Volume 14 | Issue 4 |

 Abstract

This study presents a comparative evaluation of the tensile properties of Fe550D grade TMT reinforcement bars from various manufacturers, including Polaad, Rajuri, Icon, and Uma. Fe550D bars are widely used in structural applications due to their high strength and enhanced ductility, which is essential for earthquake-resistant and high-rise constructions. The evaluation focuses on key mechanical properties such as yield strength, ultimate tensile strength, and elongation, in accordance with IS 1786:2008 standards. Results indicate variations among brands, with some bars exceeding the minimum standards in tensile strength and ductility, highlighting the importance of selecting manufacturer-certified materials for structural safety. The more study emphasizes the need third-party testing and certification to ensure compliance and consistent quality across batches.this is only for case study purpose.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fe550D, TMT reinforcement bars, Tensile strength, Yield strength, Ductility

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid increase in consumption patterns and disposal culture has resulted in significant environmental challenges, including excessive waste generation and inefficient utilization of resources. The concept of a circular economy has emerged as a sustainable solution, aiming to extend product life cycles through reuse, recycling, and refurbishment. However, existing online marketplaces do not effectively incorporate intelligent systems that promote sustainable practices or assist users in making informed decisions. Vijay Shukla Information Technology Shri Ramswaroop Memorial college of Engineering and Management Lucknow,India vijayshukla.cs@srmcem.ac.in significant role in enabling circular economy practices by connecting buyers and sellers of used goods. However, existing online marketplaces primarily focus on facilitating transactions and lack intelligent features that support sustainability or optimize user decision making processes. This research proposes the development of a Smart Circular Economy Marketplace using the MERN stack, which includes MongoDB, Express.js, React.js, and Node.js, integrated with Artificial Intelligence techniques for recommendation and price prediction. The system enables users to buy and sell second-hand products while leveraging machine learning algorithms to provide personalized recommendations and fair price estimations. The recommendation system utilizes collaborative filtering and content based approaches, whereas the price prediction module employs regression models to estimate appropriate product values based on multiple attributes. The proposed system not only enhances user experience but also contributes to environmental sustainability by encouraging reuse and reducing waste. The results indicate improved user engagement, increased transaction efficiency, and better pricing accuracy, making the system a viable solution for modern sustainable marketplaces

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

MERN Stack, Full Stack Development, AI For Recommendation And Price Prediction

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Lactose intolerance is commonly perceived as an irreversible enzymatic deficiency. However, emerging evidence suggests that intestinal adaptability and microbial modulation play a significant role in symptom manifestation. Ayurveda correlates similar conditions with Agnimandya, Ama, and Grahani Dosha. This study proposes the concept of lactose intolerance as a Gut Plasticity Disorder, emphasizing reversibility. A case series of three patients treated with an integrative protocol demonstrates restoration of lactose tolerance. The findings support a paradigm shift from dietary restriction to functional gut rehabilitation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

intolerance, Grahani, Agni, Gut plasticity, Case series, Ayurveda

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Manjusha painting, a traditional art form from Bihar is known for its vibrant colors, intricate designs and rich cultural symbolism, often depicting folklore, mythology and spiritual themes. The craft is based on a popular folktale of Sati Bihula Devi Bishahari which dates back to the 7th century CE. Despite its historical and cultural significance, the awareness and recognition of this unique art appears to be limited, particularly outside its native region. Through this study, the level of public awareness will be assessed, throwing light on factors that affect the visibility and appreciation of the art form. An in-depth exploration will document the traditional methods, motifs and themes used in this artform, emphasizing its unique storytelling aspect. During the study a contemporized collection will be designed for working women using Computer-Aided Design (CAD) and AI technology. This integration of digital tools with traditional techniques will not only preserve the essence of Manjusha art but also open up new avenues for its application in contemporary design contexts. Ultimately, this research strives to bridge the gap between traditional craftsmanship and modern technology, ensuring its continued relevance and growth in the digital age.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Folk-Tale, Storytelling, Craft Preservation, Religious Art, Motif Development, Women's Wear, Business Casual, 3D Garment visualization.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

