Volume 13 | Issue 10

 Abstract

Background: Abdominal obesity is a key predictor of metabolic disorders and cardiovascular diseases, often overlooked in young adults. Early identification through waist circumference (WC) is a simple, cost-effective screening method to prevent future complications. Objective: To find the prevalence of abdominal obesity among healthy individuals aged 18-30 years using waist circumference in Pune. Methods: A cross-sectional study was conducted on 370 participants aged 18-30 years in Pune. WC was measured using standardized ACSM guidelines. Data was analyzed using descriptive statistics. Results: Among 370 participants, 195 were females and 175 males. WC within normal limits. Only 4% of males and 5% of females were found to have high WC, indicating low abdominal obesity prevalence in this age group. Conclusion: Abdominal obesity was low among participants aged 18-30 in Pune. However, given its strong association with future metabolic complications, periodic screening and lifestyle interventions should be encouraged even among young adults.

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Abdominal obesity, Waist circumference, Young adults, Cross-sectional study, Central obesity

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In India, acceptance of technology is increasingly contingent upon whether interfaces communicate in the languages and visual grammars of their users. This research employs a comparative multiple-case methodology to analyse the impact of vernacular design on the adoption, persistence, and trust in regional-language applications catering to Hindi, Bengali, and Tamil users. The corpus utilizes interface artifact analysis, in-app string corpora, structured survey responses, India-specific app store reviews, and sectoral indicators. Dailyhunt, InShorts, ShareChat, Pratilipi, Koo, Lokal, and PhonePe are some of the main cases. Cross-case pattern matching connects vernacular design elements to perceived ease of use and perceived usefulness in the Technology Acceptance Model, as well as to social influence and facilitating conditions in UTAUT (Davis, 1989; Venkatesh et al., 2003; Yin, 2017; Eisenhardt, 1989). Results indicate that typography optimised for script legibility, localised numerals and calendars, culturally comprehensible iconography, and microcopy composed in colloquial registers diminish cognitive load and minimise code switching, thereby enhancing task success and user attitudes (Sweller, 1988; Norman, 2013). Voice input and mixed-script search reduce input friction for inflected or agglutinative forms, and error messages that follow polite language rules help people recover and build trust. The research enhances the concept of vernacular congruence as a precursor to acceptance, functioning through two mechanisms. Cognitive efficiency occurs when interaction patterns are congruent with users' scripts and literacy practices. Affective resonance occurs when tone, metaphors, and onboarding narratives are in line with how people in the area usually talk to each other. Because most new internet users in India don't speak English, these mechanisms are important for inclusive growth and for setting standards for accessibility policy, content governance, and interface design (Google & KPMG, 2017). The case synthesis elucidates the significance of vernacular design for acceptance and provides practical recommendations for product teams and regulators.

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Vernacular design; Regional language apps; Technology acceptance; TAM and UTAUT; Cognitive load; Vernacular congruence.

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Diabetes mellitus (DM) is a chronic metabolic disorder characterized by elevated blood glucose levels resulting from defects in insulin secretion, insulin action, or both. It is broadly classified into Type 1 Diabetes Mellitus (T1DM), an autoimmune destruction of pancreatic ?-cells leading to absolute insulin deficiency, and Type 2 Diabetes Mellitus (T2DM), which involves insulin resistance and relative insulin deficiency. Globally, Diabetes is a leading cause of morbidity and mortality due to its long-term complications, including cardiovascular disease, nephropathy, neuropathy, and retinopathy. The prevalence of T2DM has been rising steadily due to sedentary lifestyles, unhealthy dietary habits, obesity, and aging populations. In Ayurveda, diabetes can be correlated to Prameha. Prameha is a kapha pradhana tridoshajanya vyadhi, which is characterised by excessive and turbid urination. It can be divided into three types based on doshik predominance which is also subdivided into further types they are Kaphaja (10 types), Pittaja (6 types), Vataja (4 types), which is also Avasthanusara bheda of this vyadhi. The management of Prameha is mentioned in Ayurveda as preventive and curative aspects. Ayurveda has recommended an appropriate use of Oushadha Yogas along with proper Pathya (wholesome) Ahara, and Viharas. On the same principles, a patient was treated at OPD basis, this case report analyses the same. A male patient, aged 50 years, diagnosed case of Prameha 15 years back presented with increased frequency of micturition, excessive thirst and generalised weakness. The treatment planned was use of Shamana Oushadhas along with proper Pathya (wholesome) Ahara, and Vihara for 60 days. At the end of the treatment, marked reduction seen on the signs and symptoms like increased urination, generalised weakness and excessive thirst and on blood sugar levels.

