Volume 13 | Issue 9 |

 Abstract

In the fast-paced world of e-commerce, pricing is key to shaping customer actions and revenue maximization. Conventional pricing strategies tend to be inadequate in addressing the speed of changing market dynamics, consumer sentiment, and competitor activity. This paper delves into the use of machine learning algorithms for price optimization on e-commerce sites. Through the utilization of big data such as consumer buying patterns, competitor prices, demand for products, and seasonal patterns, machine learning algorithms such as regression analysis, reinforcement learning, and deep learning are able to adapt dynamically and set optimal prices. The paper discusses major algorithms, addresses challenges in implementation, and showcases actual business implementations that reflect enhanced profitability and consumer satisfaction. The results stress the revolutionized possibilities of smart pricing systems in contemporary e-commerce setting

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

We prove some Common Fixed Point theorems for Random Operator in random metric spaces, by using some new type of contractive conditions taking non-self-mappings.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Random metric space, Random Operator, Random Multivalued Operator, Random Fixed, Point, Measurable Mapping, Non-self-mapping

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Creative Commons Attribution 4.0 and The Open Definition

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Parmar Mandir Sthapatya: Navachar Evm Dharmik Sahisnuta Ka Ek Samagra Adhyayan

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Parmar Mandir Sthapatya: Navachar Evm Dharmik Sahisnuta Ka Ek Samagra Adhyayan

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In the rapidly evolving technological landscape, continuous skill development is critical for maintaining workforce competitiveness and addressing the growing demand for technical expertise in fields such as software development. Traditional skill assessment methods, such as manual evaluations or self-reported surveys, are often labor-intensive, costly, and lack personalization, resulting in inefficiencies that hinder effective skill enhancement. This research proposes an innovative automated skill enhancement system that integrates a Telegram bot for user interaction, n8n for workflow automation, Airtable for structured data management, and the Groq AI model for generating personalized quiz questions and learning resources. Users engage with the system through intuitive Telegram commands (e.g., /start, /quiz, /learn), selecting their desired skill set (e.g., Java, Python, JavaScript) and proficiency level (Beginner, Intermediate, Advanced). The system delivers interactive multiple-choice quizzes, evaluates responses in real time, and provides immediate feedback, including congratulatory messages for correct answers and tailored learning materials for incorrect ones. By leveraging cloud-based tools and AI-driven content generation, the system addresses the inefficiencies of conventional methods, offering a scalable, cost-effective, and engaging platform for skill development. Preliminary testing with 50 participants over two weeks demonstrated a 90% quiz completion rate, 85% accuracy in skill assessment, and 75% user satisfaction with feedback quality, underscoring the system's potential. However, challenges such as potential AI biases and accessibility for non-tech-savvy users are acknowledged. This paper details the system's design, methodology, preliminary results, and limitations, while exploring its potential to transform skill enhancement practices in educational and professional settings. Future directions include expanding skill coverage, refining AI models, and enhancing accessibility to broaden the system's impact.

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Creative Commons Attribution 4.0 and The Open Definition

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Skill enhancement, Telegram bot, n8n, workflow automation, AI, machine learning, education technology, personalized learning, skill assessment

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

We prove a unique common fixed-point theorem for two pair of weakly compatible maps in a complete metric space, which generalizes the previous results.

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Creative Commons Attribution 4.0 and The Open Definition

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Common fixed point, Complete metric space, Weakly compatible maps.

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Creative Commons Attribution 4.0 and The Open Definition

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Dietary organic acids significantly influence fish metabolism through complex biochemical pathways affecting protein synthesis, amino acid metabolism, and nucleic acid dynamics. This study investigated the temporal effects of graded citric acid supplementation (2%, 4%, and 6%) on tissue-specific protein content, free amino acid profiles, nucleic acid concentrations, and blood glucose levels in Channa striatus over 28 days. Fish were fed experimental diets and sampled at 7, 14, 21, and 28 days for biochemical analysis of muscle and liver tissues. Protein quantification utilized Bradford assay, amino acids were analyzed by ninhydrin method, and nucleic acids were extracted and quantified spectrophotometrically. Results revealed significant dose-dependent increases in tissue protein content, with 6% citric acid treatment achieving 84.86% and 49.14% increases in muscle and liver proteins, respectively, after 28 days. Conversely, free amino acid levels decreased progressively, indicating enhanced incorporation into protein synthesis pathways. RNA content increased substantially in both tissues (23.05% in muscle, 40.05% in liver with 6% treatment), while DNA showed modest but significant increases at higher doses. Blood glucose levels decreased significantly across all treatments, suggesting improved glucose utilization efficiency. These findings demonstrate that citric acid supplementation orchestrates a comprehensive metabolic reprogramming characterized by enhanced protein anabolism, accelerated nucleic acid synthesis, and optimized glucose metabolism, providing mechanistic insights into growth enhancement in aquaculture species.

