Volume 14 | Issue 5 |

 Abstract

The abrogation of Article 370 in 2019 marked a significant constitutional and administrative shift in Jammu and Kashmir,resulting in greater alignment with national policy frameworks.In this context,the implementation of the National Education Policy 2020 assumes particular importance, as it represents a comprehensive reform agenda aimed at transforming India's education system in terms of Access,Equity,Quality and Governance.This paper presents a conceptual assessment of the National Education Policy in Jammu and Kashmir in the Post Article 370 period,focusing on the changing structures of educational governance and policy integration.Drawing on constitutional provisions,policy documents and existing scholarly literature,the study examines how the removal of special status has reshaped the institutional environment for education in the region.The paper conceptually analyses key components of NEP related to school education,higher education and discusses emerging opportunities and challenges with in the regional context.The study emphasizes the importance of context-sensitive implementation of national education reforms and identifies the need for future empirical research on educational outcomes in Jammu and Kashmir

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 Keywords

National Education policy, Article 370, Educational Governance, Jammu and Kashmir

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Creative Commons Attribution 4.0 and The Open Definition

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The increasing threat of climate change poses significant challenges to global agricultural productivity, food security, and environmental sustainability. Climate Smart Agriculture (CSA) is the most suitable strategic framework to address the triple challenge of sustainably increasing productivity, reducing greenhouse gas emissions and enhancing resilience. This review provides current evidence on CSA as a roadmap for sustainable farming and long-term food security. The conceptual framework of CSA is explained with its three core pillars, namely productivity, adaptation, and mitigation and its link to sustainable agriculture and food system resilience. Key CSA practices, including conservation agriculture, agroforestry, crop diversification, integrated nutrient and pest management and climate-resilient crop varieties, were studied. The role of digital technologies such as remote sensing, crop modelling, and artificial intelligence in enhancing farm-level decision-making is discussed, along with persistent barriers to adoption among smallholder farmers. Empirical studies from Africa and other developing regions highlight the potential of CSA to improve yields, household nutrition, and climate resilience, while also highlighting the influence of socioeconomic conditions, governance, and policy design. The paper concludes with research gaps and policy recommendations for mainstreaming CSA within national agricultural strategies and global sustainability agendas, particularly the Sustainable Development Goals.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Climate Smart Agriculture, sustainable agriculture, food security, climate resilience, smallholder farmers, green house gas mitigation.

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Creative Commons Attribution 4.0 and The Open Definition

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Keywords--Machine Learning, Sleep Quality Prediction, Smartphone Usage Patterns, Random Forest Regression, Predictive Modeling, Digital Wellness, Behavioural Analytics

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Creative Commons Attribution 4.0 and The Open Definition

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In recent lots of people are experiencing depression, anxiety, or stress and these conditions really damage people's health. The problem is well recognized, but most individuals do not receive a proper diagnosis or treatment due to the social stigma associated with mental disorders, lack of mental health services, and our traditional method of diagnosing diseases, which is dependent upon self-reporting. Luckily, artificial intelligence is improving rapidly and because we have so much digital information, we can now create new algorithms based on data to identify mental health problems. This project is about using artificial intelligence to find mental disorders and it does this by looking at both organised and less organised information using machine learning. In order to make things clear, it uses traditional approaches such as Logistic Regression, SVM, and Random Forest; as well as sophisticated deep learning models such as LSTM and BERT. The older approaches are good because they are easy to understand and work brilliantly with straightforward information, while Deep Learning models are for finding hidden patterns and using those to predict what's going on. The system uses a chatbot to get information as it's needed. Accuracy-wise, the proposed hybrid approach shows excellent performance accuracy, having an accuracy prediction rate of 92.50% with the AUC-ROC score of 0.9759. This means it's more accurate than any of the models used on their own, but it is just as good at being precise, and at finding all the relevant information.

