Volume 13 | Issue 12

 Abstract

Background: Coronary Artery Disease (CAD) is one of the leading causes of morbidity and mortality worldwide. Patients with CAD often experience limitations in physical activity, emotional distress, and reduced quality of life. Adequate knowledge regarding disease management and lifestyle modification plays a crucial role in improving health-related quality of life (HRQOL). Objectives: 1. To assess the level of knowledge regarding coronary artery disease among patients. 2. To assess the health-related quality of life of patients with coronary artery disease. 3. To determine the relationship between knowledge and health-related quality of life. 4. To develop a self-instructional module based on identified knowledge gaps. Methods: A quantitative descriptive research design was adopted. The study was conducted at a selected private hospital in Indore, Madhya Pradesh. A sample of 100 patients diagnosed with coronary artery disease was selected using non-probability purposive sampling. Data were collected using a structured knowledge questionnaire and a standardized health-related quality of life scale. Results: The findings revealed that a majority of patients had moderate knowledge regarding CAD and reported average to poor quality of life in physical and emotional domains. A significant relationship was found between knowledge level and health-related quality of life. Conclusion: The study concluded that improved knowledge is associated with better health-related quality of life among patients with CAD. Development and use of a self-instructional module is recommended to enhance patient education and long-term disease management.

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Coronary artery disease, knowledge, health-related quality of life, self-instructional module, patient education

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India's role as a major producer and global supplier of generic medicines makes the assurance of drug quality a central public health and regulatory priority. The Indian Pharmacopoeia (IP), published by the Indian Pharmacopoeia Commission (IPC), is the official compendium of standards for the identity, strength, purity and performance of drugs and related substances marketed in the country and serves as a legally enforceable benchmark under the Drugs and Cosmetics Act and Rules. Through monographs, general chapters and Indian Pharmacopoeia Reference Substances (IPRS), the IP provides validated analytical methods and acceptance criteria that guide manufacturers, quality control laboratories and regulators in ensuring that medicines are of standard quality and suitable for patient use. Over successive editions, the IP has expanded and modernized to include chemical drugs, traditional medicines, biologicals, vaccines and complex formulations, while aligning with World Health Organization (WHO) good pharmacopoeial practices and participating in international harmonization initiatives such as the Pharmacopoeial Discussion Group. This review outlines the historical evolution, legal status, scientific content and implementation of the IP and critically examines its contribution to detecting substandard and falsified medicines, supporting Good Manufacturing Practices (GMP) and enabling generic interchangeability in India, as well as its growing relevance for international trade and regulatory convergence.

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Indian Pharmacopoeia, Indian Pharmacopoeia Commission, drug quality standards, medicines regulation, Good Manufacturing Practices, reference standards (IPRS), pharmacopoeial harmonization, WHO good pharmacopoeial practices, generic medicines, public health.

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A study of the symptoms, diagnosis and treatment of suicidal tendencies among adolescents in tribal areas& 2024

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A study of the symptoms, diagnosis and treatment of suicidal tendencies among adolescents in tribal areas& 2024

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Camouflage Object Detection is a challenging problem in computer vision due to the high visual similarity between target objects and their surrounding environments. Conventional object detection methods often exhibit degraded performance in camouflage scenarios because of weak object boundaries, low contrast, and complex background textures. This paper presents a segmentation-based camouflaged object detection framework using the SiNet-V2 deep neural network architecture. The proposed approach performs pixel-level segmentation to accurately localize camouflaged regions in input images. The model was trained and evaluated on publicly available benchmark datasets.

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Camouflaged Object Detection, SiNet-V2, Deep Learning, Image Segmentation, Computer Vision.

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Assess the knowledge of diabetic foot among diabetic patients attending tertiary care hospital of Vidarbha region of Maharashtra

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Vision-based single-person human activity recognition (HAR) has advanced rapidly through deep learning. This review surveys 14 recent peer-reviewed studies (2017-2025) focusing on monocular video HAR. We searched IEEE Xplore, SpringerLink, MDPI, and other databases with keywords like "vision-based HAR," "single-person," "CNN," "LSTM," and "Transformer," screening for methods, datasets, and performance. We compare each study's model, dataset, and accuracy, and highlight common limitations. Major findings include the effectiveness of attention and fusion architectures for spatiotemporal feature learning[1][2]. Performance is now very high on benchmark datasets (e.g. >96% on UCF/KTH[3][4]), but generalization and real-time constraints remain challenging. We identify research gaps - notably, reliance on limited datasets and heavy computation - and suggest directions such as lightweight models and richer data. Our review underscores progress and open issues in vision-based single-person HAR.

