unseen: Exploring the Disenfranchisement of Perinatal Loss in North-Indian Men
Mental distress is recognised as common following perinatal loss. But often, existing literature and bereavement care standards focus on women, leaving a gap in understanding mens grief. This qualitative study examined the emotional experiences of males from some Northern states of India, who had experienced perinatal loss, with a focus on grief disenfranchisement. Eleven participants were interviewed using a semi-structured guide. Thematic analysis unveiled themes on the intersection of religiosity and grief, social structuring of grief patterns, gender-based grieving, inhibited expression of grief in men, disenfranchisement of grief, self-focused coping, coping with the help of others, and interpersonal barriers to emotional disclosure. The findings provide valuable insights, helping mental health practitioners better understand mens experiences of perinatal loss and develop more effective support strategies. 2024 SAGE Publications. -
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Crafting an experiencescape for sustainable cultural tourism: A case study of udaipur's craft village "Shilpgram"
India, known for its rich and varied cultural heritage, hosts numerous fairs and festivals as vibrant platforms to showcase its diversity. Events like the Kala Ghoda Arts Festival, Ellora-Ajanta International Festival, Surajkund Crafts Mela, Pushkar Fair, and many others celebrate the country's artistic and cultural wealth. This book chapter explores sustainable culture and heritage development in Udaipur's craft village, 'Shilpgram.' The village hosts an annual craft fair during the peak tourist season, attracting artists across India to showcase their unique crafts, folk dances, and paintings. This chapter assesses Shilpgram's feasibility as an experiencescape model using a case study method. Interviews with key stakeholders provided insight into the destination's difficulties, strengths, and best practices. The study adds to our understanding of cultural locations' responsibilities in cultural tourism by balancing historical preservation with current expectations. 2023, IGI Global. All rights reserved. -
Sustainability in hospitality: The pathway to destination well-being in the "City of Lakes" Udaipur
With the rising popularity and a surge in demand for the "City of Lakes" Udaipur, the lake ecosystem has become vulnerable to various anthropogenic activities and pollution. The restricted structure of hotels on the lakefront faces various challenges in maintaining environmental regulations. This chapter explores hotels on the lakeside in Udaipur, which includes heritage hotels and modern accommodations, and their sustainability practices, such as energy efficiency, waste management, water conservation, and eco-design in hospitality architecture. Best practices in Udaipur's hospitality industry are explored through observation, document analysis, and interviews. The chapter establishes how circular economy builds environmental quality while regenerating resources. The implications of the study indicate a transformation of tourism governance in Udaipur by local authorities and academicians, which indeed can contribute to achieving a destination's well-being by addressing the challenges posed by the thriving tourism economy. 2024, IGI Global. -
Unheard and Unseen: Exploring the Disenfranchisement of Perinatal Loss in North-Indian Men
Mental distress is recognised as common following perinatal loss. But often, existing literature and bereavement care standards focus on women, leaving a gap in understanding mens grief. This qualitative study examined the emotional experiences of males from some Northern states of India, who had experienced perinatal loss, with a focus on grief disenfranchisement. Eleven participants were interviewed using a semi-structured guide. Thematic analysis unveiled themes on the intersection of religiosity and grief, social structuring of grief patterns, gender-based grieving, inhibited expression of grief in men, disenfranchisement of grief, self-focused coping, coping with the help of others, and interpersonal barriers to emotional disclosure. The findings provide valuable insights, helping mental health practitioners better understand mens experiences of perinatal loss and develop more effective support strategies. 2024 SAGE Publications. -
Chatbot Service Quality in Banking : Analyzing Indian Banking Customer Perceptions and Influence on Customer Satisfaction and Value
Purpose: The study has two objectives: first, to determine the quality of chatbot services provided by Indian banks; second, to assess the influence of chatbot service quality variables on customer satisfaction and customer value. Research Methodology: The study used a quantitative methodology, selecting individuals at random from a group of Indian banking clients. We used a questionnaire to collect data from the selected sample as part of a causal research investigation. We made use of SPSS and Python for this analysis. Customer satisfaction and value were taken into account as the dependent variables in our study. The seven elements of service qualityfunctionality, convenience, security, design, customization, enjoyment, and assurancemade up the independent variables. Findings: According to this study, client satisfaction and value were significantly shaped by the quality of the services