Volume 14 | Issue 1 |

 Abstract

Financial literacy is essential for young adults as they begin to manage their own finances in an increasingly complex economic environment. This study examines financial literacy levels and their determinants among non-professional undergraduate students in Latur City using a structured questionnaire aligned with the framework of the National Institute of Securities Markets. The findings indicate a moderate level of financial literacy, with commerce students and female students showing slightly higher financial awareness than others. However, gender and field of study do not have a significant influence on financial literacy, suggesting that knowledge gaps are broadly distributed across student groups. Given the rapid expansion of digital financial services and growing access to credit in India, this moderate literacy levels raise concerns about students' vulnerability to poor financial decisions and digital financial risks. The study recommends integrating financial literacy education into undergraduate curricula across all disciplines, emphasising both knowledge and practical application, and strengthening institutional partnerships to promote responsible financial behaviour among young adults.

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 Keywords

Financial Literacy, Financial Knowledge, Financial Behaviour, Financial Attitude.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The AmazeHair app represents an industry first fusion of artificial intelligence and augmented reality, in what is a step-change in personal hair care and digital wellbeing. This article will examine the myriad functionalities of the platform, which uses AI-powered image analysis to evaluate vital hair and scalp health factors such as dandruff, hair fall, dryness and split ends in real-time image mining on top of user-provided inputs. Use of machine learning algorithms for precise diagnostics, the AI-enabled device provides customized care recommendations based on real-time and historical data to its users. The AR features of the system support immersive virtual hairstyle try-on and treatment previews, resulting in realistic and interactive experiences that increase engagement by guiding users towards informed aesthetic decisions. AmazeHair has enhanced its ecosystem by adding the Hair Health Tracker and Routine Scheduler to support longitudinal patient engagement with personalized regimens and measure improvement in hair health. Powered by AI recommendation engines, your recommended haircare shopping is taken care of across trusted e-commerce platforms, simplifying the purchase based on personal needs and diagnosis. Expert advice from certified dermatologists and trichologists, along with an interactive support community, do their part to make SourceClear streamlines approach to digital wellness as holistic as possible. Behavioral motivation is innovation #1 on the platform, with the HairCoins reward system gamifying compliance to haircare regimes - through functionalities like reminders and rewards - and encouraging user retention. The inclusion of homemade treatments is another focus signaled by the report, combining traditional methods with AI-based personalisation to provide more holistic care. This approach reflects a Routine.

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 Keywords

Artificial Intelligence , Personalized Haircare, Digital Wellness, Image Analysis, Hair and Scalp Health, Machine Learning Diagnostics;Virtual Hairstyle Simulation, User Engagement, Hair Health Tracker, Routine Scheduler, Dermatologist Consultation, Traditional Remedies, Holistic Care, Digital Health Innovation, Cosmetology Technology, User-Centric Design, Beauty and Wellness Industry.

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The Rythu Bandhu Scheme (RBS), introduced by the Government of Telangana, is a pioneering direct investment support programme aimed at strengthening agricultural productivity and ensuring financial security for farmers. This study examines farmers' perceptions and levels of satisfaction with the Rythu Bandhu Scheme in Telangana State. Adopting a descriptive and analytical research design, the study is based on primary data collected from a sample of 300 farmers selected through a stratified random sampling technique from different districts of Telangana. The study analyzes farmers' awareness levels, utilization patterns, perceived benefits, and challenges associated with the scheme. The findings reveal that the Rythu Bandhu Scheme has significantly contributed to timely agricultural investment, reduced farmers' dependence on informal credit sources, and enhanced confidence in agricultural activities. A majority of the respondents expressed satisfaction with the scheme due to direct income support and ease of access. However, certain challenges persist, including the exclusion of tenant farmers, inaccuracies in land records, and occasional delays in fund disbursement. The study concludes that while the Rythu Bandhu Scheme has positively impacted farmers' livelihoods and strengthened agricultural sustainability, policy refinements, improved land record management, and inclusive coverage are essential to enhance its overall effectiveness and long-term success.