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Human Activity Recognition (HAR), single-person, video, convolutional neural network, LSTM, attention, transformer.

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UNESCO has defined "Women's empowerment is the process by which women become aware of gender-based unequal power relationships and acquire a greater voice in which to speak out against the inequality found in the home, workplace, and community". The definition itself indicates that the women empowerment is process and it has change according to the situation. That process also include social, economic, political and cultural progress among women. The present research paper intend to find out those progress with a sociological point of view. Historical elements witnessed there was no space for women in any aspect. Treated as subordinate of men and denied in decision making. However, the present situation somehow better and progressive. Hence, the present research paper tries to find out some of the important aspects of women empowerment.

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Keywords: Empowerment, Inequality, Change, Subordinate, Process

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Abstract-- Cardiovascular diseases (CVDs) continue to be the primary cause of death globally, highlighting the critical need for efficient prevention and early detection. Traditional diagnostic approaches, though clinically valuable, often involve high costs, delayed diagnosis, and limited personalization. Leveraging extensive hospital records, this work proposes a robust machine learning-driven framework for automated feature selection, risk prediction, and clinical decision support in CVD management. A comprehensive prepossessing pipeline, including normalization, missing value handling, and feature selection, ensured reliable model inputs. Multiple machine learning algorithms classified patients into cardiovascular risk categories based on clinical and lifestyle parameters such as cholesterol, blood pressure, and fasting blood sugar, and ECG. To enhance predictive accuracy, a Super Learner ensemble algorithm was employed to combine multiple base models, achieving an F1-score of 92.3% with a 90.94% average accuracy, outperforming current methods. Metrics like accuracy and precision were employed in performance validation. recall, F1-score, and ROC-AUC, demonstrating robustness across datasets. The integrated recommendation engine provides personalized lifestyle and medical guidance, including dietary changes, exercise plans, and consultation needs, through a user-friendly graphical interface for instant predictions and recommendations. The novelty of this work lies in combining the Super Learner ensemble approach with a personalized recommendation system, thereby improving predictive accuracy and supporting preventive cardiovascular care to alleviate the overall healthcare burden.

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Keywords-- Cardiovascular Disease (CVD), Machine Learning (ML), Super Learner, Risk Prediction, Personalized Healthcare, Preventive Medicine, Recommendation System, GUI.

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Diabetic retinopathy (DR) is a microvascular complication caused by long-term diabetes and is a leading cause of vision loss. Due to lifestyle changes, retinal abnormalities may appear within a decade of diabetes onset or even earlier. Modern medicine offers mainly conservative, symptomatic treatments, and current DR therapies have notable limitations. In Ayurveda, DR correlates with Madhumehajanya Timir, and traditional Ayurvedic texts describe several formulations for diabetes and its ocular complications. This case study evaluates the actual effectiveness of these Ayurvedic treatments in managing DR. For many years, Ayurvedic pharmaceutical companies have prepared various kwath formulations, which Acharyas have traditionally used to treat numerous diseases. Diabetic retinopathy is increasingly common, and Ayurveda offers an effective line of treatment for managing its symptoms. Administering a kwath medicated with drugs possessing Pitta-Rakta Shamaka properties can significantly support the management of diabetic retinopathy.

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Diabetic retinopathy, Madhumehajanya Timir, Kwath, Pitta-Rakta Shamaka.

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Representational spaces that surfaced in Kerala by the 1930s significantly shaped public consciousness and bolstered communist ideology among the people. Work environments, tea shops, and reading rooms formed novel public spheres during the second quarter of the 20th century. These spaces fostered inter-caste interaction and expedited the process of socialization. The presence of subaltern people rendered these spaces crucial for communists leaders, predominantly upper-caste Hindus, to engage with. Transcending caste barriers, upper caste-Hindus dared to get mingled with lower strata of society. Dynamic political interactions at these spaces, nurturing numerous friendships, infused class consciousness among subaltern groups, thereby bringing them closer to communism.

