Volume 14 | Issue 6 |

 Abstract

ABSTRACT Background Chronic Heart Failure (CHF) is a major cardiovascular disorder associated with frequent hospital readmissions, poor prognosis, increased healthcare expenditure, and reduced quality of life. Recurrent hospitalizations among CHF patients commonly occur due to inadequate self- management practices, poor medication adherence, delayed symptom recognition, and associated comorbidities. Understanding hospital readmission patterns and associated factors is essential for improving patient outcomes and planning effective nursing interventions. Objectives o To assess hospital readmission patterns among patients with chronic heart failure. o To identify factors associated with hospital readmissions among patients with chronic heart failure. o To determine the association between hospital readmission patterns and selected demographic and clinical variables. Methods A quantitative research approach with a descriptive cross-sectional research design was adopted for the study. A total of 150 patients diagnosed with chronic heart failure were selected using a purposive sampling technique based on eligibility criteria and willingness to participate in the study. Data were collected using a demographic and clinical variable sheet along with a structured hospital readmission assessment checklist. Hospital readmission patterns, frequency of hospital admissions, contributing factors, and associated demographic and clinical variables were assessed. Data were analyzed using descriptive and inferential statistics. Results Among 150 participants, 46% had one previous hospital readmission, 32% had two readmissions, and 22% had more than two readmissions within the previous one year. Poor medication adherence (58%), excessive fluid intake (44%), delayed symptom recognition (41%), and uncontrolled comorbidities (38%) were identified as major contributing factors for hospital readmissions. A significant association was found between hospital readmission patterns and educational status, duration of illness, smoking history, and NYHA classification (). Conclusion The study findings revealed that hospital readmissions among patients with chronic heart failure were strongly associated with poor self-management practices and disease-related factors. Early identification of high-risk patients and strengthening nurse-led patient education programmes may help reduce avoidable hospital readmissions and improve patient outcomes.

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Chronic Heart Failure, Hospital Readmission, Readmission Patterns, Cardiac Nursing.

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This study examines the impact of sales promotion tools on consumer buying behaviour, specifically in the grooming and wellness sector. The research is being conducted in the Ranchi district. Businesses use these tools to provide incentives to consumers, which motivate them to purchase the products. Based on existing literature, there have been limited studies conducted specifically within this sector. The emergence of digitalisation, adoption of artificial intelligence, augmented reality and cultural integration, such as the rise in demand for Korean grooming and wellness products, highlights the change in consumers' tastes and preferences. The preferences and purchasing patterns in this industry are constantly changing due to increased customer awareness, lifestyle changes, and growing competition among brands. The research examines the influence of promotional tools like price discounts, premiums, free samples, etc., on consumer buying behaviour in today's time. The sample size of this study is 236 respondents, and the researcher has used a convenience sampling technique. The primary data is collected through a structured questionnaire with a 5-point Likert scale. The secondary data is collected through online sources. The analysis of the collected data was done with the help of SPSS software, and Microsoft Excel was used for graphical representation. The research found that there is a strong relationship between sales promotional tools and consumer buying behaviour. Customers are looking to form a long-term relationship with brands within this sector. In an intense competitive market like grooming and wellness, brands should use loyalty programs to retain and encourage customers to repurchase. Integration of artificial technology and augmented reality enhances consumer experiences. Brands should use balanced monetary offers that do not make consumers question the quality of products or brand equity. Free samples/trials reduce financial and psychological risk borne by consumers.

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Sales Promotion, Consumer Buying Behaviour, Sales Promotional Strategies, Grooming Industry, Wellness Products, Purchase Intentions.

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Visual impairment significantly affects independent mobility, environmental awareness, and access to printed information in daily life. EchoLens-VI: An Intelligent Voice-Guided Perception System for Visually Impaired Individuals presents a wearable assistive solution that combines computer vision, optical character recognition, and speech synthesis to enhance user safety and autonomy. The system employs a Raspberry Pi integrated with a camera module to capture real-time images of the surrounding environment. TensorFlow Lite based object detection identifies obstacles, people, vehicles, doors, and other relevant objects, while the PyTesseract OCR engine extracts textual information from signboards, labels, and documents. Recognized content is processed and converted into natural speech through Google Text-to-Speech, enabling immediate audio feedback. Image preprocessing techniques improve recognition accuracy under varying environmental conditions. The architecture supports continuous monitoring and prioritizes critical alerts for effective navigation assistance. Experimental evaluation demonstrates reliable object detection performance, acceptable text recognition accuracy, and practical response times for real-world usage scenarios. The proposed system offers a cost-effective, portable, and intelligent assistive technology that promotes independence, accessibility, and confidence for visually impaired users.