[3:18 pm, 01/04/2026] Shanvi: Proliferation of cases of missing persons around the world with grave humanitarian considerations that are at times made worse by the impotence of old ways of searching, hard work being put into rummaging through documents, public announcements, and putting posters up. Conversely, our approach using AI involves a deep-learning face recognition for rapid and improved identification of missing persons. As such, the framework integrates OpenCV and dlib-ResNet algorithms to achieve highly accurate near-real-time face matching on the Euclidean distance of 128-dimensional face embeddings. The front end of the user interface for this reporting and monitoring service is designed in React.js while the back end uses Node.js and Express.js and the underlying scalable data management is supported by MongoDB. The facility together with using the WhatsApp Business API for sending real-time alerts to matches magnifies the arena for citizen-family-government collaboration. Performance evaluation based on accuracy, precision, recall, and F1 score to confirm reliability was conducted using benchmark data sets. FaceTrace ensures the scalability of the system, quick delivery, and data security through cloud-based hosting. This platform is attached to the technology-based social model whereby the recovery of missing persons will be an expedited community-impelled intelligent process.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Facial Recognition, Deep Learning, Missing Person Identification, OpenCV, dlib-ResNet, MongoDB, WhatsApp API, Artificial Intelligence.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

AURA is an AI-based institutional platform designed to support student mental wellness and academic assistance in a college environment. The system integrates a Flask and MongoDB backend with a Gemini-powered chatbot, mood-aware user interface personalization, and multimodal study support for text, image, and PDF inputs. It continuously analyzes mood and conversational sentiment to estimate stress levels, identify at-risk students, and generate timely alerts for proctors and HODs through role-based dashboards. In addition, AURA provides grievance management, self-regulation activities, and secure session-based access control to support both intervention and engagement. The platform demonstrates a closed-loop approach that combines emotional monitoring, AI assistance, and administrative oversight to improve student well-being and academic support

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

student mental wellness, AI-based academic support, stress detection, mood analysis, sentiment analysis, emotion-aware computing, mental health monitoring, chatbot assistance, adaptive user interface, institutional analytics, early intervention, role-based dashboards, grievance management, multimodal learning support, predictive risk assessment.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Freshwater ecosystems and their associated biodiversity face unprecedented threats from anthropogenic pressures, habitat degradation, and climate change.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Aquatic biodiversity, avian ecology, Silgi River, freshwater fish, behavior patterns, riparian ecosystem

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

SmartShelf AI is an intelligent book recommendation system that integrates emotion AI, semantic understanding, and quantum computing to deliver highly personalized suggestions. It analyzes user mood through natural language input using a 27-class emotion detection model. These emotional profiles are mapped into a semantic space alongside book metadata for deeper contextual matching. A quantum kernel-based similarity model captures complex relationships beyond classical methods to improve recommendation accuracy. The system is implemented as a full-stack, privacy-preserving application, demonstrating the practical use of quantum machine learning in real-world scenarios.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Book Recommendation System, Emotion-Aware AI, Quantum Computing, Quantum Kernel, Variational Quantum Circuit, Semantic Embeddings, Natural Language Processing, GoEmotions, SentenceTransformers, Hybrid Recommendation System, Affective Computing, Privacy-Preserving AI

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Creative Commons Attribution 4.0 and The Open Definition

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In the 21st century, shifting toward a green economy is not merely an environmental choice; it is also an important economic strategy. For a developing country like India, this transition represents a "double dividend" because it protects the environment while simultaneously creating employment opportunities. This paper examines the relationship between green growth and employment generation in India. The study focuses on major sectors such as renewable energy, sustainable agriculture, waste management, and green infrastructure. By analysing recent policy reports and international data sources, the paper identifies emerging patterns in green job creation and evaluates the effectiveness of government initiatives supporting this transition. The findings indicate that India's expansion in solar and wind energy has created significant employment opportunities. However, the growth of green jobs is constrained by several challenges such as lack of specialised skills, limited technological capacity, and financial barriers. The study concludes that stronger policy support, increased investment in green technology, and large-scale skill development programmes can transform the green economy into a major driver of sustainable and inclusive employment generation in India.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Green Economy, Green Jobs,EmploymentGeneration,Renewable Energy, Sustainable Development, India.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

HR Analytics, also called Human Resource Analytics, is becoming popular in organizations. It helps improve employee performance and reduce turnover. This study focuses on how HR Analytics improve employee performance and retention in the manufacturing industry.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

HR Analytics, Employee Performance, Employee Retention, Workforce Planning, Data-Driven Decision Making, Predictive Analytics, Employee Engagement, Human Resource Management, Productivity Improvement, Employee Turnover

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Creative Commons Attribution 4.0 and The Open Definition