Volume 14 | Issue 6 |

 Abstract

The implementation of Artificial Intelligence (AI) in rural banking systems has transformed rural management according to current recognition of its revolutionary impact. AI creates pathways for financial management in rural areas to achieve operational efficiency and customer accessibility and innovative business models through its system transformation capabilities. The study uses secondary data from academic journals and industry reports and international case studies to examine major opportunities and threats and ethical challenges which arise from implementing AI in rural banking systems.The results show that AI provides substantial benefits for rural management through three main advantages which include personalized data-driven services that improve financial inclusion and predictive analytics that enhance credit evaluation and risk assessment for rural communities and automated banking activities which reduce costs and machine learning algorithms that improve fraud detection. The advantages of these benefits provide solutions to address three persistent issues which affect rural areas because they include insufficient infrastructure and information gaps and restricted access to formal financial services. The introduction of AI technology into rural financial systems creates multiple dangers which include data management privacy issues and algorithmic biases that impact underrepresented rural populations and cybersecurity threats and the need for advanced AI systems to operate rural services. The main problems include ethical issues which involve decision-making systems that lack transparency and accountability and fairness and automated systems which will result in job losses for rural service workers. The research work highlights the need for the development of inclusive regulatory frameworks, ethical standards, and governance structures specifically designed for rural areas to ensure responsible AI implementation. The study determines that AI technology provides substantial benefits for rural management and rural banking system development yet effective risk management and ethical responsibility measures need to be established to achieve sustainable rural development.

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 Keywords

Artificial Intelligence (AI), Rural Banking, Banking Sector, Financial Technology (FinTech), Risk Management, Ethical Challenges, Data Privacy, Fraud Detection, Automation in Banking.

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Creative Commons Attribution 4.0 and The Open Definition

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Janusandhigata Vata is explained in concise form in our Samhitha. The symptoms includes Vatapoorna-Dritisparsha, Sandhi Shotha, Prasarana Acuchanayo Vedana, Atopa, Sandhi Hanti. Various treatment modalities have been employed such as Bahya and Abhyantara Snehana, Basti Prayoga, Upanaha, Agnikarma, Bandhana, Unmardana. Aetiology and symptomology of Sandhigata Vata mentioned in Samhitha, mimics with the symptoms of osteoarthritis of contemporary science. Osteoarthritis is defined as a non-inflammatory degenerative joint disease marked by degeneration of articular cartilage, accompanied by pain and stiffness of joints. When left untreated this disease makes the person crippled and dependent on others for attending normal daily activities.

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 Keywords

Janusandhi, Sandhigata Vata, Vata Dosha, Osteoarthritis

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This review explores Generation Z's attitudes towards green consumerism, with particular attention to the ongoing gap between their environmental values and their actual sustainable purchasing habits. Methodology: A systematic literature review was conducted, combining peer-reviewed articles from sources such as ScienceDirect and Google Scholar, along with industry reports from Circana and WWD, focusing on publications from 2020 to 2026. Key Findings: Although more than 75% of Gen Z consumers say sustainability is more important than brand names, and 81% are willing to pay more for eco-friendly products, fast-fashion apps continue to grow rapidly, with over 54 million downloads in early 2025. Social media raises awareness about sustainability but also encourages overconsumption through popular trends. The gap between attitudes and actions is influenced by factors such as price sensitivity, the desire for convenience, doubts about the authenticity of sustainability claims, and digital activism that sometimes replaces real-world action. Research Gaps: Most studies treat Gen Z as a single group, ignore cultural differences outside of Western settings, and do not explain why this gap is especially noticeable in this generation. Recent data suggests that Gen Z's views on sustainability are not fixed and can change quickly over time. Practical Implications: Companies should focus on transparency, affordability, and options for reusing or reselling products, while governments should invest in green infrastructure, environmental education, and stronger rules against misleading sustainability claims. It is crucial to understand Gen Z's complex relationship with sustainability as they become the most powerful consumer group in the coming decade. This review brings together recent research from 2025 to 2026 to offer a detailed view of the paradox of green consumerism among Gen Z, highlighting important areas for future research that include long-term studies and cross-cultural comparisons.