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Assistive Technology, Smart Glasses, Raspberry Pi, Computer Vision, TensorFlow Lite, Optical Character Recognition (OCR), PyTesseract, Object Detection, Text-to-Speech, Visual Impairment, Wearable Devices, Artificial Intelligence.

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प्रस्तुत शोध पत्र "ई-कॉमर्स के दौर में उपभोक्ता व्यवहार को समझने में आर्टिफिशियल इंटेलिजेंस की भूमिका: डिजिटल मार्केटिंग के नए आयाम" डिजिटल युग में ई-कॉमर्स और आर्टिफिशियल इंटेलिजेंस (AI) के बढ़ते महत्व को रेखांकित करता है। आज के समय में जब उपभोक्ता खरीदारी के लिए तेजी से डिजिटल प्लेटफॉर्मों की ओर रुख कर रहे हैं, व्यवसायों के लिए उपभोक्ता व्यवहार को बारीकी से समझना और उसके अनुसार अपनी मार्केटिंग रणनीतियों को ढालना अत्यंत आवश्यक हो गया है। AI तकनीक, जैसे कि मशीन लर्निंग और प्रेडिक्टिव एनालिटिक्स व्यवसायों को ग्राहकों के डेटा को वास्तविक समय में संसाधित करने, उनकी रुचियों, प्राथमिकताओं और खरीदारी के पैटर्न का सटीक विश्लेषण करने में मदद करती है। इस शोध का मुख्य उद्देश्य यह पता लगाना है कि कैसे AI ई-कॉमर्स प्लेटफार्मों पर उपभोक्ता व्यवहार को समझने और उसे प्रभावित करने के लिए नए आयाम खोल रहा है। इसके साथ ही, शोध इस बात पर भी ध्यान केंद्रित करता है कि AI-संचालित डिजिटल मार्केटिंग रणनीतियां कैसे व्यवसायों के लिए ग्राहक प्रतिधारण रूपांतरण दर और परिचालन दक्षता में सुधार करती हैं। यह शोध यह भी उजागर करता है कि कैसे वैयक्तिकृत सिफारिशें लक्षित विज्ञापन, और इंटरैक्टिव चैटबॉट्स उपभोक्ताओं के अनुभव को समृद्ध करते हैं और उनके खरीदारी के निर्णय को सुव्यवस्थित करते हैं। इस अध्ययन के लिए मिश्रित-पद्धति अनुसंधान का उपयोग किया गया है, जिसमें सर्वेक्षणों और फोकस समूहों के माध्यम से उपभोक्ताओं की प्राथमिकताओं और अनुभवों पर प्राथमिक डेटा एकत्र किया गया है। इसके अलावा, प्रासंगिक अकादमिक साहित्य, केस स्टडीज़, और ई-कॉमर्स प्लेटफ़ॉर्म रिपोर्टों से माध्यमिक डेटा का भी विश्लेषण किया गया है। शोध के निष्कर्ष बताते हैं कि AI तकनीकों का एकीकरण न केवल विपणन प्रयासों को अधिक प्रभावी बनाता है, बल्कि यह उपभोक्ताओं के लिए अधिक सुविधाजनक और संतोषजनक खरीदारी अनुभव भी प्रदान करता है। हालाँकि, डेटा गोपनीयता और नैतिक उपयोग जैसी चुनौतियां भी मौजूद हैं, जिन पर व्यवसायों को ध्यान देने की आवश्यकता है। यह शोध उन ई-कॉमर्स व्यवसायों के लिए महत्वपूर्ण अंतर्दृष्टि प्रदान करता है जो प्रतिस्पर्धी बाजार में आगे रहने और स्थायी ग्राहक संबंध बनाने के लिए AI की क्षमता का लाभ उठाना चाहते हैं।