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Creative Commons Attribution 4.0 and The Open Definition

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Protein metabolism, nucleic acid synthesis, amino acid catabolism, glucose homeostasis, metabolic reprogramming

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Creative Commons Attribution 4.0 and The Open Definition

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Empowering women through self help groups: An Analytical Study

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Empowering women through self help groups: An Analytical Study

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Creative Commons Attribution 4.0 and The Open Definition

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Communities worldwide face increasing challenges posed by natural disasters, exacerbated by climate change. They have essential knowledge, experience, and abilities regarding building resilience, and have developed innovative approaches to reducing the everyday risks they face. This paper explores the transformative potential of community-based disaster preparedness initiatives in fostering resilience among vulnerable populations. With the increasing frequency and intensity of natural disasters, there is a growing recognition of the need for localized, community-driven strategies to mitigate risks and enhance preparedness. Drawing on case studies from diverse geographic and cultural contexts, this research examines the key components of successful community-based programs. The paper emphasizes the importance of community engagement and participatory processes in conducting localized risk assessments and developing tailored preparedness plans. It investigates the integration of traditional knowledge with modern technologies, such as Geographic Information Systems (GIS) and mobile applications, to create robust early warning systems that resonate with local communities. The paper further delves into innovative educational tools and capacity-building programs that empower communities to take an active role in their own resilience. It discusses the role of social networks, emphasizing the importance of fostering collaborative relationships between communities, local governments, NGOs, and other stakeholders. Finally, the research extends its focus beyond immediate response efforts, examining long-term strategies for building community resilience. This paper contributes to the evolving discourse on community-based disaster preparedness by providing practical insights and suggestions for policymakers, practitioners, and researchers who are trying to strengthen vulnerable communities' resilience in the face of changing climate and rising disaster risk.

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Creative Commons Attribution 4.0 and The Open Definition

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Disaster, Community Engagement, Disaster Preparedness, Innovative Approaches, Capacity Building

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract: This article examines how Dandakaranya--the central Indian rehabilitation scheme for post-Partition refugees--functions as a recurring memory-landscape in Bengali Dalit writing. Instead of treating Dandakaranya only as an administrative site of resettlement, this study reads it as a portable topography that shapes narrative temporality, ethical judgment, and political claim in the life writings and testimonios of Bengali Dalit authors (notably Manoranjan Byapari and Jatin Bala). By juxtaposing parliamentary debates and policy documents with Dalit autobiographical texts and recent scholarship on refugee governance, conservation, and the Marichjhapi affair, I argue that Dandakaranya becomes in Dalit literature both an index of state failure and a mnemonic technology: a set of routes, queues, papers, and affinities that refugees carry into later settings (urban slums, reserve forests, courts). The article elaborates three interlinked claims: (1) Dalit writing transforms bureaucratic detail into moral evidence; (2) Dandakaranya-memory organizes nostalgia as critical evaluation rather than sentimental longing; and (3) the Dandakaranya -> return -> Marichjhapi sequence reveals continuities between development, conservation, and casteed governance. Close readings of texts, archival references (Rajya Sabha debates), and historiographic synthesis support the argument.

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Dandakaranya, Marichjhapi, Bengali Dalit Literature, Refugee Politics, Namasudra, Matua, Memory Landscapes, Exile, Migration.

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Creative Commons Attribution 4.0 and The Open Definition

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Tobacco is a harmful genotoxic natural compound. Tobacco smoke is harmful to smokers and to those exposed to Tobacco smoke. The chemicals found in bidi, cigarette, and cigar etc,. smoke are known for their toxicity. Nicotine, the principal pharmacologic agent common to all forms of Tobacco is a powerfully addicting drug. Thus nicotine in bidi smoke puts smokers at risk for addiction. Nicotine also has adverse effect on cardiovascular health. Tobacco is widely used in cigarette, cigar, chewing tobacco, gutkahs, etc.,. Exposure showed a high risk of human health and development of several types of oral cancers. A total of 56 male daily wage workers in Chandanagar area, Hyderabad, Telangana were investigated for genetic damage in buccal cells of exposed and control subjects. A questionnaire based survey was conducted and buccal smears were collected from oral cavity and analysed for nuclear damage. A high frequency of karyolysis and micronucleated cells were observed among males. The higher percentage of nuclear damage was observed in workers who were smokers. The habit of smoking resulted in the frequency of formation of micronuclei in buccal cells when compared with controls. The present study clearly reveals the mutagenic and genotoxic nature of tobacco and its products. It is necessary to educate the public about the adverse effects of tobacco consumption and prevent nicotine addiction, to decrease genetic damage and risk of serious diseases.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Micronuclei, Buccal Mucosa, Smokers.

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Creative Commons Attribution 4.0 and The Open Definition