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 Keywords

Rythu Bandhu Scheme, Farmers' Perception, Satisfaction Level, Agricultural Support, Telangana, Direct Benefit Transfer, Rural Development

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Background: Competency-based medical education (CBME) has been globally recognized as an effective strategy for aligning clinical training with measurable outcomes and patient safety standards [4-6]. Shalya Tantra, the surgical discipline of Ayurveda, is historically grounded in classical treatises such as the Sushruta Samhita. While these texts provide detailed surgical doctrines, conventional pedagogy has remained predominantly theory-oriented, limiting the development of measurable surgical competencies. The introduction of the Competency-Based Dynamic Curriculum (CBDC) by the National Commission for Indian Systems of Medicine (NCISM) represents a paradigm shift toward outcome-driven education emphasizing procedural proficiency, ethical practice, and clinical reasoning. [12,13] Objective: This study aimed to analyze the alignment of the Shalya Tantra CBDC syllabus with NCISM competency mandates and to evaluate the effectiveness of innovative teaching-learning strategies in improving surgical skills, ethical decision-making, and learner engagement. Methods: A mixed-methods design was adopted, comprising (1) qualitative content analysis of undergraduate and postgraduate Shalya Tantra syllabi, (2) a three-round Delphi survey among experienced educators, and (3) a pilot implementation of simulation-based training assessed through Objective Structured Clinical Examinations (OSCEs). Quantitative data were analyzed using nonparametric statistical methods. Results: Curriculum mapping demonstrated comprehensive alignment between course outcomes and program outcomes across eight modules. Delphi consensus (85%) supported simulation, problem-based learning (PBL), and team-based learning (TBL) as superior to didactic lectures. Pilot OSCE scores showed a statistically significant improvement in procedural competence (median increase from 52% to 78%; p < 0.001). Ethical communication and emergency decision-making competencies also improved markedly. Conclusion: The CBDC framework significantly enhances surgical proficiency and ethical preparedness in Shalya Tantra education. Structured simulations, OSCE-based assessments, and experiential learning ratios effectively bridge classical Ayurvedic principles with contemporary clinical expectations. National-scale implementation and longitudinal outcome research are strongly recommended.

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 Keywords

Shalya Tantra, competency-based education, CBDC, NCISM, surgical simulation, Ayurveda surgery

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Creative Commons Attribution 4.0 and The Open Definition

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Agriculture remains a vital pillar of developing economies, yet a large number of farmers continue to face persistent challenges such as lack of transparent market prices, overdependence on intermediaries, uncertain weather patterns, and insufficient awareness of government welfare schemes. These issues often lead to reduced income, poor decision-making, and limited access to opportunities. To overcome these challenges, Agrivision has been developed as an integrated digital platform. That consolidates essential agricultural services into a single, user-friendly system. Agrivision provides real-time mandi price information, enabling farmers to make informed selling decisions. It also offers a direct farmer-to-buyer marketplace that minimizes the role of middlemen and ensures fair pricing. The platform incorporates AI-based crop advisory systems that assist farmers in crop selection, disease management, and yield optimization, along with accurate weather forecasts to support timely farming activities. Additionally, it serves as a centralized portal for accessing information about government schemes and subsidies. This report presents the system architecture, design methodology, implementation details, and performance evaluation of Agrivision. By integrating diverse datasets and machine learning models with a multilingual mobile interface, the platform is well-suited for rural users. Experimental results indicate improved decision-making, higher profitability, and reduced dependency on intermediaries. Future enhancements may include satellite-based crop monitoring, block chain-enabled trading, and advanced predictive analytics.

