Volume 12 | Issue 12 |

 Abstract

Ayurveda has two main aims - one is to maintain the health of a healthy individual and the second is to treat a diseased person. Rasayana Chikitsa has a significant role in meeting Ayurveda's first goal. Rasayana Chikitsa is also a part of Ashtanga Ayurveda which presents its importance. Rasayana is any herb, food, or activity that confers youthfulness and cures diseases. If taken properly, the Rasayana prevents early aging and keeps you young and active both physically and mentally. Rasayana primarily refers to nourishment on all scales, from the macro to the micro-cellular level. All Rasayanas are nutrition promotores in general but there are certain target-specific Rasayana Medhya Rasayana for the brain, Hridya Rasayana for the heart, Chakshusya Rasayana for the eye, etc. It accelerates the formation of new Dhatus and retards aging. This way, it comprehends our body's vital energy and boosts immunity. A good intellectual power acts as a catalyst in all aspects of life. Ayurveda provides a list of herbs known for nootropic activity and their multi-dimensional utility in various conditions. Yashtimadhu, Guduchi, Shankhapushpi, and Mandookparni are the four Medhya Rasayana that Acharya Charaka briefly explained. It is said that Shankhapushpi is the best among all Medhya Rasayana Dravya. These drugs enhance one's capacity for acquiring knowledge (Dhi), retention (Dhriti), and memory (Smriti). Medhya Rasayana medications are used to promote health and prevent and treat mental illnesses in people of all ages. Recently there has been a tremendous urge to explore medicinal plants globally for improving cognitive function owing to their less adverse effects. Throughout the Nighantu period, more cognitive enhancers were occasionally introduced to classical literature under the label Smritikara Dravya and in folk practice.

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 Keywords

Medhya Rasayana, Memory, Nootropics, Intellectual power, Medha, Dhi, Dhriti, Smriti.

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Diabetes, a major global source of morbidity, must be identified early in order to be effectively managed and complications avoided. In this work, we propose a machine learning method for diabetes prediction that makes use of a Support Vector Machine (SVM) model. We carried out comprehensive preparation using a publically accessible dataset, which included choosing pertinent properties, addressing missing values, and normalizing features. Several kernels (linear, polynomial, and RBF) were used to optimize the SVM model, and performance was enhanced through hyperparameter adjustment. The model's effectiveness was validated using evaluation measures such as accuracy, precision, recall, F1-score, and ROC-AUC, which achieved [certain performance criteria]. Our results demonstrate the potential of SVM in clinical decision support systems for the diagnosis of diabetes. In order to improve model resilience, future research will examine sophisticated feature engineering approaches and broaden the dataset to include a variety of populations.

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 Keywords

Diabetes Prediction, Support Vector Machine (SVM), Pima Indians Diabetes Dataset, Machine Learning, Radial Basis Function (RBF) Kernel, Hyperparameter Tuning, Accuracy, Precision, Recall, F1-Score, ROC-AUC, Data Preprocessing, Feature Selection, Healthcare Analytics, Early Diagnosis

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The National Education Policy (NEP) 2020 emphasizes holistic education, recognizing the critical role of nutritional education in supporting students' physical, cognitive, and emotional development. Nutritional education aligns with NEP's goals of fostering lifelong healthy habits, improving academic performance, and reducing health disparities in India. Integrating nutritional knowledge into school curriculums helps students understand the importance of a balanced diet, promoting both personal and community well-being. NEP 2020 also enhances this focus by advocating experiential learning methods, such as school kitchen gardens and improved mid-day meal programs, to reinforce practical knowledge. While the policy sets a strong foundation for nutritional education, its effectiveness will depend on addressing challenges like resource limitations, cultural diversity, and monitoring outcomes. In conclusion, NEP 2020's approach to nutritional education holds promise for developing healthier, more informed citizens, contributing to India's vision of a balanced, inclusive, and skill-oriented education system.

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 Keywords

Nutrition, Education, NEP-2020, Importance, Effectiveness

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The Bharatiya Nyaya Sanhita (BNS), India's new criminal code, has introduced major changes in the country's criminal laws. The provisions related to rape in BNS have been structured to protect female sexual assault victims. This has raised a concern about the gender-biased approach of this code. This research paper critically examines Bharatiya Nyaya Sanhita's provisions on rape from a gendered perspective, analysing whether the legal framework perpetuates gender bias and excludes male and non-binary victims of sexual violence. This paper calls for a shift in India's legal framework on rape to be gender-neutral for a more inclusive legal approach that ensures justice and support for all, regardless of their gender.

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 Keywords

gender-neutral, sexual violence, rape laws, BNS.

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Black cotton soil, characterized by its high swelling and shrinkage properties, poses significant challenges to construction and infrastructure development. Stabilizing this soil is crucial for improving its engineering properties and ensuring structural durability. This study explores the use of sugarcane bagasse ash (SCBA), an agricultural waste by-product, as a sustainable stabilizing agent for black cotton soil. SCBA, rich in silica and alumina, reacts with soil particles to enhance strength and reduce plasticity. Laboratory tests were conducted to evaluate the effects of varying SCBA percentages on soil properties, including Atterberg limits, compaction characteristics, unconfined compressive strength (UCS).The results show a significant improvement in soil strength, reduced swelling potential, and enhanced load-bearing capacity with the optimal SCBA content. This approach not only improves soil performance but also promotes waste recycling and environmental sustainability. The findings demonstrate the potential of SCBA as a cost-effective and eco-friendly material for soil stabilization.