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public sphere, communists, vayanasalas, work spaces, subalterns, class consciousness

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Obesity is a major public health issue shaped by many factors beyond simple calorie intake, with nutrient composition and overall dietary quality playing crucial roles in metabolic health and the regulation of weight gain. Obesity is better understood as a metabolic and nutritional disorder rather than simply a calorie issue. Dietary quality and nutrient composition strongly shape metabolic health, with processed, calorie-dense foods promoting dysfunction and whole, nutrient-rich foods supporting healthy weight management. Effective obesity management must go beyond calorie counting and focus on improving dietary quality. Prioritizing whole, nutrient-dense foods in public health strategies can support more sustainable and effective obesity prevention and management. A literature review was conducted to analyze studies on food quality, nutrient composition, and their relationship with metabolism and obesity, with the aim of critically evaluating how dietary quality and nutrient composition influence obesity and overall metabolic health.

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Keyword - Obesity, Caloric intake, Diet quality, processed foods, Physical activity

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This has raised a concern of West Bengal in regards to the quality of primary education in the region despite the tremendous growth of enrollment, development of infrastructure, and policy interventions. Recent evaluations have shown that a high percentage of students in lower grades are not well equipped with basics in literacy and numeracy activities which is a sign of systemic failure in the processes of teaching-learning. In this paper, the significant issues that have contributed towards the decline are critically looked at which include teacher shortages, poor training, infrastructural disconnects, socio-economic hindrances, and administrative inefficiencies. Using the current reports, observations in the classroom, and secondary information, the research illuminates the collective effect of these factors as they negatively affect learning outcomes and increase educational inequalities especially in rural and disadvantaged communities. The paper also gives a discussion of evidence-based solutions that can be used to restore the primary education system. These involve fortification of basic learning courses, timely hiring of teachers, professional development, school infrastructure and encouragement of parental and community involvement. They are focussed on the incorporation of technology, open governance, and inclusive practices in accordance with NEP 2020. It claims that learners should be subjected to holistic and multi- level reforms to gain meaningful and long-lasting reforms in the standard of learning. Finally, the paper recommends a team-based solution that entails the government agencies, the teaching fraternity, the communities, and the civil society to regain the trust and revive the credibility of primary education in West Bengal.

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West Bengal, learning outcomes, foundational literacy, Teacher shortages, NEP 2020, school infrastructure, learning governance, social-economic barriers to education, and quality education.

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? ??????? : ???+???? ?? ?????????? '???????'??????? ???????? ?????? ???. ???????? ???????? ?????? ??? ??????? ??????? ??? ???????? '???????' ?? ?????????? ?????? ????. ?? ???? ????????? ???. ???????? ??????? ???, ???, ????, ???, ?????? ??????????? ?? ???? ?????????? ???? ????? ???? ??? ????. ????? ????,??????,?????,???????,????,?????????, ??????? ??? ????? ???????????? ? ?????? ???, ?????????? ????? ???. ????? ???????, ??????? ?????????? ???????? ???????????? ???????? ??????? ???? ???? ??????? ???? ???. ??? ???? ??? ???? ???????? ?? ????? ?? ???? ????????????????, ????????? ????? ????????????? ??? ? ??????? ?????? ?????. ????? ?????? ???? ?????? ???????? ?? ????? ??????? ???? ????. ???? ????? ?????? ?????? ???? ???? ??????????????? ????????? ??? ???? ???? ?? ???? ?????? ?????????? ???????? ???? ? ????? ??? ???????????? ????? ??? ?????? ?? ?????? ??????? ???????? ???????? ???? ??????? ????. ??????? ???? ?? ??????? ?????? ????? ????? ???? ???????? ????????? ????? ???? ????? ? ???????? ???????? ???????. ????????? ?????? ??? ? ??????? ???? ?????? ????. ????? ??? ?????? ????????? ????????????? ?????????????? ????????????? ?????? ???? ???? ?? ?? ?????? ?????????? ???? ??? ????????? ????????????? ?????????? ?? ?????? ??????? ???? ???.

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? ??????? : ???????, ???????????, ?????????, ??????????????, ?????????, ????? ???????, ??????????, ?????, ???????????????, ????, ???????, ??????, ??????, ??????????, ?????????, ???????? ???????.