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 Keywords

Artificial Intelligence, Mental Health Prediction, Machine Learning, NLP, Chatbot, Lifestyle Data, Digital Psychiatry

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Nursing practice is changing internationally as a result of the healthcare industry's fast digital transformation, putting nurses at the forefront of technology-driven care delivery. Since they make up about 59% of the healthcare workforce worldwide, nurses are essential to the effective implementation of digital health advances. Digital technologies like artificial intelligence (AI), telemedicine, and electronic health records (EHRs) are being used more and more to fill staffing gaps and improve treatment efficiency as the global healthcare sector is expected to have a deficit of 5.7 million nurses by 2030. Digital solutions have proven to have the capacity to enhance productivity, lower mistakes, and improve patient outcomes on a global scale. Artificial intelligence (AI) and robots are revolutionizing clinical decision-making and patient monitoring, allowing nurses to provide accurate, data-driven care. Additionally, real-time data gathering is made easier by digital health systems, which enhance population health management and promote evidence-based nursing practice. Government initiatives like national digital health programs and more private sector investment are driving a major digital transformation in healthcare in India. The COVID-19 pandemic further accelerated the use of digital platforms and telemedicine, increasing accessibility, especially in underserved and rural areas. According to recent estimates, hospitals in India are progressively using AI and digital solutions to lessen burden; these technologies may save medical workers two to three hours of their daily workday.

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 Keywords

:- Digital transformation, Cutting edge technology, AI, Telemedicine and global health workforce.

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Abstract: Scheduled tribes of Jangle Mahal, eastern fringe of Chotanagpur plateau region are socio-economically backward and marginalised ethnic groups. Tribal people accounts 8.6 percent of India's total population. Since, after seven decades of independence, Scheduled Tribes (ST) are still at the margin of society. This study seeks a deeper insight into the demographic situation of the tribal communities. Primary data were collected from 117 and 114 sample houses of the Sabar and Santal communities, drawn from 9 selected villages following a stratified random sampling technique. The result indicates that Santals perform better in education than Sabar community. Both communities have high sex ratio compared to the national sex ratio. The average dependency ratio of the Sabar community is more (47.8 %) than Santal community (42.02 %). Also, the Sabar community show higher Child Women Ratio (284.72), indicating a higher level of fertility than the Santals (235.29). Sabar has a nuclear family system, with average family size of 3.65 and Santals shows joint family system with average family size of 4.59. The unemployment problem is very high among the Sabar community. The study reveals that illiteracy, a greater degree of dependency, and limited access to the mainstream socio-economic activities make the tribal people vulnerable. Collective and coordinated efforts of Govt. policy makers, planners, economists, and social scientists may formulate community specific plan for economic as well as social upliftment of these marginalised groups.

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 Keywords

Tribal Society, Literacy, Dependency Ratio, Child Women Ratio

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Creative Commons Attribution 4.0 and The Open Definition

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The sustainability of modern digital enterprises depends as much on the stability and well-being of their workforce as on financial performance. India's fintech sector, once buoyed by record venture capital inflows, has encountered a pronounced period of investment deceleration- commonly described as the funding winter- that has introduced significant organizational and human resource challenges. Workforce reductions, aggressive cost rationalization, and intensified performance expectations have converged to heighten workplace stress, weaken employee morale, and threaten long-term retention. This paper presents a conceptual study that examines the interplay between employee well-being, ethical leadership, and organizational resilience within fintech firms navigating financial constraints. Anchored in Stakeholder Theory and Sustainable Human Resource Management (SHRM), the study argues that organizations which place human sustainability at the heart of their strategic response to funding downturns are considerably better positioned to preserve talent continuity and strategic adaptability. A conceptual framework is proposed in which ethical leadership and supportive organizational culture function as mediating forces - moderating workplace stress, reducing turnover intentions, and ultimately strengthening organizational resilience. The paper advances the idea of the sustainable talent ecosystem as a purposeful construct within digital financial organizations and offers a theoretical model to guide future empirical investigation into fintech workforce management.

