Volume 13 | Issue 10 |

 Abstract

Ayurveda, one of the oldest holistic medical sciences, is gaining renewed global relevance in the 21st century. However, its reliance on practitioner-dependent, subjective diagnostic methods has hindered its scalability and international acceptance. This review provides a chronological literature survey of Artificial Intelligence (AI) integration into Ayurveda, examining developments from conceptual frameworks to modern research automation. Beginning with pre-2015 feasibility studies and the emergence of Ayurgenomics, the paper traces the evolution of AI applications in Prakriti classification, Vikriti quantification, therapeutic personalization, and drug discovery. Further, it highlights emerging technologies such as Agent-Based AI Systems (AAIS) and predictive health analytics that promise to redefine Ayurveda as a global, data-driven science. Critical challenges--including data scarcity, model interpretability, and ethical governance--are also analyzed. The review concludes that the fusion of Ayurveda and AI, termed "Ayurveda Intelligence," represents not just modernization but a paradigm shift in healthcare delivery and research automation.

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 Keywords

Ayurveda, Artificial Intelligence, Machine Learning, Prakriti, Vikriti, Diagnostic Standardization, Predictive Analytics, Drug Discovery, Ayurveda Intelligence

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In order to create lightweight concrete, the addition of an artificial aggregate made from plastic waste was investigated. After designing five different mixes and testing the qualities of both fresh and hardened concrete while gradually increasing the quantity of artificial aggregate, it was discovered that the slump As the quantity of artificial aggregate in the concrete rose, the concrete's density fell. Both the tensile and compressive In stage two, the blend that best met the study's requirements for density and compressive strength was selected for additional research. Because the manufactured aggregate has a lower density than natural aggregate, this ideal mix substituted 15% of the natural material by weight, or more than 37% of the volume.

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Optimum replacement , Recycled Plastic , Strength

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Back pain is a prevalent musculoskeletal disorder, particularly among individuals engaged in repetitive and sedentary work. Female tailors represent a high-risk group due to prolonged sitting, inadequate ergonomic setups, and repetitive arm and shoulder movements. This review synthesizes current evidence on the causes, prevalence, pathophysiology, and preventive measures associated with occupational low back pain among female tailors. Recognizing the multifactorial origin of back pain in this occupational group highlights the need for targeted ergonomic interventions and education. Prevention strategies must include workplace modifications, awareness programs, and structured exercise regimens.

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Low Back Pain, Female Tailors, Occupational Health, Ergonomics, Musculoskeletal Disorders, Posture-Related Pain

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Digital parenting has emerged as a crucial aspect of modern parenting, given the pervasive role of digital technology in children's lives. This review article explores the concept of digital parenting, its significance in ensuring children's safe and productive engagement with technology, the sources of digital parenting knowledge, challenges faced by parents, and strategies to enhance digital literacy within families. The article also highlights the role of health professionals, especially nurses, in promoting awareness and guiding parents toward safe digital practices.

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Digital Parenting

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An online community where people congregate to create, share, and alter their thoughts is known as web-based social networking. thoughts regarding any data. Online long-distance social networking communication has significantly altered how people communicate and work together during the past ten years. The utilization of the Internet has expanded decisively throughout the course of recent many years, and it has had a significant influence on how people interact and behave. Although frequent communication between friends and family members has been linked to internet use by school pupils, face-to-face interaction has decreased. Internet addiction has been characterised as an instinct rather than intoxication. Student internet addiction has a negative impact on their social, mental, and physical well-being. The objective of the ongoing review is to look at what social media means for Students' mental health with regards to pressure, tension, and sorrow. In this review, the overview technique was utilized. An example of 40 students of 9th to 12th classes, ranging in age from 16 to 18, was randomly chosen from the Varanasi district's various schools, with 20 students involving social media for under 2 hours and 20 students involving it for over 2 hours. The information was analysed using mean, standard deviation, and the t-test to determine the effect of social media on young people's mental health. The findings show a substantial difference between students who use social media for less than 2 hours and young people who use it for more than 2 hours in terms of the levels of resentment, anxiety, and stress. We could therefore conclude that students who use social media for more than 2 hours have worse mental health than those who use it for fewer than 2 hours.

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Keywords: Social Media, Mental Health, Students, User, Internet addiction, Varanasi.

