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Wind Power Density Projections for the Indian Offshore Region: Annual and Seasonal Changes
No full textOffshore wind energy offers a sustainable solution for India’s transition from fossil fuels. Understanding how wind resources may vary under future climate conditions is essential for effective planning and development. This study assesses projected offshore wind power density (WPD) in the Indian offshore region using daily wind speeds from 13 CMIP6 global climate models under SSP2-4.5 and SSP5-8.5 scenarios. Quantile mapping bias-correction, using ERA5 reanalysis as the reference, was applied to improve model performance, and multi-model ensemble results were analysed for historical (1990–2014) and future periods. The findings reveal distinct spatial and seasonal variability in future WPD. A dipole-like pattern persists, with WPD reductions in the northwest Arabian Sea and moderate increases along the southwest coast of India, particularly during the monsoon season. Under SSP5-8.5, non-monsoon seasons show widespread declines by 2100. These results highlight the importance of incorporating climate-responsive planning and robust bias-correction practices to ensure sustainable offshore wind development in India
Understanding Concrete Damages: Causes, Contributing Factors, and Integrity Assessment
No full textConcrete, one of the most widely used construction materials, is susceptible to various defects
that compromise its durability and structural integrity. Deterioration results from a combination
of chemical, physical, and environmental factors, including acid attack, chloride penetration,
sulfate reactions, abrasion, erosion, fire exposure, and shrinkage cracks. Corrosive agents such
as CO₂-rich water, salts, and alkalis accelerate degradation, while physical damage further
exacerbates structural deterioration. Additionally, chloride ions reduce the pitting potential,
making reinforcement more vulnerable to corrosion. External conditions, such as temperature
fluctuations, moisture variations, and pollution, can further contribute to material degradation.
This study examines the root causes of concrete defects, emphasizing the influence of material
composition, environmental exposure, and construction practices. A deeper understanding of
these factors is essential for developing effective mitigation strategies, enhancing quality
control measures, and ensuring long-term structural reliability through routine inspections,
maintenance, and preventive techniques
Evaluating the Impact of Multimodal AIGC Tools on the Efficiency of Short Video Production
No full textThe rise of AI-generated content (AIGC) is transforming the creative industry, especially in video production. With the fast-paced demands of short videos, creators increasingly rely on AI tools. However, most are single-function, like ChatGPT for text and SUNO for music. Multimodal AIGC tools integrate text, image, audio, and video generation, streamlining workflows by automating tasks such as scriptwriting, design, music production, and editing. This study explores the effectiveness of a multimodal AIGC tool developed by ByteDance called Jimeng, examining its potential to simplify workflows, reduce costs, and foster innovation in short video creation.Using experimental methods to quantify the efficiency of short video production by multimodal AIGC tools. Based on the experiment, the multimodal AIGC tools have improved the efficiency of short video production by over 100%, revealing the ability of AIGC to reshape the short video ecosystem and enhance creative possibilities
Modernizing Testing: A Comparative Review of Test Automation Frameworks and AI Tools
No full textArtificial Intelligence has emerged as a revolution in software testing due to the software industry’s rapid expansion, allowing Quality Assurance (QA) teams to produce higher-quality software more quickly and effectively. The comparative assessment of test automation frameworks and Artificial Intelligence (AI) powered tools presented in this journal emphasises the revolutionary potential of incorporating advanced AI capabilities into software testing procedures. The objective of this study is to create a framework that will enable organisations to implement AI-driven automation in software testing that is compatible with their requirements. The expected results from this research are to come up with a framework that improves accuracy, scalability, and adherence to software standards while minimizing manual effort and increasing overall testing efficiency. The methodology combines questionnaires and a literature review to discover the organisation’s automation technologies and their influence on increasing product quality. A hybrid methodology will be used for this study that will have both quantitative and qualitative data via surveys and interviews review to discover the organisation’s automation technologies and their influence on increasing product quality
Digital Innovation and Higher Education Quality: An Interdisciplinary Integration-Driven Model
No full textDigital transformation profoundly impacts higher education through increased quality and integration between disciplines, but its its specific mechanisms, particularly the role of interdisciplinary integration in mediating digital innovation and educational quality, remain underexplored. In developing a theoretical model for explaining how digital innovation raises educational quality, this study employs a mixed-methods approach combining literature review, survey, and in-depth interviews with university students and instructors. It concludes that digital innovation maximizes resource utilization, enhances instructional efficiency, promotes equitable knowledge dissemination, and strengthens innovation capacities. Integration between disciplines strengthens the impact of digital innovation, generating a positive feedback loop that continues to enhance educational quality. This work enriches theoretical and practical insights into digital education and integration between disciplines and can serve as a guideline for universities to promote digital and integration instruction. It can also inform policymakers in supporting educational digital transformation. There is a potential for future studies to expand data collection in universities worldwide and explore new technology such as AI, big data, and blockchain in driving smarter and fairer higher education. These findings offer actionable strategies for institutions to bridge resource gaps and foster equitable digital transformation
Integrating Art Therapy and Emerging Technologies for Enhanced Neuroplasticity and PTSD Intervention
