Volume 14 | Issue 5 |

 Abstract

Autoimmune disorders are multifactorial immune-mediated diseases characterized by loss of immunological self-tolerance. Ayurveda conceptualizes these conditions through the principles of Dhatu Vaishamya, Agni Dushti, Ama Utpatti, Srotorodha, and Ojas Kshaya. This comprehensive review integrates classical Ayurvedic literature with contemporary immunological research to establish Dhatu-wise correlations with major autoimmune disorders. Modern biomarkers, imaging findings, and immunopathological mechanisms are compared with Ayurvedic Lakshana and Samprapti. The review also highlights future research directions for integrative biomarkers, microbiome-based correlations, and personalized medicine approaches for autoimmune disease management.

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 Keywords

Autoimmunity , Sapta Dhatu, Ojas Kshaya, Ama, Agni Dushti, Biomarkers, Immunology, rheumatoid arthritis, systemic lupus erythematosus, multiple sclerosis, psoriasis, and Hashimoto thyroiditis.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

nitrifying bacteria; Bacillus cereus; Bacillus subtilis; Bt cotton; rhizosphere; 16S rRNA; MPN method; nitrogen cycling; Cry1Ac; soil microbiology

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This research paper explores the transformative role of smart agriculture technologies in improving farming efficiency and crop productivity through the integration of Deep Learning and IoT sensors. By analyzing intelligent agricultural monitoring systems, crop disease detection models, and real-time environmental sensing platforms, the study highlights how these technologies reduce manual effort, improve accuracy in disease identification, ensure timely monitoring, and provide automated decision-making support for farmers. The implementation of IoT-enabled sensors with deep learning algorithms enables continuous data collection, real-time analysis, and scalable smart farming solutions tailored to modern agricultural needs. The paper concludes that intelligent agriculture systems significantly contribute to sustainable farming practices by empowering farmers with accurate insights, automation, and improved crop management capabilities.

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Design of a Smart Agriculture Monitoring and Crop Disease Detection System Using Deep Learning and IoT Sensors

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This paper explores the intricate relationships between organizational learning, employee engagement, and job satisfaction. By examining the theoretical underpinnings and empirical evidence, it identifies how organizational learning processes enhance employee engagement through the mediating role of job satisfaction. The study utilizes a descriptive approach from several organizations.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Organizational Learning, Employee Engagement, Job Satisfaction, Human Resource Management, Organizational Behavior.

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Creative Commons Attribution 4.0 and The Open Definition

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This research paper explores the transformative role of intelligent online examination systems in enhancing digital education and ensuring secure remote assessments through the integration of Computer Vision and Facial Recognition technologies. By analyzing AI-powered examination platforms, automated proctoring systems, and real-time student monitoring solutions, the study highlights how these technologies reduce manual supervision, improve exam integrity, ensure authentication accuracy, and provide efficient online assessment management. The implementation of Computer Vision algorithms and Facial Recognition models enables real-time candidate verification, suspicious activity detection, and scalable remote examination solutions tailored to modern educational needs. The paper concludes that intelligent online examination systems significantly contribute to secure digital learning environments by empowering institutions with automated monitoring, transparency, and improved examination reliability.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

This research paper explores the transformative role of intelligent online examination systems in enhancing digital education and ensuring secure remote assessments through the integration of Computer Vision and Facial Recognition technologies. By analyzing AI-powered examination platforms, automated proctoring systems, and real-time student monitoring solutions, the study highlights how these technologies reduce manual supervision, improve exam integrity, ensure authentication accuracy, and pr

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 Abstract

Bharat Soviet Sangh 20 Varshiya Maitri Sandhi 1971 Ek Aitihasik Vishleshanatmak Adhyayan

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Bharat Soviet Sangh 20 Varshiya Maitri Sandhi 1971 Ek Aitihasik Vishleshanatmak Adhyayan

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Native plant-derived medicinal practices constitute an integral part of traditional healthcare systems in rural India, particularly in biodiversity-rich districts such as Murshidabad, West Bengal. Indigenous communities, traditional healers (Vaidyas, Ojhas), and rural households rely extensively on medicinal plants for treating a wide range of ailments. The present study reviews the traditional ethnomedicinal knowledge associated with native plant species in Murshidabad district and explores their sustainable applications in healthcare and biodiversity conservation. Data from previous ethnobotanical studies indicate that over 50 medicinal plant species belonging to approximately 39 families are commonly used in the district. Frequently utilized plant parts include leaves, roots, bark, fruits, and seeds, addressing ailments such as digestive disorders, skin diseases, fever, diabetes, jaundice, and musculoskeletal problems. Sustainable application of these medicinal resources requires proper documentation, conservation of sacred groves, community participation, cultivation practices, and integration of traditional knowledge with scientific validation. This study highlights the significance of preserving indigenous medicinal knowledge and promoting sustainable utilization for ecological and socio-economic development in Murshidabad.

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 Keywords

Ethnomedicine, Medicinal plants, Indigenous knowledge, Sustainability, Murshidabad, West Bengal, Traditional healthcare, Biodiversity conservation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The urban traffic in cities has gotten so worse as vehicle ownership has grown. Which actually means longer commutes, more fuel burned, and higher emissions. Most of navigation systems handle it the same way they always have: compute a route, react when something slows down. The congestion is already there by the time the system notices. We have built a Dynamic Route Rationalization framework to address this. It combines Graph Convolutional Networks and Long Short-Term Memory models with a modified A* search algorithm. The traffic data comes in through the Google Maps API. The GCN handles spatial structure -- which road segments connect, and how they influence each other. The LSTM handles time -- how patterns shift across the day. The two together makes sure the system forecast congestion a few steps ahead instead of catching up to it. The route selection uses a cost function that weighs distance, travel time, congestion level, incident severity, and predicted conditions. The weights aren't fixed and they shift depending on what's happening. A* then uses that cost to generate routes that avoid congestion before it builds. On urban traffic datasets, the framework reduced travel times, avoided more congestion events, and produced more stable routes during peak hours than baseline approaches.

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 Keywords

Urban Traffic Optimization, GCN-LSTM, Dynamic Cost Algorithm, A* Routing, Smart Mobility, Real-Time Traffic Prediction

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The traditional e-learning system allows users to learn new things easily but the problem arises because it fails to consider learning ability of individuals. Some learners have understood the concepts in less time but some takes more time and it does not give importance for increasing critical thinking and gives only limited access to users. This limitation has become the reason to implement new learning system by using artificial intelligence. The main advantage of this work is that it allows learner to give feedback for the quizzes generated by it. Some learners may find the questions easy while others may find them difficult based on this feedback the system automatically adjusts upcoming concepts and question difficulty. It also increases critical thinking of user by analyzing the things in different way rather than just giving importance only for memorizing the things. The system also includes a progress bar in which user can easily see the number of courses they are learning and percentage of each course.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Feedback-Based Learning, Artificial Intelligence, Critical Thinking, Personalized Learning, e-learning System.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sanskrit Vyakaran evam Nyaya Parampara mein San Pratyay Mithila ke Vishesh Sandarbh mein Ek Darshanik evam Bhashai Vishleshan

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Creative Commons Attribution 4.0 and The Open Definition

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Sanskrit Vyakaran evam Nyaya Parampara mein San Pratyay Mithila ke Vishesh Sandarbh mein Ek Darshanik evam Bhashai Vishleshan

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Creative Commons Attribution 4.0 and The Open Definition