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आर्टिफिशियल इंटेलिजेंस (AI), ई-कॉमर्स, उपभोक्ता व्यवहार, डिजिटल मार्केटिंग, मशीन लर्निंग, प्रेडिक्टिव एनालिटिक्स, डेटा गोपनीयता।

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Diabetic Retinopathy (DR) is one of the most common microvascular complications of Diabetes Mellitus and is a leading cause of preventable blindness worldwide. The chronic hyperglycemic state causes progressive retinal vascular damage, resulting in retinal ischemia, hemorrhages, exudates, neovascularization, and visual impairment. Although Diabetic Retinopathy is not directly described in the classical Ayurvedic texts, its clinical manifestations can be correlated with Madhumeha, Prameha Upadrava, Timira, Kacha, and Drishtigata Rogas. Ayurveda emphasizes the preservation of vision through the maintenance of equilibrium among Dosha, Dhatu, and Mala. Management includes Nidana Parivarjana, Shodhana, Shamana Chikitsa, Rasayana Prayoga, dietary regulation, and ocular therapeutic procedures. This review aims to explore the Ayurvedic understanding and management of Diabetic Retinopathy through classical references and contemporary perspectives.

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Diabetic Retinopathy, Madhumeha, Timira, Netra Roga, Rasayana, Ayurveda

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Abstract Women entrepreneurship has emerged as a key driver of economic growth, employment generation, and social transformation in rural India. Despite their growing contribution to household income and rural development, women entrepreneurs continue to face numerous socio-economic, cultural, financial, and technological barriers. This study examines the current status of rural women entrepreneurship in India, identifies the major challenges faced by women entrepreneurs, and evaluates the role of government support initiatives in promoting entrepreneurial development. The study adopts an exploratory and descriptive research design based on qualitative secondary data collected from research articles, government reports, policy documents, and published literature. The findings reveal that limited access to finance, inadequate education and skills, gender discrimination, poor infrastructure, digital illiteracy, and restricted market access remain significant obstacles to entrepreneurial growth among rural women. At the same time, government initiatives such as the Pradhan Mantri MUDRA Yojana, Stand-Up India Scheme, National Rural Livelihoods Mission (NRLM), Women Entrepreneurship Platform (WEP), and Self-Help Group (SHG) programmes have played a vital role in enhancing financial inclusion, skill development, and business opportunities for women. The study concludes that strengthening awareness, improving access to credit and technology, simplifying administrative procedures, and expanding mentorship and training programmes are essential for fostering a supportive entrepreneurial ecosystem. Promoting rural women entrepreneurship is crucial for achieving inclusive economic growth, gender equality, and sustainable rural development in India.

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Women Entrepreneurship, Rural Development, Self-Help Groups, Government Schemes, Financial Inclusion, Women Empowerment, Rural India.

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The exponential surge in digital data across distributed systems has intensified the demand for compression mechanisms that are both lossless and computationally intelligent. Traditional algorithms such as Huffman coding, Lempel-Ziv variants, and arithmetic coding have served the field well for decades, yet exhibit fundamental limitations when confronted with contextually rich or heterogeneous data streams. This paper presents an intelligent file compression and decompression system that harnesses DeepSeek-R1:1.5B -- a lightweight yet powerful large language model -- deployed locally via Ollama to drive context-aware probability estimation and entropy encoding. The proposed system integrates LLM-generated probability distributions into an arithmetic coding backend, enabling significantly improved compression ratios for text-dominant file types compared to classical baselines. Experimental evaluation across diverse datasets demonstrates measurable gains in compression efficiency while maintaining perfect lossless reconstruction. The system addresses practical deployment concerns through local inference via Ollama, mitigating privacy and latency overheads associated with cloud-based LLMs. This work bridges the theoretical potential of neural language models with tangible, deployable compression infrastructure and charts a course for hybrid AI-classical compression frameworks.

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Lossless Compression, Large Language Models, DeepSeek-R1, Ollama, Entropy Coding, Arithmetic Coding, Intelligent Compression, Sequence Modeling, Probability Estimation, AI-driven Data Management, etc.