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Over the past decade, the rapid spread of social media has fundamentally changed tourism education. It has reshaped not only how students learn but also how they communicate and build their professional identities. This paper presents a comprehensive review of recent theoretical perspectives and empirical evidence on the role of social media in the lives and learning of tourism students. Drawing on social constructivist theory, digital identity frameworks, and media learning approaches, it synthesizes literature published between 2022 and 2025 to explore how digital platforms affect students' academic engagement, emotional well-being, and career preparation. The review brings together insights from more than twenty recent scholarly studies and organizes the main findings into three closely connected areas of impact: o Cognitive and academic engagement through interactive digital environments; o Socio-emotional effects arising from online interaction and the curation of digital identities; o Professional development through digital self-presentation and networked learning opportunities. The analysis is informed by foundational theories, including Bandura's Social Cognitive Theory, Vygotsky's Social Constructivism, and Goffman's Presentation of Self in Everyday Life, which help explain how students behave and develop within online tourism education spaces. The findings show that social media can significantly boost motivation, support collaborative learning, and provide valuable industry exposure. At the same time, it introduces important challenges, including digital fatigue, unhealthy self-comparison, and superficial forms of engagement. The paper concludes by proposing a conceptual model that captures the cyclical relationship between social media use, cognitive engagement, emotional mediation, and professional identity formation. It highlights the critical moderating roles played by digital literacy and institutional support. This synthesis adds to the growing conversation about digital transformation in tourism education. It underlines the importance of thoughtfully integrating social media into teaching practices, alongside training in emotional intelligence and ethical online behavior. The review offers practical insights for educators, researchers, and policymakers working to develop tourism curricula that are both resilient and well-adapted to the digital age.

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Social Media, Tourism Education, Tourism Students, Cognitive Engagement, Emotional Regulation, Professional Identity Construction, Social Constructivism, Social Cognitive Theory, Goffman's Presentation of Self, Digital Literacy, Institutional Mediation, Virtual Learning Environments, Experiential Learning, Emotional Well-Being, Career Readiness, Higher Education, Digital Pedagogy, Media and Communication Studies, Online Learning Behavior, Sustainable Tourism Education.

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More than 795 thousand people in the US experience a stroke, per year. Out of this, around 610 thousand are RST or new strokes. Strokes are a leading factor of mortality for Americans with 140 thousand people dying annually. [3] Stroke incidence has increased drastically in the young population, with over 20% of those affected being under the age of 45. Hemiparesis, which occurs following a stroke, is a significant motor impairment that affects up to 65 percent of stroke sufferers because of a high rate of muscle frailty. Muscle pain is a significant role in delayed recovery following a stroke in victims, and it is also a common symptom reported in patients. This can result in a patient's range of physical activities being limited or even immobilized. Between 30% and 60% of stroke victims report having less physical range in the damaged body portion when performing daily activities. The feasibility of a 4 by 4 excible sensor matrix which uses paper as a base is explored and a pressure sensor based on paper is developed. This helps reduce the cost and fabrication time. Additionally, the matrix's static and dynamic properties are discussed. Despite considerable variance in response between sensors due to the structural material qualities, the sensor may be efficiently used to continuously evaluate stroke rehabilitation patients' recovery. The matrix's performance is evaluated using a neural network that has been designed to recognize the location of a load using the values of individual sensors.

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Artificial Intelligence, Stroke, Recurrent Neural Network, Sensors

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The etiology, pathophysiology, and medication management of type 1 and type 2 diabetes mellitus are the main topics of this review. Insulin resistance and decreased insulin secretion brought on by genetic and lifestyle factors cause type 2 diabetes, whereas type 1 diabetes is an autoimmune disease that kills pancreatic beta cells, resulting in insulin insufficiency. Insulin therapy is the mainstay of type 1 diabetes management, with the help of newer alternatives like islet transplantation, stem cell therapy, and gene-based therapies. Oral and injectable drugs like metformin, sulfonylureas, thiazolidinediones, alfa glucosidase inhibitors, DPP 4 inhibitors, SGLT 2 inhibitors and GLP 1 receptor agonists are used to treat type 2 diabetes. Effective glycemic control and the avoidance of complications from diabetes depend on combination therapy and lifestyle changes.

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Diabetes mellitus, Medication management, Pathophysiology, Etiology, Classification, Innovative therapies.