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Atterberg Limits, Compaction

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This paper introduces the VITA Healthcare Pilot, an innovative AI-powered platform designed to revolutionize personalized healthcare services. Utilizing the advanced capabilities of Google Generative AI (GenAI), the system offers a comprehensive suite of functionalities, including real-time symptom analysis, health monitoring, medication management, and emergency navigation. By integrating cutting-edge artificial intelligence with user-centric design principles, the VITA Healthcare Pilot aims to address critical gaps in healthcare delivery. This study explores the platform's architecture, methodology, and experimental outcomes, highlighting its transformative potential to enhance accessibility, patient engagement, and the efficiency of healthcare systems. Additionally, the paper discusses future enhancements such as telemedicine integration, wearable device support, and blockchain-enabled data security to further expand its impact

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 Keywords

AI in Healthcare, Generative AI, Symptom Analysis, Health Monitoring, Emergency Navigation

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This paper provides a comparative analysis of the right to privacy in India and the United States, examining the legal and constitutional frameworks in both countries, and evaluating their alignment with international human rights standards, particularly those outlined in the Universal Declaration of Human Rights (UDHR). Privacy is recognized as a fundamental human right that safeguards personal liberties and protects individuals from unwarranted intrusion into their private lives. While both India and the U.S. offer legal protections for privacy through constitutional provisions and legislation, the scope and effectiveness of these protections vary significantly, especially in the digital age. In India, the right to privacy is enshrined under Article 21 of the Constitution, with landmark rulings like Puttaswamy v. Union of India (2017) affirming its fundamental status. Additionally, India is in the process of implementing the Personal Data Protection Bill to regulate data privacy. In contrast, the U.S. relies on the Fourth Amendment and sectoral laws like the Privacy Act and the Electronic Communications Privacy Act, but challenges remain, particularly concerning the balance between privacy and national security, especially in the post-9/11 context. The paper highlights key differences, such as the U.S.'s lack of comprehensive federal data protection laws compared to European standards, and India's struggle with surveillance programs like Aadhaar. Both countries face significant challenges in ensuring privacy in the digital era, where surveillance, data breaches, and technological advancements complicate privacy protection. The paper concludes by proposing stronger privacy regulations, better oversight of surveillance activities, and enhanced international cooperation to address the global nature of data flows and privacy concerns in the digital age.

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PRIVACY , LAWS

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The present study was undertaken to evaluate the toxicity and effects of a commercial formulation of the herbicide, Glyphosate on liver enzyme system in the freshwater air breathing fish Labeo rohita. The 24, 48, 72 and 96 h LC50 of Glyphosate, calculated by Direct interpolation Method, were determined to be 0.018ml/liter, 0.015 ml/liter, 0.012 ml/liter and 0.009 ml/liter respectively. In addition to concentration and time dependent decrease in mortality rate, stress signs in the form of behavioural changes were also observed in response to the test chemical.

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Glyphosate, toxicity, Labeo rohita, oxidative stress, environmental pollution, LC50.

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While the use of aloes has been useful in making beauty and cosmetic products more attractive, ingredients to check unwanted prices on abuse could be managed through a concept of cosmetovigilance. Aloe Vera: You have probably heard in some natural cosmetic formulas because of its multifunctional actions, Aloe vera has earned a place ingredient that is already parament for moisture and hydration to hydrate or oriented from home care consumers as it acts moisturizing, anti-inflammatory, healing; This abstract examines the optimization given by Aloe Vera as an adjuvant for cosmetic efficacy and opens accessible approaches to unsafe considerations of cosmetovigilance. However, the challenges for Aloe Vera continue to be its efficacy and safety for all who are now exposed to many hair care products one-handed: mimicking the excellent skin-care world. Although its natural ingredients are fantastic for maintaining skin hydration, counteracting the signs of aging, and treating acne; if used long term can have side effects which may include allergic reactions or your own body getting too good at moisturising itself... over-moisturisation. To maintain the benefits of Aloe Vera in cosmetics, while preventing risks from overshadowing consumer safety, it becomes indispensable follow-up by cosmetovigilance practices. Such an overview in the current review is essential to highlight balancing strategies i.e., cosmetic benefits provided by Aloe Vera should be balanced with strict safety evaluations which are necessary for safeguarding consumer health and maintaining the integrity of a product. Incorporation of thorough safety assessments; and consumer feedback during the Product Development Lifecycle would promote the overall reliance on safe Aloe Vera-based cosmetics. This will attempt to synchronize the beauty benefits that are obtained from Aloe Vera with proper use while building trust amongst consumers and responsible cosmetic innovation.

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 Keywords

Cosmetovigilance , moisturizer, anti inflammatory aleovera

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Creative Commons Attribution 4.0 and The Open Definition

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The practicality of rule-based techniques for text sarcasm detection is investigated in this study. Although the discipline has recently been dominated by deep learning techniques, rule-based approaches provide explainability and can work well in some applications. In order to detect sarcastic words, we suggest an improved rule-based framework that makes use of sentiment analysis, linguistic patterns, and contextual clues. Our approach combines a thorough set of guidelines drawn from sardonic expression analysis and linguistic theory. We test our method on benchmark datasets and show that it is effective at detecting sarcasm, especially when explainability is important or training data is limited.

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 Keywords

Sarcasm Detection, Natural Language Processing (NLP), Sentiment Analysis, Machine Learning, Deep Learning, Rule-Based Systems

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Creative Commons Attribution 4.0 and The Open Definition