Volume 14 | Issue 3 |

 Abstract

INTRODUCTION: Shireesha (Albizia lebbeck Benth.) is a Vishaghna dravya described extensively in Ayurvedic classics. It is mentioned from the Vedic period to Nighantu period with wide therapeutic applications, especially in Visha, Kasa, Shwasa, and Kushtha. Classical texts emphasize its role in detoxification and management of Kaphaja and allergic disorders.MATERIALS & METHODS: A comprehensive literary review was carried out from primary Ayurvedic sources including Charaka Samhita, Sushruta Samhita, Ashtanga Hridaya, and Nighantus such as Bhavaprakasha Nighantu etc. Data regarding Rasa, Guna, Virya, Vipaka, Karma, therapeutic indications, and classical formulations of Shireesha were collected, compiled, and analysed.RESULTS: Classical literature consistently identifies Shireesha as a potent Vishaghna drug. In Samhitas, it is included under Vishaghna Mahakashaya and Shirovirechaniya Gana, indicated in Visha, Kasa, Shwasa, Kushtha, and other skin disorders. Nighantus describe it predominantly with Kashaya-Tikta Rasa, Laghu Guna, and variable Virya (Ushna/Sheeta). It is widely used in classical formulations like Pancha Shireesha Agada etc. Variations are observed in Virya and Guna across different texts, indicating diverse interpretations.DISCUSSION: The compiled data highlights Shireesha as a multi-dimensional therapeutic drug with main action in Visha Chikitsa and Kaphaja Vyadhi. Differences in Virya and Guna among Nighantus suggest regional or interpretative variations, while the uniform emphasis on Vishaghna Karma supports its strong detoxifying and anti-allergic potential.CONCLUSION: Classical Ayurvedic literature establishes Shireesha as a Shreshta Vishaghna dravya with wide therapeutic utility. The consistency of its indications across texts validates its importance in Ayurveda and provides a strong foundation for further pharmacological and clinical research.

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Shireesha, Albizia lebbeck, Review, Vishaghna, Yogas

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Email Spam Detection System is an intelligent text classification application designed to identify and filter spam emails using Machine Learning and Natural Language Processing techniques. The system employs a Multinomial Naive Bayes classifier trained on TF-IDF vectorized features to accurately distinguish between spam and legitimate (ham) messages. A Flask-based REST API serves real-time predictions to a dynamic web frontend, providing users with confidence scores, keyword-level threat indicators, and a session-based scan log. Experimental evaluation demonstrates high classification accuracy with reliable detection of spam patterns including phishing, promotional scams, and fraudulent solicitations.

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Spam Detection, Naive Bayes, TF-IDF, Machine Learning, NLP, Flask, Email Classification.

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An Analytical Study of the Tehsils of Bhilwara District Based on Population Size and Rank

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An Analytical Study of the Tehsils of Bhilwara District Based on Population Size and Rank

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Email marketing is a powerful form of direct marketing used to promote a business's products and services. It can be used as part of a marketing automation strategy to build customer loyalty, deepen relationships, and keep customers engaged with your brand, products, and services. E-mail marketing plays a crucial role in supporting and enhancing other marketing strategies. Direct E-mail Marketing is the fastest option for sales. The objective of this paper is to know the respondents' opinions towards E-mail marketing, to study its advantages, and challenges, and to compare the effectiveness of e-mail marketing. We have collected data from 100 respondents. Our study is based on primary and secondary data. We have observed from this study that today social media marketing and other marketing channels have overtaken email marketing and still consumers have a favourable perception of email marketing. In this study, we can see that the respondents are highly satisfied with email marketing by applying the chi-square value and paired t-test. We used the tools like SPSS and Excel.

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E-mail marketing, Digital marketing, social media, customer awareness, respondents.

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This paper examines the articulation of black identity, resistance, and cultural affirmation in selected poems of Langston Hughes within the socio-historical context of the Harlem Renaissance. Poetry is treated as a medium that preserves collective memory and voices the experiences of marginalized communities. Hughes' works such as "I, Too," "The Negro," "Cross," and "Dream Variations" foreground the realities of racial discrimination, social inequality, and the search for belonging while simultaneously celebrating African American resilience and creativity. The study situates Hughes' poetic vision alongside the broader cultural awakening of the Harlem Renaissance, a movement that sought to redefine African American identity through literature, music, and art. By analysing Hughes' use of metaphor, musical rhythm, historical reference, and everyday imagery, the paper explores how his poetry constructs a powerful narrative of dignity and self-assertion. It further highlights the poet's engagement with themes of migration, segregation, mixed heritage, and the dream of social equality. Through close textual reading and contextual interpretation, the research argues that Hughes' poetry functions both as a protest against racial injustice and as a transformative cultural expression that reshapes perceptions of black identity in modern America. Research Question: How does Langston Hughes employ poetic form, imagery, and cultural symbolism to articulate and affirm black identity during the Harlem Renaissance?