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Objectives: To evaluate the Current trends of molar mesialization Materials and Methods: This Review article includes articles (2019-2025) . Studies included orthodontic patients in the permanent dentition with Angles Class II division1 or 2, Class II subdivision, class I, mild or no skeletal discrepancies, 2-6 mm crowding, treated with CA. Results: Both Aligner and the Temporary Anchorage Devices (TADs) are effective in the molar mesialization. TADs (or a Hybrid TAD-Aligner system) are vastly superior and essential for predictable molar mesialization. Conclusions: The integration of Temporary Anchorage Devices (TADs) has effectively addressed the historical challenge of anchorage loss, while the advent of shape memory aligners and specialized molar protraction devices has refined the precision of tooth movement.

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molar mesialization, molar protraction, space closure, mandibular molar movement. TADs, mini-implants, transpalatal arch (TPA), skeletal anchorage

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The cloud-based systems and digital communication is increasing rapidly day by day and to ensure confidentiality, authenticity of information and integrity strong cryptographic mechanisms are needed. At present time in cyber security infrastructures, encryption key management and secure key exchange protocols plays a vital role. Various encryption key management techniques, public-key encryption methods, password-based key exchange protocols, chaos-based encryption systems, proxy re-encryption mechanisms, and homomorphic encryption approaches are inspected in this review paper. Twelve published papers are analysed to check the developments in encryption technologies and key distribution mechanisms. This review paper mainly focused on the transformation of secure key methodologies and their advantages, disadvantages, practical applications. Besides that, after analysis the different techniques revels the rising trends like, how to secure cloud-based communication? How to resist from cryptographic attacks? How to stronger the privacy preservation? In this review paper findings give right direction about traditional encryption system and advanced approaches indicate for future research. Different research gaps, future gaps also included in this study which helps for next generation applications cyber security.

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Cryptography, Encryption Keys, Key Exchange Protocols, Public-Key Encryption, Homomorphic Encryption

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Rapid urbanization and population growth have led to an increasing demand for high-rise buildings in urban areas where land availability is limited. As the height of buildings increases, their vulnerability to lateral loads such as earthquakes and wind also increases. High-rise reinforced concrete (RC) buildings are particularly susceptible to excessive lateral displacement, story drift, and torsional effects during seismic events. Therefore, it becomes essential to incorporate efficient lateral load-resisting systems to ensure the safety, stability, and serviceability of such structures. Among the various structural systems available, reinforced concrete shear walls and steel bracing systems have proven to be effective in enhancing the seismic performance of multi-storey buildings. Shear walls provide significant lateral stiffness and strength, while steel bracing systems improve the load-resisting capacity and energy dissipation of the structural frame. The combined use of these systems can further enhance the overall performance of high-rise buildings subjected to seismic forces. The present study focuses on the analysis and comparison of the structural behaviour of a high-rise RC building of G+40 storeys using different lateral load resisting systems. The main objective of this research is to evaluate the effectiveness of RC shear walls and steel bracing systems in controlling lateral displacement, story drift, and overall structural response under seismic loading conditions. A three-dimensional model of the building is developed and analysed using ETABS software. Different structural configurations are considered, including a bare frame model, a model with RC shear walls, a model with various steel bracing arrangements and a model with both the systems RC shear wall and steel bracing. These models are analysed to study their dynamic behaviour and seismic performance. The seismic analysis of the building is carried out using appropriate methods in accordance with relevant design codes. Important structural response parameters such as base shear, story displacement, story drift, fundamental time period, and story stiffness are evaluated and compared for different structural systems. The analysis aims to determine how the introduction of shear walls and bracing systems influences the lateral stiffness and overall stability of the building. The results obtained from the analysis indicate that the inclusion of RC shear walls and steel bracing significantly increases the stiffness of the building and reduces lateral displacement and story drift enhancing lateral load resistance and reducing the fundamental time period of the structure. The study also highlights that different bracing configurations have varying levels of effectiveness in controlling seismic response. In many cases, the combination of shear walls and steel bracing systems provides better performance compared to using either system alone. Overall, this study demonstrates that the proper selection and placement of shear walls and steel bracing systems play a crucial role in improving the seismic performance of high-rise buildings. The findings of this research provide useful insights for structural engineers in designing safer and more efficient high-rise RC buildings in earthquake-prone regions. The results can contribute to optimizing lateral load resisting systems for tall buildings and improving their resilience against seismic forces.

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Shear wall, Steel bracing, Base Shear, Story Displacements, Story Drift, Fundamental time period, Story stiffness.

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