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Prameha, Diabetes Mellites, Shamana Oushadha

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The changing environment of performance management is critically examined in this review study, which highlights a significant shift from traditional annual evaluations to dynamic Strategic Performance Management Systems (SPMS). It fully examines the significant influence SPMS has on two important organizational imperatives: increasing worker productivity and guaranteeing strong attainment. Through a comprehensive review of the literature, the study demonstrates how SPMS, which is characterized by its fundamental principles of constant, real-time feedback, careful goal alignment at all organizational levels, committed coaching, and advanced technology integration, creates a workforce that is genuinely transformed. This all-encompassing strategy develops a workforce that is more profoundly engaged, consistently skilled, and ultimately highly accountable--all of which are critical for managing the complexity of modern business. The review meticulously discusses the intrinsic mechanisms through which SPMS demonstrably enhances both individual employee output and overall organizational performance, illustrating how enhanced clarity, ongoing constructive dialogue, and a strong developmental focus drive superior results. Additionally, it addresses the common yet significant implementation challenges organizations frequently encounter when adopting or refining SPMS, offering practical insights and strategic considerations to overcome potential barriers. Concluding, the paper identifies and analyzes the key future trends poised to further reshape the performance management field, forecasting innovations that will continue to optimize human capital and drive sustained organizational success in a rapidly changing world.

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Strategic Performance Management Systems, Employee Productivity, Continuous Performance Management, Feedback, HR Technology.

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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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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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Krishi Vikas Ki Samsyayen Evam Sambhavanayen : Bhagalpur Jila Ka Ek Bhaugolik Adhyayan

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Krishi Vikas Ki Samsyayen Evam Sambhavanayen : Bhagalpur Jila Ka Ek Bhaugolik Adhyayan

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Artificial Intelligence (AI) has rapidly emerged as an influential force across various domains within healthcare, especially surgery, transforming conventional surgical practices into highly sophisticated, data-driven interventions. This systematic review comprehensively examines the integration and impact of AI technologies in surgical practices spanning preoperative, intraoperative, and postoperative phases. The primary objective is to critically evaluate current evidence regarding the effectiveness, safety, cost-efficiency, and patient-centred outcomes associated with AI-enhanced surgical interventions. A detailed and rigorous literature search was performed across multiple databases from January 2013 to August 2023. Search strategies employed targeted keywords such as "Artificial Intelligence," "Machine Learning," "Deep Learning," "Robotic Surgery," "Computer-Assisted Surgery," and "Predictive Modelling." Two independent reviewers systematically screened articles and extracted pertinent data, resolving discrepancies via consensus or third-party arbitration. Methodological quality was appraised using standardized tools ensuring comprehensive and robust assessment. From an initial pool of 4,126 records, 75 high-quality studies met inclusion criteria. Results demonstrated substantial enhancements in surgical efficiency, particularly through reductions in operative times most pronounced in robotic-assisted and minimally invasive surgeries. AI-driven interventions consistently demonstrated improved surgical precision. Additionally, patient-centred outcomes, including reduced postoperative pain, quicker return to daily activities, and higher patient satisfaction, further emphasized AI's beneficial role. However, evidence regarding cost-effectiveness presented mixed results due to initial investment costs for AI infrastructure balanced against long-term economic benefits from improved clinical outcomes and reduced hospital stays. In conclusion, AI represents a transformative advancement in surgery with substantial potential to enhance clinical efficiency, accuracy, patient safety, and overall surgical outcomes. Despite current methodological limitations, ongoing technological improvements, interdisciplinary collaboration, and rigorous prospective research are essential to realize AI's full promise in surgical practice.

