Volume 14 | Issue 9 |

 Abstract

In the present scenario, the development of mobile phones is the strongest digital tools that enables farmers to avail government beneficiary schemes, status, information, and services, facilitating in farmers' empowerment in rural areas. The mobile phones ensure accessibility of information and services, interactive, user-friendly even helps to small and marginal farmers to get familiar with accessing through Apps. The government services are available through web portals, login with the help of an internet connection through computers and laptops. Smartphones with net facilities are facilitating two-way login to government websites. Firstly, in smartphones, farmers can log in through the Google search engine can visit the official website address of the concerned government departments. Secondly, Mobile Apps applications are developed by the government for farmers with user-friendly features, which can be accessed directly through login to the apps. These Apps are downloaded from Play Store and installed on their smart phone can easily access information services. This paper analyse role of Mobile apps in enhancing farmers access to government information and agricultural services in Karnataka state.

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Mobile Apps, Farmers, Agriculture information and services

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Traditional advertising is increasingly bypassed by Generation Z in favor of peer-like, algorithm-driven social commerce. This research paper investigates the structural impact of social media influencer marketing on Gen Z buying behavior, with a specific focus on the moderating role of micro-influencers . Utilizing a mixed-methods design and contemporary structural equation modeling (SEM) approaches, the study evaluates how dimensions such as perceived authenticity, niche expertise, and parasocial interaction moderate the pathway from influencer content exposure to consumer purchase intentions. Recent literature highlights that while macro-celebrities capture top-of-funnel reach, chronic over-commercialization has triggered deep ad fatigue among Gen Z. Findings demonstrate that micro-influencers significantly outperform broader tiers in driving actual conversions due to a heightened perception of trust, lower skepticism, and highly relatable community engagement

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Generation Z; Micro-Influencers; Purchasing Intentions; Perceived Authenticity; Social Commerce; Consumer Behavior.

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Yogashastre Niyamangam: Ekam Vishleshanatmakam Adhyayanam

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Yogashastre Niyamangam: Ekam Vishleshanatmakam Adhyayanam

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Lok Sangeet hamari cultural identity aur traditional values ka important part hai. Ismein use hone wale sthaniya vaadya yantra jaise dholak, bansuri, ektara, nagada aur sarangi sirf music ko beautiful banane ke liye nahi, balki local traditions, festivals, rituals aur social life ko express karne ka medium bhi hain. Ye instruments ek generation se doosri generation tak cultural knowledge aur folk traditions ko preserve karte hain. Modernization ke karan inka use kam ho raha hai, isliye inke conservation aur promotion ki zarurat hai. Yeh study lok sangeet mein sthaniya vaadya yantron ke cultural importance aur unki preservation ki need ko highlight karti hai.

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Lok Sangeet, Sthaniya Vaadya Yantra, Culture, Tradition, Cultural Heritage.

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 Abstract

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Mathematical Expression, Numerical Methods, Math symbols and Database

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Type 2 Diabetes Mellitus (T2DM) is a chronic metabolic disorder characterized by insulin resistance and progressive pancreatic ?-cell dysfunction. Effective glycemic control is critical to prevent microvascular and macrovascular complications associated with T2DM. This study aimed to evaluate the comparative efficacy and safety of monotherapy versus combination therapy in managing T2DM. A total of 100 patients were enrolled, with 50 receiving monotherapy and 50 receiving multi-drug therapy. Clinical outcomes, including fasting plasma glucose, postprandial glucose, and HbA1c levels, were monitored over six months. Results demonstrated that combination therapy produced a significantly greater reduction in HbA1c (1.8%) compared to monotherapy (0.9%), with manageable adverse effects. The findings suggest that combination therapy offers superior glycemic control by targeting multiple pathophysiological mechanisms of T2DM, while monotherapy remains effective during early disease stages. Personalized treatment strategies are recommended to optimize long-term outcomes in diabetic patients.