No full textPost-traumatic stress disorder (PTSD) remains resistant to many conventional treatments, underscoring the need for integrative approaches that harness neuroplasticity. Art therapy, with its capacity to facilitate nonverbal trauma processing and multisensory engagement, has shown distinctive advantages over verbal and pharmacological interventions. Recent innovations, including virtual reality (VR), artificial intelligence (AI), and biofeedback have amplified the therapeutic efficacy of art-based interventions by enabling adaptive, real-time modulation of emotional and physiological states. This review synthesizes current research on technologically enhanced art therapy, comparing it to established treatments such as cognitive behavioral therapy (CBT) and eye movement desensitization and reprocessing (EMDR). Findings indicate that multimodal interventions leveraging VR and biofeedback foster improved emotional regulation, memory reconsolidation, and resilience, particularly when integrated with conventional methods. The novelty of this work lies in identifying how art therapy, augmented by emerging technologies, activates neuroplastic mechanisms through personalization, multisensory immersion, and closed-loop feedback. The study concludes that future PTSD care will benefit from interdisciplinary collaboration, rigorous empirical validation, and the development of personalized, technology-supported therapeutic ecosystems designed to optimize long-term recovery
Case Analysis of Generative AI Adoption and Application Based on the UTAUT Theory: Taking Ctrip's TripGenie Intelligent Travel Chatbot as an Example
No full textThis study takes TripGenie, an intelligent travel chatbot jointly developed by Trip.com (affiliated with Ctrip) and Microsoft, as a case study. Combined with the core framework of the Unified Theory of Acceptance and Use of Technology (UTAUT), it systematically analyzes the adoption logic and application value of Generative Artificial Intelligence (GenAI) in the tourism industry. The research findings indicate that the successful adoption of TripGenie stems from its accurate matching of the performance needs of both users and enterprises, reduction of technical usage thresholds, diffusion relying on industry demonstration effects, and formation of enabling conditions through the integration of resources from both parties. Ultimately, it achieves the upgrading of user experience, business growth, and optimization of operational efficienc
Achievement Growth Performance (AGP): Definition, Connotation, Characteristics and its Value
No full textThis paper introduces Achievement Growth Performance (AGP), a novel and comprehensive concept that integrates students' motivation, continuous ability growth, and academic performance into a dynamic developmental framework. Unlike traditional performance metrics that solely concentrate on static academic achievement, AGP emphasizes a holistic growth trajectory, encompassing learning initiative, skill acquisition, personal development, and long-term educational outcomes. AGP is designed to comprehensively measure students' motivation for growth, their process of comprehensive development and enhanced abilities, and the overall quality improvement process and its ultimate outcomes. It transcends the conventional focus on a single metric of "academic achievement," highlighting that students should not only achieve specific results but also demonstrate comprehensive development. This concept is based on the integration of two established theories: achievement motivation theory, proposed by McClelland and Atkinson, and performance theory. AGP has significant potential to revolutionize performance methodologies and educational models by shifting the focus from simple "score ranking" to a comprehensive "growth trajectory". This document lays the groundwork for continuous investigation and application of this groundbreaking idea, suggesting further research could quantify AGP through metrics like a 'Growth Performance Index' and explore its adaptability in diverse cultural settings
A Critical Eco-Linguistic Discourse Analysis of 'The Lorax'
No full textDegradation of the environment and ecological crises are increasingly worrying issues people face globally, yet the mainstream narrative paradoxically endorses a dangerously exploitative outlook toward nature. Children’s literature, which greatly impacts growing children, provides a unique groundwork to confront environmental narratives. This paper presents a critical Eco-linguistic discourse analysis (CEDA) of The Lorax by Dr. Seuss. This book is a widely recognized green narrative in children’s literature which can be analyzed through Eco-critical lens. Drawing on Arran Stibbe’s (2015) framework, the study aims to explore the role of language in shaping environmental values, ideologies, and human-nature relationship. This research adopts qualitative discourse analysis method, to analyzing metaphor, identity, agency and linguistic choices in the text. The findings reveal that the metaphors of consumption show nature as a commodity. The Lorax presents criticism of anthropocentric and consumerist ideas. The Once-ler stands for industrial exploitation and ecological irresponsibility. Linguistic choices further emphasize the contrast between anthropocentrism and ecocentrism. In this story The Lorax character represents ecological agency and speak out against the commodification of nature. The study proposes that sustainable language practices and environmental literacy can be promoted in education by engaging students in eco-critical discussions and eco-centric activitie
Artificial Intelligence Empowers Sustainable Supply Chains
No full textWith the continuous turbulence in the global market and the rapid development of artificial intelligence (AI), the sustainable development of supply chains has attracted significant attention. Addressing the "efficiency-environmental protection-equity" challenges faced by current sustainable supply chains, this paper attempts to analyze how AI can empower sustainable supply chains and explores AI's ability to handle the dynamic complexity of supply chains, including real-time data monitoring, accurate prediction, intelligent decision-making, risk management, data sharing, and continuous learning. The study finds that AI can empower sustainable supply chains through the following aspects: demand forecasting and inventory optimization, logistics network optimization, supply chain risk management, supplier management, production and manufacturing optimization, real-time monitoring and transparency, as well as carbon footprint management and emission reduction optimization. Through these means, AI helps improve supply chain efficiency, reduce costs, enhance forecasting and demand management capabilities, strengthen risk management and emergency response capabilities, and boost supply chain resilience