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 Keywords

Generation Z, green consumerism, attitude-behavior gap, sustainable purchasing, sustainability generation, social media influence, fast fashion, overconsumption, digital green activism, value-action gap, pro-environmental behavior, re-commerce, green washing, consumer behavior, climate anxiety

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Creative Commons Attribution 4.0 and The Open Definition

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Waste segregation plays a vital role in modern waste management by enabling efficient recycling, reducing landfill accumulation, and minimizing environmental pollution. The increasing volume of municipal waste generated from urbanization and population growth has created a demand for intelligent and automated segregation solutions. This paper presents SensorFusionBin: An IoT-Enabled System for Automated Wet, Dry, and Metallic Waste Segregation, designed to classify waste materials using embedded sensing technologies and automated control mechanisms. The proposed system integrates a moisture sensor, metal detection sensor, Arduino-based controller, servo-driven segregation mechanism, and IoT-enabled monitoring framework to identify and separate different categories of waste with minimal human intervention. Moisture sensing is utilized to detect biodegradable wet waste, while metallic objects are recognized through metal detection techniques. Materials that do not satisfy either condition are categorized as dry waste. The automated segregation process improves sorting accuracy, enhances hygiene, and supports sustainable waste management practices. Experimental evaluation demonstrates reliable waste classification and effective bin allocation under controlled conditions. The system offers a cost-effective, scalable, and environmentally responsible approach for smart homes, institutions, public facilities, and future smart city applications.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Waste Segregation, Internet of Things (IoT), Arduino Uno, Moisture Sensor, Metal Detection Sensor, Sensor Fusion, Smart Waste Management, Embedded Systems, Automation, Sustainable Environment.

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Creative Commons Attribution 4.0 and The Open Definition

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Distributed Denial of Service (DDoS) attacks represent one of the most significant security threats to Internet of Things (IoT) networks, causing service disruption, resource exhaustion, and degradation of network performance. This study presents FMDADM, a multi-layer DDoS attack detection and mitigation framework based on machine learning for stateful SDN-inspired IoT environments. The proposed framework utilizes flow-based network traffic features extracted from the DrDoS_DNS dataset and applies preprocessing, normalization, and feature selection using SelectKBest with mutual information. Ten highly relevant traffic attributes are selected to improve classification efficiency and reduce computational complexity. Multiple machine learning algorithms, including Decision Tree, Random Forest, Logistic Regression, Support Vector Machine, and Naive Bayes, are trained and evaluated to identify malicious traffic patterns. A layered detection strategy combines rapid filtering and detailed verification to enhance reliability and accuracy. The framework also incorporates stateful traffic analysis and real-time monitoring through a Flask-based dashboard. Experimental results demonstrate effective attack detection, reduced false alarms, improved response capability, and enhanced security for IoT networks.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

DDoS Detection, Internet of Things (IoT), Machine Learning, Random Forest, Decision Tree, Stateful Analysis, Network Security, Traffic Classification, SDN-Inspired Mitigation, DrDoS_DNS Dataset.

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Creative Commons Attribution 4.0 and The Open Definition

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Among the bioactive phytochemicals found in nutraceuticals and functional foods, polyphenols hold great importance as antioxidant, anti-inflammatory, cardioprotective, antibiotic-resistant, and therapeutic agents. By scavenging for free radicals, chelating metal molecules, and modulating oxidative stress pathways, they are instrumental in the prevention of chronic diseases caused by oxygen damage. Accurate analysis of polyphenols is challenging due to structural diversity, polarity differences, instability, and susceptibility to degradation during extraction and analysis. The main extraction methods for polyphenol isolation are conventional solvent extraction,, ultrasonic-assisted extraction, supercritical fluid extraction and pressurized liquid extraction; they are reviewed with regard to their mechanisms, benefits and drawbacks. Moreover, ORAC, DPPH, and FRAP are commonly employed antioxidant evaluation methods like CUPRAC for comparison. Additionally, it discusses recent developments in hyphenated analytical methods, improved method techniques for sample preparation, and method optimization strategies. The review highlights the importance of utilizing reliable analytical methods for quality control, standardization, and regulatory compliance in nutraceutical development