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 Keywords

: Sustainable Commerce, Fintech Workforce, Ethical Leadership, Employee Well-Being, Organizational Resilience, Talent Retention.

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SAMVAAD (Sign and Multimodal Voice Assistive Access & Dialogue) is an AI-powered accessibility platform developed to bridgecommunication gaps between individuals with hearing, speech, and visual impairments and the general public. Existingassistive systems generally focus on only one form of disability and fail to provide integrated communication support.SAMVAAD addresses this limitation by combining Sign Language recognition, Speech-to-Text (STT), Text-toSpeech(TTS), Braille translation, and 3D avatar-based sign visualization into a unified web-based platform. The system uses Artificial Intelligence, Computer Vision, and Natural Language Processing technologies such as OpenCV, MediaPipe, and Flaskto enable real-time multimodal communication. The proposed framework provides users with text, speech, sign, and Braille interaction modes while maintaining a lightweight and locally deployable architecture. The platform also includesan educational module for learning Sign Language and Braille, thereby promoting accessibility awareness and inclusiveinteraction. SAMVAAD demonstrates how AI can be ethically utilized for social good by improving communication accessibility and empowering differently-abled individuals.

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 Keywords

Index Terms - Artificial Intelligence, Accessibility, Sign Language Recognition, Braille Translation, Speech-to-Text, Textto-Speech, , OpenCV, MediaPipe.

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Creative Commons Attribution 4.0 and The Open Definition

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Traditional certificate verification is slow, fraud-prone, and built on centralized systems that create obvious single points of failure. This paper proposes and implements a blockchain-based certificate verification system on Ethereum that addresses these problems at the architectural level. The system uses Solidity smart contracts for certificate lifecycle management, SHA-256 hashing for tamper detection, and IPFS for decentralized document storage. A role-based access control model, ECDSA digital signatures, and consensus-based validation protect against forgery and unauthorized changes. Four modules handle the core workflows: institutional issuance, student credential management, employer verification, and administrative governance. Testing on a private Ethereum network with 5,000 certificate transactions showed a 99.97% reduction in verification time compared to paper-based methods, zero successful fraud attempts, and improved system availability through distributed architecture.

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 Keywords

Blockchain, Certificate Verification, Smart Contracts, Ethereum, Distributed Ledger Technology, SHA-256 Hashing, Digital Credentials, IPFS, Solidity, Decentralized Applications.

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Today, amid the ever-evolving financial markets, tools like Chartink play a vital role in finding investment targets. Nevertheless, their dependence on manually constructed filters and quasi-programmingbased syntax results in serious usability issues. To tackle these problems, we propose a next-generation cloudbased solution based on the dual Large Language Model (LLM) architecture that will let you easily scan the financial market using simple and conversational NLP input. The proposed system uses an innovative approach to filtering data dubbed as Programmatic Filter Synthesis. In this process, the Qwen3-14B model from the OpenRouter API creates a JSON object including SQL query parameters that are validated by our system and safely executed against the DuckDB analytical engine running queries on 5.5 GB of Apache Parquet data. Moreover, our system is equipped with a local guard module known as Qwen3Guard-Gen-0.6B that filters out all the possible hazardous or inappropriate inputs before processing them via the generation module. The entire stack includes the following: web front-end: React/Next.js 16; server-side: Python FastAPI with SSE streaming, caching: Redis service and Supabase authentication. We achieved an 87% adjusted semantic accuracy rate while testing our system on 100 benchmark prompts.

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 Keywords

Cloud Computing, Large Language Model (LLM), Financial Data Analysis, Programmatic Filter Synthesis, Natural Language Processing (NLP), Text-to-SQL, DuckDB, Dual-LLM Architecture, Server-Sent Events (SSE).

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Creative Commons Attribution 4.0 and The Open Definition