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Pan facial fractures represent one of the most challenging scenarios in trauma and reconstructive surgery. In addition to complex skeletal disorganization, surgeons and anaesthesiologists must address life-threatening airway compromise. The decision regarding airway management is critical, as it directly influences surgical access, patient safety, and long-term outcomes. Conventional orotracheal and nasotracheal intubation techniques are often precluded due to fracture patterns, cerebrospinal fluid leaks, or the need for intraoperative maxillomandibular fixation. Over the past three decades, alternative strategies such as submental intubation, submandibular intubation, tracheostomy, and fibreoptic techniques have evolved to address these unique needs. This review consolidates current evidence on airway management strategies in pan facial fractures, examining indications, technical considerations, complications, and outcomes. Algorithmic approaches are proposed to guide clinical decision-making, while highlighting innovations such as ultrasound-assisted techniques.

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Pan facial fractures; Airway management; Submental intubation; Tracheostomy; Fibreoptic intubation; Maxillofacial trauma; Difficult airway.

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Unlocking India's Hidden Gold Wealth" A Path to Economic Balance and Growth

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Gold, Hidden Gold, GDP, Economy, Wasiq Bashir, Wasiq Shan,

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Abstract This paper examines how Kokborok literature has functioned as a vehicle for preserving and transmitting the cultural identity of the Tipra (Tripuri) people of Tripura. It traces the historical trajectory of Kokborok from strong oral traditions to an expanding written corpus, analyses thematic currents in poetry, prose and drama, and assesses modern institutional and community initiatives that support revitalization and standardization. Drawing on historical accounts, recent policy documents, and contemporary studies, the research highlights both achievements (dictionaries, translations, curriculum inclusion) and ongoing challenges (script debates, urbanization, language shift). The study concludes with recommendations for strengthening literature-based cultural preservation through education, publishing support, and participatory cultural programmes.

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Keyword:- KOKBOROK LITERATURE, TRIPURA CULTURE, KOKBOROK SCRIPT, ORAL TALES.

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The main vision of the Pradhan Mantri POshan SHAkti Nirman (PM POSHAN) scheme is to increase the school enrolment of children, provide nourishment and eradicate classroom hunger and malnutrition. Several Methods have been used to ensure the effective implementation of the scheme, but none of them covered all the aspects of the scheme. The primary objective of this study is to develop a comprehensive, quantitative, efficient, and user-friendly scoring scale that encompasses all aspects of the PM POSHAN scheme. The effectiveness of this scale will be assessed in various schools, aiming to improve the monitoring process and enhance the implementation of the scheme. Both qualitative and quantitative methods were used to develop the scale. A purposive sampling technique was used to select the schools and associated kitchens to test the scale. The results revealed that PM POSHAN scale evaluation in schools showed compliance with government guidelines in purchasing, storage, and cleaning of cooking areas. However, improvements were needed in food preparation, cooking, personal hygiene, school authority involvement, beneficiary satisfaction, and infrastructure. Quality assurance results were concerning, revealing non-compliance with guidelines and unacceptable outcomes. To conclude, this is the first-ever tool developed to date, covering all the categories included in the guidelines. This will thus help in the effective monitoring of the scheme. Moreover, its availability in digital format and local language (Marathi) adds to its accessibility.

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PM POSHAN Scheme, Monitoring, Adolescents, Schools, Mumbai

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Data Mining is one of the knowledge discovery steps in database, in which modeling techniques are applied. In this research work, the performance analysis of classification algorithms like K - Means and FCM methods are applied for dealing with medical database for mining. To increase the efficiency of mining process, some preprocessing needs to be done to the data. Medicinal data mining methods are used to analyze the medical data information resources. The effort to develop knowledge and experience of frequent specialists and clinical selection data of patients collected in databases to facilitate the diagnosis process is considered a valuable option. Diagnose the Diabetes, Lung and Liver diseases are a significant and tedious task in medicine. For detecting a disease number of tests should be required from the patient. But using data mining technique the number of test should be reduced. This reduced test plays an important role in time and performance. This research work analyzes and performance study about how data mining techniques are used for predicting the diabetes, lung and liver diseases. In this work, use familiar two data mining algorithms and performance evaluation of different UCI Repository datasets like Diabetes, Liver Disorder and Lung Cancer data on the basis of Performance Measure and Cost Measure. Experimental results showed the good accuracy when applied to the adjust data.

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KNN, SVM, K-Means, K-Medoids, Fuzzy

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