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The advancement of diffusion-based generative models has significantly transformed controllable image synthesis, enabling realistic rendering across diverse domains such as editing, and semantic manipulation. Despite these developments, virtual try-on--the task of synthesizing high-fidelity images of a target person wearing a new garment--remains technically challenging due to complex interactions between human pose, garment geometry, occlusions, and appearance fidelity. Existing GAN-based and deformation-based systems often struggle with texture misalignment, identity drift, and loss of garment details in high-resolution scenarios.This paper introduces SDM-VTON, a diffusion-based virtual try-on framework built upon the SDXL latent diffusion model and enhanced with Garment-Guided Cross-Attention (GGCA), a novel conditioning mechanism that integrates spatially aligned garment features into the U-Net denoising process. SDM-VTON includes (1) a multi-scale GarmentNet encoder-decoder that extracts hierarchical clothing features; (2) an image-conditioned adapter that injects CLIP-based semantic embeddings into transformer layers; and (3) a Try-On U-Net augmented to accept pose, segmentation, and mask priors for geometry-aware inpainting. The system is trained end-to-end in latent space, enabling identity preservation, accurate garment transfer, and superior texture reconstruction compared to prior state-of-the-art diffusion models such as LaDI-VTON and FITMI. Extensive experiments on the VITON-HD and Dress-Code datasets demonstrate that IDM-VTON achieves new benchmarks across SSIM, LPIPS, FID, KID, and CLIP Score. This work establishes SDM-VTON as a robust, workspace-native virtual try-on system suitable for next-generation e-commerce, digital dressing rooms, and personalized fashion visualization.

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[Virtual try-on, diffusion models, SDXL, cross-attention, CLIP, humanpose estimation, latent diffusion, semantic alignment]

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Kerala's acclaimed "Model of Development," characterised by high literacy, robust healthcare, and gender equity, has long been viewed as a benchmark for social progress in India. Yet persistent challenges--rising mental health concerns, lifestyle diseases, unemployment, ecological vulnerability, and declining community vitality--highlight the limitations of conventional metrics like GDP and HDI in capturing true well-being. This paper argues for integrating Bhutan's Gross National Happiness (GNH) framework into Kerala's development planning, given the cultural, social, and environmental parallels between the two regions. GNH's multidimensional approach, encompassing psychological well-being, time use, cultural resilience, and environmental stewardship, offers a more holistic measure of progress. Through a critical review of Kerala's current socio-economic indicators, the study identifies policy gaps and proposes a locally adapted GNH-based framework, embedded in participatory governance and linked to resource allocation. By complementing economic indicators with happiness metrics, Kerala can move towards a development model that ensures not just material prosperity but sustainable, inclusive, and meaningful well-being for all citizens.

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Kerala Model, Gross National Happiness, development planning, well-being indicators, policy integration

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Th?la occupies a foundational position in Bharatanatyam, functioning simultaneously as a structural framework and an aesthetic life-force. While rhythm is often understood as a temporal guide that regulates movement, its deeper role lies in shaping bodily discipline, expressive continuity, and aesthetic fulfilment. This paper examines th?la as an embodied rhythmic principle that governs the organisation of movement and facilitates the realisation of bh?va and rasa in Bharatanatyam. Through a critical engagement with classical texts, dance theory, and performance practice, the study argues that th?la is not merely an external metric but an internalised rhythmic consciousness that integrates body, time, and emotion. The paper highlights how rhythmic internalisation transforms technical execution into an aesthetically meaningful experience, thereby establishing th?la as a unifying force between structure and aesthetics in Bharatanatyam.

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Th?la, Bharatanatyam, Rhythm, Structure, Aesthetics, Bh?va, Rasa, Laya, Performance Practice

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The Information Technology (IT) sector plays a significant role in the economic growth of India by contributing to employment generation, foreign exchange earnings, and technological advancement. Among the leading IT companies in India, Tata Consultancy Services Limited (TCS) has emerged as a dominant player with consistent financial performance, strong profitability, and global presence. The present study aims to analyse the financial performance of Tata Consultancy Services Limited using ratio analysis and trend analysis. The study is based on secondary data collected from the annual reports of TCS for a period of five years from 2019-20 to 2023-24. Key liquidity, profitability, solvency, and efficiency ratios have been applied to assess the company's financial health. The findings reveal that TCS has maintained stable profitability, efficient asset utilization, and a strong capital structure during the study period. The study provides useful insights for investors, academicians, and financial analysts in evaluating the financial soundness of TCS.

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Financial Performance, Ratio Analysis, Trend Analysis, IT Sector, Tata Consultancy Services

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