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Artificial Intelligence, Machine Learning, Deep Learning, Robotic Surgery, Surgical Outcomes, Systematic Review, Surgical Precision, Patient Safety, Cost-effectiveness, Clinical Efficiency

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Ethanolic extracts of Piper betel (betel leaf) and Lantana camara (lantana) were used in the formulation and evaluation of an antibacterial ointment. Due to their medicinal qualities, which include antibacterial qualities, both of these plants have long been utilized in traditional medicine. Lantana camara and Piper betel ethanolic extracts were made for this study and added to a base ointment. A variety of bacterial and fungal strains were tested for the ointment's antibacterial efficacy using conventional microbiological methods. The physicochemical characteristics of the ointment, such as its stability, pH, consistency, and spreadability, were evaluated. The formulation showed potential efficacy against common infections, and the results showed significant antibacterial activity. In order to verify the ointment's biocompatibility, the study also evaluated its safety profile. The creation of the ointment by mixing these plant extracts offers a natural substitute for antibacterial therapy, which adds to the increasing demand for plant-based pharmaceuticals.

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Lantana Camara, Piper betel, Antimicrobial Ointment, Ethanolic Extract

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The present study examines the dynamic relationship between market volatility and option trading activity in India's derivatives market from 2018 to 2025. The Indian derivatives segment, which is dominated by the NIFTY index options, has experienced exponential development in both trading volume and investor participation, rendering it a critical area for volatility assessment. The study employs correlation and time-series econometric techniques to investigate whether fluctuations in option trading activity contribute to changes in market volatility, applying secondary data from the National Stock Exchange (NSE) and India VIX. In order to investigate the strength and direction of the relationship between these variables, descriptive statistics, correlation matrices, and regression models are implemented. The findings suggest a substantial and positive correlation between volatility and trading activity, suggesting that high levels of trading intensity frequently occur in conjunction with increased market uncertainty. The results contribute to the comprehension of behavioural patterns in India's derivatives market and provide investors, risk managers, and regulators with valuable insights for the development of more effective volatility management and monitoring frameworks.

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Key Words: NIFTY index, Volatility, India VIX, National Stock Exchange

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Public sector construction projects frequently face scheduling challenges, leading to delays, cost overruns, and compromised quality. These challenges often stem from complex regulatory environments, bureaucratic processes, limited resources, and coordination failures among stakeholders. This paper investigates key factors contributing to scheduling inefficiencies in public construction projects, using case studies and survey data from multiple government-backed infrastructure developments. The study identifies root causes, quantifies their impact on project timelines, and proposes solutions such as integrated scheduling tools, stakeholder communication enhancement, and adoption of digital construction technologies like BIM.

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Public sector, construction scheduling, project delay, resource allocation, stakeholder coordination, construction project management, BIM, risk management.

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This study was conducted to assess the effectiveness of supportive psychotherapy in raising self-esteem among elderly individuals residing in selected old age home in Delhi NCR. Self-esteem, defined as a person's belief in their own worth and value, plays a critical role in shaping choices, resilience, and overall psychological well-being. A pre-experimental one-group pre-test post-test design was adopted, using non-probability purposive sampling to select 30 elderly participants. The study aimed to (1) assess baseline self-esteem levels, (2) evaluate the impact of supportive psychotherapy on self-esteem, and (3) determine the association between post-test self-esteem scores and selected demographic variables. Pre-test findings revealed that 14 participants (46.6%) had low self-esteem, while 16 (53.3%) had average self-esteem. Post-test results showed a marked improvement, with 28 participants (93.3%) exhibiting average self-esteem and 2 (6%) achieving high self-esteem. Statistical analysis using Fisher's exact test indicated a significant association between post-test self-esteem scores and demographic variables such as educational status, marital status, and occupation prior to admission to the old age home (p < 0.05). Other demographic variables showed no significant association (p > 0.05). The study concludes that supportive psychotherapy is effective in enhancing self-esteem among elderly individuals.

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Self-esteem, supportive psychotherapy, elderly people, effectiveness, assessment.

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