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Langston Hughes, black identity, Harlem Renaissance, racial discrimination, jazz poetry, cultural memory, protest literature, African American experience, metaphor, social justice

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The family is one of the most fundamental social institutions, playing a crucial role in socialization and value transmission. Traditionally, Indian society has been characterized by the joint family system, where multiple generations lived together under one roof. This system was not merely a residential arrangement, but a powerful medium for cooperation, love, values, security, and a sense of collective responsibility. However, in recent decades, there has been a significant shift towards the nuclear family system. This transformation has been driven by factors such as urbanization, industrialization, education, economic independence, and changing social values. The present paper examines the transition from joint family to nuclear family in Indian society, analyzes its major causes, and evaluates its social implications. The study highlights both the positive and negative consequences of this shift and emphasizes the need to balance modern lifestyles with traditional family values.

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Joint family, Nuclear family, Social change, Urbanization, Indian society

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Unemployment has been perceived as a challenging as well as serious problem throughout the world. In India unemployment is not only a burning problem but it has become a source of various unexpected deviant behaviours among youth reflected in their activities in form of separatism, antinationalism, terrorism, regionalism etc. Unemployment exerts economic social and psychological pressures, results in deviant behavior and mental ill-health. Shelton (1985) reported the social and psychological impact of unemployment in terms of increased stress, depression, anxiety and interpersonal problems unemployment led to decrease in perceived competence, activity and life satisfaction and increase in depressive affect (feather and O' Brien, 1986). Macky (1984) found that unemployed were possessing poorer mental health than their counterparts.

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UNEMPLOYMENT & MENTAL HEALTH

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The fashion industry has recently experienced increasing pressure to adopt environmentally responsible practices due to growing concerns about climate change, textile waste, and unethical labor practices. Sustainable fashion has emerged as a response to these challenges by promoting environmentally friendly materials, ethical production processes, and responsible consumption patterns. The purpose of this research is to examine consumer perception and purchase intention toward sustainable fashion in Gujarat, India. The study aims to understand how consumers view sustainable clothing, the factors that influence their buying decisions, and the barriers that prevent them from purchasing eco-friendly apparel. Primary data was collected from 300 respondents across various cities in Gujarat using a structured questionnaire. The research used a descriptive research design while applying quantitative analysis methods to examine consumer responses. The researchers used statistical methods which included frequency distribution and correlation analysis and regression analysis to assess how awareness and environmental concern and price perception affected purchase intention. The study results demonstrate that Gujarat consumers possess a favorable attitude toward sustainable fashion because they recognize its environmental advantages yet they only buy sustainable products at a moderate level. Price sensitivity and product unavailability and insufficient awareness about sustainable brands emerged as the primary obstacles. The research discovered that environmental awareness together with product quality perception managed to determine customers' buying behavior. The research recommends that sustainable fashion companies need to establish more affordable products while educating customers about their offerings and developing more distribution points to increase sustainable clothing use throughout the area. The research study helps people understand how consumers in developing economies behave toward sustainable fashion by providing valuable information to businesses and policymakers and researchers who want to promote sustainable consumption.

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Sustainable Fashion, Consumer Perception, Purchase Intention, Environmental Awareness, Green Consumption, Gujarat Fashion Industry

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Cancer identification using molecular data is a complex and resource-intensive process, particularly in low- resource healthcare settings. This project proposes a minimalistic recursive model for molecular cancer identification using text-based genetic and biomarker information. The system analyzes unstructured molecular text data and applies iterative reasoning to refine cancer type predictions. By employing a lightweight and efficient computational approach, the proposed system reduces complexity while maintaining reliable performance. The model is designed as a preliminary decision-support system and is intended strictly for educational and research purposes.

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Cancer identification, Molecular data, Biomarker information, Recursive model, Decision-support system

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In the modern customer-driven market, the demand for customized products has increased significantly. However, traditional product design methods rely heavily on expert knowledge, manual planning, and repeated trial-and-error processes, making customization time-consuming and costly. This paper presents a Smart Product Design Assistance System using Artificial Intelligence, Machine Learning, and Natural Language Processing (NLP) to support automated and structured customized product design. The system accepts user requirements in textual form and applies NLP techniques to extract meaningful design features, which are further analysed using machine learning models to map the input to predefined product design and manufacturing workflows. Based on this analysis, the system generates structured end-to-end manufacturing guidance, including raw material selection, required tools, design considerations, step-by-step manufacturing procedures, cost estimation, and safety guidelines. The proposed system focuses on accurate and well-structured text-based guidance rather than image generation, ensuring clarity and reliability. By storing expert knowledge in a centralized knowledge base and automating design-related decision-making, the system reduces dependency on human experts, minimizes errors, and shortens the product development cycle, making customized product design more accessible for educational and small-scale manufacturing environments.

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Artificial Intelligence (AI), Natural Language Processing (NLP), Machine Learning (ML), Customized Product Design, Intelligent Design Assistance, Knowledge-Based System, Smart Manufacturing, Manufacturing Process Planning, Text-Based Requirement Analysis, Automated Manufacturing Guidance, Product Concept Generation, AI- Assisted Design System, Design Automation, Intelligent Decision Support, Digital Product Development, Human- AI Collaboration in Design, Smart Design Workflow, Intellige

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