Volume 14 | Issue 7 |

 Abstract

BACKGROUND: Shoulder dysfunction is frequently reported in individuals with Type 2 diabetes mellitus and restricted mobility being common clinical manifestations. These musculoskeletal problems may arise from altered collagen metabolism, glycation of periarticular tissues, and chronic hyperglycemia, ultimately affecting functional activities. AIM: To determine the relationship between shoulder mobility impairment among patients with Type 2 diabetes mellitus. METHODS: A Observational study was conducted in Sri Ramakrishna Multi speciality Hospital for 6 months including 100 participants diagnosed with age ranges between from 30 to 50 based on inclusion and exclusion criteria to find the impact of shoulder mobility impairment with a self- administered questionarrie on demographic data and clinical variables were collected and analysed. RESULTS: The findings demonstrated a significant association between reduced shoulder ROM and higher pain and disability scores. Patients with longer duration of diabetes and elevated HbA1c values tended to show greater mobility restriction and increased pain levels. The correlation coefficients indicated that mobility impairment was moderately to strongly related to functional limitation. CONCLUSION: Shoulder mobility restriction was closely linked with functional disability in individuals with Type 2 diabetes mellitus. Early screening and targeted physiotherapy interventions may help reduce shoulder complications and improve quality of life in this population.

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 Keywords

Diabetes ,HbA1c , shoulder external rotation and abduction range of motion

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Creative Commons Attribution 4.0 and The Open Definition

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This narrative review examines the intersection of large language models (LLMs) and academic writing in higher education, with a specific focus on Claude AI a model whose institutional adoption has expanded rapidly but whose representation in the peer-reviewed literature remains comparatively limited. Drawing on peer-reviewed sources published between 2020 and 2025 across databases including Scopus, Web of Science, ERIC, ScienceDirect, and Frontiers, this review synthesizes evidence on the benefits, risks, and cognitive implications of generative AI-assisted academic writing. The literature confirms that generative AI tools, led overwhelmingly by research on ChatGPT, improve measurable dimensions of student writing including cohesion, fluency, and revision behavior, while simultaneously introducing well-documented risks: over-reliance, academic integrity violations, and detector bias against non-native English writers. Evidence on cognitive and critical-thinking outcomes remains genuinely contested, with reviews reporting both enhancement and erosion of higher-order thinking depending on task design and instructional scaffolding. Against this backdrop, the review identifies a central and consequential gap: despite Claude's formal deployment across universities including Northeastern University, the London School of Economics and Political Science, and Champlain College, and despite substantial documented student and educator usage, only a small number of peer-reviewed studies examine Claude specifically within academic writing contexts. This asymmetry between institutional deployment and independent scholarly scrutiny means that current pedagogical guidance on "AI-assisted writing" rests on evidence base derived almost entirely from a different model family. The review concludes by outlining research gaps and future directions specific to Claude AI, particularly within English for Academic Purposes and English for Specific Purposes contexts, and offers implications for educators, curriculum designers, and institutional policymakers navigating this evolving and unevenly evidenced landscape.

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 Keywords

Large Language Models, Claude AI, Academic Writing, Higher Education, Generative Artificial Intelligence, Academic Integrity, English for Academic Purposes

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 Abstract

Background: An estimated 15 million babies are born too early every year. Approximately 1 million children die each year due to complications of preterm birth. Premature infants, especially Very Low Birth Weight (VLBW) infants (<1500 g), are a group at high risk of infectious diseases in Neonatal Intensive Care Units (NICUs). Methods and materials: A true experimental research was done among the 100 preterm neonates (32-36 weeks) in NICU (Neonatal Intensive Care Unit) & RNB (Referral Newborn), RMMCH at Chidambaram from November 2021 to October 2022. Colostrum swabbing was done for the experimental group and routine nutritional care was given to the control group. Pre test and post test assessments of feeding problems with its changes using LATCH scale were done for both the groups in related to the intervention. Results: There was a significant difference found between experimental and control groups in feeding problems (p<0.001). Conclusion: Colostrum may be an ideal "first immune stimulator" for premature infants; and indeed premature human colostrum has higher concentration of proteins, cytokines, and secretory immune globulins compared with term colostrum by which the immunologic factor in Oral Colostrum administration may stimulate and protect the immature neonatal immune system.