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 Keywords

Digital Agriculture, Real-Time Market Prices, AI Crop Advisory, Weather Forecasting, Government Schemes, Predictive Analytics, Farmer Empowerment

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Creative Commons Attribution 4.0 and The Open Definition

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In this paper, an attempt has been made to challenge the popular opposition posited between religion and philosophy, namely the idea that the two are mutually exclusive. The primary line of argumentation in this paper is to establish the diversity within philosophical traditions, which is otherwise overlooked due to a narrow and reductive approach to defining the scope, aims, and objectives of philosophy. By reiterating the element of "practices" (or "spiritual exercises") centered around the transformation of the self, a case for the intersection between philosophy and religion is argued.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

religion; philosophy; spiritual practices; philosophy as a way of life; hikmah

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Creative Commons Attribution 4.0 and The Open Definition

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The financial sector faces major challenges such as inefficiencies in claims processing, lack of transparency, high operational costs, and reliance on intermediaries. This research explores blockchain technology as a solution to create a decentralized, transparent, and secure claims management framework. By integrating smart contracts and cryptographic techniques, the proposed IP-NS-FS-BLKCHN model aims to enhance trust, efficiency, and compliance, benefiting both customers and organizations in the insurance industry.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Blockchain, Smart Contract, Consensus, Distributed Application, Inter Planetary File System, Internet Planetary Network Systems, Oracle

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Creative Commons Attribution 4.0 and The Open Definition

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This project involves the usage of AI for predicting the stock prediction and a way of analysing the AI for predicting stocks and comparing it with traditional ML procedure

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI,ML, StockPrediction

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Creative Commons Attribution 4.0 and The Open Definition

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This article examines the potential of forensic linguistics as a rigorous and innovative method for literary interpretation, situating it within the broader interdisciplinary dialogue between law and literature. While forensic linguistics has traditionally functioned as an analytical tool for legal investigations, addressing authorship attribution, discourse analysis, pragmatic inference, and evidentiary evaluation, its methodological principles offer valuable insights into the structure and meaning of literary texts. The study argues that literary narratives, much like legal testimonies, operate as sites of communicative acts shaped by intention, credibility, deception, and power. By applying forensic linguistic techniques to narrative voice, character interaction, stylistic patterning, and discursive structures, the article demonstrates how linguistic evidence can illuminate concealed motives, latent power hierarchies, and the mechanics of narrative reliability. The methodological framework developed here incorporates authorship analysis, speech act theory, Critical Discourse Analysis, forensic narratology, and corpus-based approaches. The discussion highlights both the strengths of this interdisciplinary synthesis such as enhanced interpretive precision and evidentiary rigor, and its limitations, including risks of overinterpretation and challenges related to literary intentionality. Ultimately, the article positions forensic linguistics as a viable and theoretically rich approach that expands the analytical possibilities for contemporary literary scholarship.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Forensic Linguistics, Literary Interpretation, Discourse Analysis, Forensic Narratology, Law and Literature

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the modern digital era, effective communication remains a significant challenge for individuals with hearing and speech impairments. Traditional sign language communication often requires trained interpreters, which limits accessibility and real-time interaction with the general population. Although several assistive technologies have been developed, many existing solutions suffer from limited accuracy, lack real-time processing, dependency on internet connectivity, and poor user adaptability. This paper proposes an AI Based Sign Language Recognition and Language Translator designed to bridge the communication gap between sign language users and non-signers. The proposed system utilizes computer vision and deep learning techniques to recognize hand gestures captured through a webcam and convert them into meaningful text and speech in real time. MediaPipe Hand Tracking is employed to extract hand landmark features, which are classified using a custom-trained neural network model. To improve reliability, a confidence-based filtering mechanism is implemented to reduce misclassification of gestures. Additionally, the system integrates an offline speech-to-text module and a multilingual translation component, enabling seamless bidirectional communication across different languages. A Streamlit-based interactive user interface provides real-time visualization, gesture training support, and smooth user interaction. The proposed solution offers a lightweight, scalable, and practical approach for assistive communication, accessibility technologies, and inclusive educational environments.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence, Sign Language Recognition, Hand Gesture Recognition, Deep Learning, Computer Vision, Assistive Technology, Accessibility Systems.

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Creative Commons Attribution 4.0 and The Open Definition