provided. Customers value was significantly impacted by functionality and enjoyment, and their satisfaction was greatly influenced by assurance, design, and personalization. The unexpected negative impact assurance had on customer value is noteworthy and calls for more research. Practical Implications: In the highly competitive banking industry, this research has important ramifications for banks. It highlighted how important service quality is, which led banks to give priority to customer pleasure and think about making strategic changes. Banks could obtain a competitive advantage by improving the quality of their services, improving chatbot services, and implementing a customer-centric strategy by utilizing the research findings that have been presented. Our research helped banks evolve with the needs of their customers in mind, enabling them to gain credibility, repeat business, and long-term success in the ever-changing banking services market. Originality/Value: This study examined how consumers in Indian banks perceive the value and satisfaction of chatbot services and how they use them. The study provided useful recommendations and concepts to improve the general consumer experience. 2024, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
The linkage of sustainable development and spirituality at workspace from the perspectives of university teachers
Purpose Sustainability and spirituality are interrelated concepts that hold immense importance in todays world. The purpose of this study is to explore the influence of spirituality (and its dimensions) on sustainability in the educational sector, in addition to examining the role of socio-demographic factors. Design/methodology/approach A quantitative research design was employed using a structured questionnaire. The data were analysed through independent t-tests, analysis of variance, correlation analysis and structural equation modelling (SEM) to assess relationships between socio-demographic factors, workspace spirituality and sustainability. Findings The study found no significant differences in sustainability levels across gender, age or years of work experience. However, significant differences in workspace spirituality were observed between males and females, and across different age groups and experience levels. Positive correlations were found between workspace spirituality and dimensions such as compassion, transcendence and meaningful work, while mindfulness showed a negative correlation. SEM results further indicated that compassion and meaningful work positively influence sustainability, while mindfulness negatively affects it. Transcendence, however, showed no significant impact. Research limitations/implications The study highlights the deep interconnection between spirituality and sustainability and how socio-demographic factors shape this relationship. It provides insights for educational institutions to foster spiritually enriching environments that not only enhance academic outcomes but also promote ethical awareness, personal growth and environmental responsibility. Originality/value This research uniquely bridges gaps between spirituality, sustainability and employee demographics, offering practical implications for creating spiritually fulfilling and sustainable workspaces in the educational sector. 2026 Emerald Publishing Limited -
Highly Luminescent MOF and Its in Situ Fabricated Sustainable Corn Starch Gel Composite as a Fluoro-Switchable Reversible Sensor Triggered by Antibiotics and Oxo-Anions
Frequent use of antibiotics and the growth of industry lead to the pollution of several natural resources which is one of the major consequences for fatality to human health. Exploration of smart sensing materials is highly anticipated for ultrasensitive detection of those hazardous organics. The robust porous hydrogen bonded network encompassing a free-NH2 moiety, Zn(II)-based metal-organic framework (MOF) (1), is used for the selective detection of antibiotics and toxic oxo-anions at the ppb level. The framework is able to detect the electronically dissimilar antibiotic sulfadiazine and nitrofurazone via fluorescence "turn-on"and "turn-off"processes, respectively. The antibiotic-triggered reversible fluoro-switching phenomena (fluorescence "on-off-on") are also observed by using the fluorimetric method. An extensive theoretical investigation was performed to establish the fluoro-switching response of 1, triggered by a class of antibiotics and also the sensing of oxo-anions. This investigation reveals that the interchange of the HOMO-LUMO energy levels of fluorophore and analytes is responsible for such a fluoro-switchable sensing activity. Sensor 1 showed the versatile detection ability which is reflected by the detection of a carcinogenic nitro-group-containing drug "roxarsone". In view of the sustainable environment along with quick-responsive merit of 1, an in situ MOF gel composite (1@CS; CS = corn starch) is prepared using 1 and CS due to its useful potential features such as biocompatibility, toxicologically innocuous, good flexibility, and low commercial price. The MOF composite exhibited visual detection of the above analytes as well as antibiotic-triggered reversible fluoro-switchable colorimetric "on-off-on"response. Therefore, 1@CS represents a promising smart sensing material for monitoring of the antibiotics and oxo-anions, particularly appropriate for the real-field analysis of carcinogenic drug molecule "roxarsone"in food specimens. 2022 American Chemical Society. -