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Type 2 Diabetes Mellitus, Monotherapy, Combination Therapy, Glycemic Control, HbA1c, Antidiabetic Drugs, Insulin Resistance, Pharmacotherapy

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The study tries to explore the efficacy of toy pedagogy as a means of teaching mathematics at the foundational stage. The pretest-posttest control group experimental model, which is one of the quasi-experimental research designs, was used in the study. The study targets students of Government Primary Assamese Medium Schools in Nagaon district. The sample students of the study were selected by the purposive sampling method. The annual examination result of class 1 was taken as the basis for selecting the experimental and control groups. A total of 46 students of class 2 were selected into two groups from two schools. To assess student achievement after the intervention using Toy Pedagogy, a pre-test and post-test were conducted. In preparing the tests, three chapters were considered from the textbook. Achievement scores from pre-tests and post-tests of two groups, one exposed to Toy Pedagogy and the other to traditional teaching methods, were analyzed to evaluate the relative effectiveness of the Toy Pedagogy approach. Analysis and interpretation of the data reveal that among these two methods, teaching with toy pedagogy was the more effective method. The effect of teaching different groups of students by these two different methods was found to be significant, but teaching by toy pedagogy was more effective than the traditional method. Teachers' positive perceptions of toy pedagogy in mathematics education are vital for making the teaching-learning process more effective. New perspectives and ideas can improve mathematics education in future courses of action at the foundational level.

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Teaching, Mathematics, Pedagogy, Toy based, Play based activities, early childhood, foundational stage, academic achievement _______________

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 Abstract

विश्व में सर्वोत्तम संस्कृतियों में बृज प्रदेश की संस्कृति का नाम आता है। बृज संस्कृति से अभिप्रेत भारत वर्ष का हृदय है। भारत में बृज जनपद की संस्कृति महत्वपूर्ण तथा महिमामयी है। इसी कारण बृज का स्थान सर्वश्रेष्ठ माना गया है। वर्तमान समय में मथुरा जिले के समीपवर्ती प्रदेश को बृज के नाम से जाना जाता है। बृज भूमि की चैरासी कोस की परिक्रमा की यात्रा हजारों वर्ष पुरानी है। चैरासी कोस की यात्रा का उल्लेख वेद, पुराण, श्रुति ग्रन्थ संहिता आदि में भी मिलता है। इस परिक्रमा के अंतर्गत 1300 से अधिक गांव 1000 सरोवर, 12 वन, 25 उपवन 16 कदम्बखण्ड, देवी मंदिर और अनेक पर्वत और यमुना घाट पड़ते हैं। वराह पुराण के अनुसार पृथ्वी पर 66 अरब तीर्थ हैं और सभी तीर्थ चातुर्मास में बृज में आकर निवास करते हैं। इसीलिए हजारों श्रदालु बृज परिक्रमा के लिए आते हैं। ऐसी मान्यता है कि 84 कोस की परिक्रमा लगाने से 84 लाख योनियों से छुटकारा मिल जाता है।

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बृज प्रदेश, सांस्कृतिक यात्रा, बृज संस्कृति 84 कोस परिक्रमा।

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Generative Artificial Intelligence; Higher Education; AI Governance; Human-AI Cognitive Governance; Authority Specification Gap; HACGI; Human Authority

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Choosing a biodegradable wound-dressing formulation that meets mechanical strength, controlled breakdown, sufficient porosity, a biocompatible pH, and antimicrobial effectiveness all at once is traditionally done through slow, resource-heavy lab testing across an enormous space of candidate materials and coatings. This paper introduces BEST (Biomaterial and Engineering Suitability Tool), an end-to-end decision-support platform that classifies a candidate wound-dressing formulation using ten physico-chemical input measurements, without needing the material's identity to be specified. The system pairs a soft-voting ensemble made up of a Random Forest model and a Gradient Boosting model, trained on a domain-informed synthetic dataset of 2,000 samples, inside one scikit-learn pipeline, and serves it through a Flask REST API consumed by a React single-page front end. In addition to a predicted class, the system produces a property-level rating, an explanation based on feature importance, and a templated natural-language suggestion for the next experimental step. The deployed ensemble reaches 88.0% accuracy on the held-out test set and 85.2% (plus or minus 1.1%) across five-fold cross-validation, with the antimicrobial index and biodegradation rate standing out as the strongest predictors. The platform additionally includes several decision-support add-ons -- an explainable-AI feature-impact display, a molecular structure viewer for bioactive coating compounds, an automated formulation optimizer, a sustainability (BioScore) metric, a side-by-side formulation comparison tool, and an exportable PDF report -- turning it into a full first-pass screening assistant rather than a plain classifier. This paper covers the motivation, dataset construction, system architecture, implementation, results, limitations, and directions for future research on the platform.

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 Keywords

Machine Learning, Biomaterials, Wound Dressing, Ensemble Learning, Decision Support, Explainable AI

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