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Polyphenols, Nutraceuticals, RP-HPLC, Antioxidant Assays, DPPH,FRAP,CUPRAC,ORAC, Sample Preparation, Analytical Method Development

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Creative Commons Attribution 4.0 and The Open Definition

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This paper explores the intersection of medical humanities and literature in expressing illness. It introduces narrative medicine, which merges scientific expertise with narrative skills to validate patient experiences, particularly in articulating pain. Paul Kalanithi's memoir exemplifies how pain can inhibit communication, supporting Elaine Scarry's assertion that pain can render language ineffective. Silence, whether stemming from suffering or a conscious choice, is discussed as having multiple meanings, with Kalanithi highlighting the need for physicians to actively listen to patients' values. Various narrative techniques are analysed, such as fragmentation, repetition, and metaphor, to convey the chaotic experience of illness. The study emphasizes the ethical duty of clinicians to develop narrative competence and engage with patients' voices, a sentiment echoed by scholars Prabhu and Goldie, who argue that listening is crucial for accurate diagnosis and understanding patient identity. Literature not only expresses suffering but also offers the vocabulary and moral insights necessary for healing, positioning storytelling as essential in making sense of pain.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Medical humanities; Pain; Silence; Narrative strategies; Empathetic listening.

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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

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Aluminium sandwich plate, ANSYS Workbench, directional deformation, Hanning window, stiffener geometry, transient FEA.

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Creative Commons Attribution 4.0 and The Open Definition

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Over-the-Counter (OTC) drugs are medicines that can be purchased without a doctor's prescription and are commonly used for the treatment of minor illnesses such as fever, headache, cough, cold, acidity, allergies, and body pain. These medicines play an important role in self-care and primary healthcare by providing quick and convenient access to treatment for common health conditions.The present study was conducted to understand the pattern of OTC drug usage, consumer behavior, commonly sold medicines, and the role of pharmacists in guiding patients. A three-day survey was carried out at three local medical stores through observation and interaction with pharmacists and consumers. The findings revealed that analgesics, antacids, cough syrups, cold remedies, and vitamin supplements were among the most frequently purchased OTC medicines. Adults and middle-aged individuals were found to be the major users of these medications. Most consumers preferred OTC drugs because of their easy availability, affordability, and ability to provide quick relief from minor health problems. The study also highlighted the important role of pharmacists in recommending suitable medicines and providing dosage instructions. Although OTC medicines offer several benefits, their inappropriate use may lead to adverse drug reactions, overdose, drug interactions, and delayed diagnosis of serious illnesses.In conclusion, OTC drugs are an essential component of modern healthcare systems. However, public awareness, responsible self-medication practices, pharmacist counseling, and effective regulatory control are necessary to ensure their safe and rational use.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Over-the-Counter (OTC) Drugs,Self-Medication,Consumer Awareness,Pharmacist Counseling,Non-Prescription Medicines,Drug Safety

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Ageing (Jara) is a natural, progressive process involving structural and functional decline, reduced tissue regeneration, and susceptibility to chronic diseases. Ayurveda attributes premature ageing to Agni Mandya (metabolic weakness), Ama (toxin accumulation), and Dosha imbalance, particularly aggravated Pitta. Panchakarma, the prime detoxification therapy, offers preventive and rejuvenative benefits, with Virechana Karma (therapeutic purgation) being especially indicated for Pitta disorders and metabolic reset. This procedure eliminates morbid Doshas and Ama via the lower pathway, restores Agni, clears Srotas (body channels), and optimizes tissue receptivity for Rasayana therapy. From a modern perspective, Virechana may improve gut health, enhance liver detoxification, reduce systemic inflammation, and modulate oxidative stress--mechanisms linked to healthy ageing and longevity. This conceptual review integrates classical Ayurvedic insights with biomedical concepts to elucidate Virechana's potential in age modulation and preventive geriatrics. The synthesis suggests that Virechana Karma, when followed by Rasayana, could serve as an effective holistic intervention for delaying degenerative changes, preserving vitality, and promoting quality ageing.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Panchakarma, Virechana, Ageing, Jara, Rasayana, Detoxification, Longevity

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Creative Commons Attribution 4.0 and The Open Definition