Optimized trimetallic CoNiFe phospho-boride electrocatalyst for overall seawater electrolysis
Utilizing abundant seawater for hydrogen production by electrolysis poses new challenges to electrocatalyst performance, demanding effectiveness, resilience, and selectivity for oxygen evolution reactions (OER) over undesired reactions in harsh saline conditions. Herein, trimetallic phospho-boride, CoNiFePB, was synthesized via a chemical reduction method by carefully tuning the concentrations of all elements for overall seawater splitting. The optimized CoNiFePB demonstrated superior OER activity, requiring only 239 mV to achieve 10 mA/cm2 in alkaline simulated seawater, outperforming bimetallic configurations (CoNiPB and CoFePB). The enhancement in hydrogen evolution reaction (HER) activity was attained by adjusting the B/P molar ratio in CoNiFePB, resulting in a low overpotential of 137 mV. A comprehensive kinetic analysis revealed that Ni and Fe play crucial roles in enhancing the adsorption and desorption of the reactant and product, respectively, while Co serves as the active site for intermediate formation, collectively boosting the activity of the trimetallic CoNiFePB. While the electron modulation achieved by B and P triggers the formation of active sites and avoids chloride ion oxidation. The bifunctional CoNiFePB catalyst deposited on Ni foam (NF) demonstrated excellent durability for 10,000 cycles and maintained performance for 70 h in chronoamperometric testing at a high current density of 0.7 A/cm2, emphasizing its long-term stability in alkaline seawater. When integrated into an advanced seawater electrolyzer with a zero-gap assembly, CoNiFePB/NF achieved a current density of 2 A/cm2 at a cell voltage of approximately 2.43 V in alkaline natural seawater. These findings provide significant insights into electrocatalysis for seawater splitting with promising implications for commercial applications. 2025 Elsevier B.V. -
Bridging Science and Spirituality: Investigating the Effects of OM Chanting on Brain Waves
In Hindu tradition, the syllable "OM" holds significant spiritual and cultural value in Hindu tradition and is believed to produce positive psychological and physiological effects. Despite its prominence in spiritual practices, the neurophysiological basis for these benefits remains underexplored. In this study, electroencephalography (EEG), a non-invasive method for measuring electrical activity in the cerebral cortex, was employed to investigate the physical changes in brain wave patterns that occur when listening to OM chanting. Five frequency bands, namely delta, theta, alpha, beta, and gamma, are associated with brainwaves recorded through EEG, which define different states of cognitive and emotional nature. With these, this research analyzes EEG signals before and after chanting to identify and quantify changes, and to discuss the therapeutic implications. Several signal processing techniques, such as time and frequency domain analysis, assess variations in amplitude, frequency, and coherence across different brain regions. These findings show an increase in alpha amplitudes (34.2%) and an 85.4% improvement in the theta/beta ratio, related to relaxation, emotional regulation, and additional focus, as well as a decrease in beta waves, linked to stress and cognitive overload. This would show stronger neural integration between the brain hemispheres. The OM chanting evoked these results as a possible neurotherapeutic tool for stress management and cognitive enhancement. In bridging ancient spiritual practices with modern neuroscience, this study provides information on how such seemingly nonsensical meditations as OM chanting can enhance brain function, which is favorable for the third Sustainable Development Goal (SDG) of the United Nations, regarding the goal of healthy life and wellbeing throughout all ages. Further research should be done into these effects in different populations and over long periods to confirm that this is a long-term therapeutic effect. 2025, Sakarya University. All rights reserved. -
Combined weighted feature extraction and deep learning approach for chronic obstructive pulmonary disease classification using electromyography
The COVID-19 outbreak has led to a rise in respiratory disease-related deaths, including Chronic Obstructive Pulmonary Disease (COPD). Early diagnosis of COPD is crucial, but it can be challenging to distinguish between different chronic pulmonary diseases due to their similar symptoms, leading to misdiagnosis and time-consuming manual inspections. To address this issue, this paper explores the use of a deep learning model to differentiate COPD from other lung diseases using lung sound captured during Electromyography (EMG). The model includes steps such as noise removal, data augmentation, combined weighted feature extraction, and learning. The model's efficacy was evaluated using various metrics, including accuracy, precision, recall, F1-score, kappa coefficient, and Matthews correlation coefficient (MCC), with and without augmentation. The results show that the model achieved 93% accuracy and outperformed other existing state-of-the-art deep learning models, increasing the robustness of clinical decision-making. The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management 2023.