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 Keywords

Breast milk, Colostrum, Extremely Low Birth Weight, Human milk, Preterm neonate, Neonatal Intensive Care Unit,

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Creative Commons Attribution 4.0 and The Open Definition

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The Kashmir conflict has remained one of India's most persistent national security challenges since 1947, but the mass displacement of Kashmiri Pandits in 1990 marked a critical turning point in insurgency dynamics. This episode underscored the limitations of India's counterinsurgency (COIN) framework, raising urgent questions about minority protection, governance, and military strategy. Over the subsequent three decades, India's COIN doctrine evolved through successive phases shaped by the Kargil War (1999), recurrent cycles of militancy, civil unrest (2008-2016), and the intensification of cross-border terrorism. The abrogation of Article 370 in 2019 constituted a constitutional and doctrinal watershed, fundamentally reconfiguring the security architecture of Jammu and Kashmir. This study critically traces the trajectory of India's COIN doctrine across these phases, situating it within the broader geopolitical contest involving India, Pakistan, Kashmiri separatists, and foreign fighters. The roots of the conflict lie in the 1947 partition, when competing claims over Jammu and Kashmir emerged: Pakistan asserted its case on religious and cultural grounds, while India's claim rested on the accession decision of the princely ruler under conditions of external aggression. By examining these historical foundations alongside doctrinal shifts, the research highlights how India's counterinsurgency strategies have oscillated between militarization, developmental interventions, and constitutional integration, reflecting the complex interplay of security imperatives and democratic governance.

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Kashmiri Pandit, Exodus, Article-370, insurgency, Counterinsurgency, Doctrine, Human Rights,

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The present study examines how institutional care contributes to the well-being of elderly residents living in Prakhanti Dham Old Age Home, Barpathar, Assam. The study explores the living conditions, health status, emotional well-being, and social relationships of senior citizens. The research is based on both primary and secondary data, utilizing interview schedules, observation, and case studies among twenty elderly residents selected through purposive sampling. The study is guided by Michel Foucault's perspective on discipline, power, surveillance, and institutional regulation. The findings reveal that while the institution provides shelter, healthcare, and safety, many residents continue to experience emotional distress due to separation from their families. The study concludes that old age homes play an important role in promoting dignity and inclusion, although institutional care should be supported by family involvement and emotional support.

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Ageing, Old Age Home, Senior Citizens, Quality of Life, Social Inclusion, Prakhanti Dham

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Creative Commons Attribution 4.0 and The Open Definition

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The Advancement in computer vision and artificial intelligence technologies have enabled the development of intelligent systems capable of automating educational processes and enhancing classroom management. The conventional method of marking attendance is known to be time-consuming and vulnerable to proxy attendance; moreover, it only tracks whether the student is present in the classroom. The constant monitoring of the student's level of attentiveness becomes a subjective process in modern times when all classes take place in the virtual mode. Therefore, this paper introduces an Intelligent and efficient solution that combines attendance management and engagement analysis. The proposed method uses facial recognition techniques based on facial embeddings and Euclidean distance matching to automatically identify registered students and record the attendance. Additionally, behavioural indicators including head pose analysis, eye gaze estimate, and drowsiness detection utilizing Eye Aspect Ratio (EAR) are used to track student attentiveness. To offer centralized access to attendance data, engagement analytics, and administrative features, a Flask-based web application is created. In order to make it easier to analyze student participation and attentiveness during class, the system also includes event logging and engagement score computation. With an accuracy of 85.00%, experimental evaluation showed that the facial recognition module performed reliably. Teachers can learn more about student's presence and attentiveness by combining engagement monitoring and attendance management into a single framework. The suggested method facilitates data-driven decision-making in online learning environments and provides a workable and affordable alternative for intelligent classroom monitoring

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 Keywords

Intelligent Classroom Systems, Face Recognition, Computer Vision, Student Attendance Management, Face Embeddings, Euclidean Distance Matching, Eye Aspect Ratio (EAR), Drowsiness Detection, Gaze Estimation, Head Pose Estimation, Student Engagement Monitoring, Educational Analytics

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The becoming known of Artificial Intelligence has transformed Traditional Supply Chains into Intelligent Digital Eco Systems. In the defence electronics manufacturing sector, where reliability, security, operability and speed are of Paramount Importance. AI-driven digital Supply Chains are revolutionizing procurement, production, inventory management, logistics and Predictive maintenance. The integration of AI enhances operational efficiency, Reduces Costs, Strengthens Security, Improving decision-making Capabilities.

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Artificial Intelligence, Digital Supply Chain, Predictive Analytics, Smart manufacturing etc.

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ABSTRACT: OBJECTIVES: To assess the knowledge on artificial intelligence among nurses working in government hospital Chittoor Andhra Pradesh. To evaluate the attitude on artificial intelligence among nurses working in government hospital Chittoor Andhra Pradesh. To determine the association between selected demographic variables such as age, gender, educational qualification, year of experience, current working area, type of employment, source of information. METHODOLOGY: Research methodology is a systemic way of doing research to solve a problem. It compromises of problems the objectives of study hypothesis that have been formulated the variable under study the method needs for the data collection and statistical method used for analyzing data and used for data collection and logic behind it. And the whole, it gives a general pattern of gathering and processing of research data. RESULTS: The findings of study regarding level of knowledge and attitude on artificial intelligence among nurses revealed that. 60% of the study population are at the age group between 26 - 35 years. 90% of the population are female 45% of the population are B.sc undergraduate nurses. 45% of the population have 6 to 10 years of experience 42% of the study population are permanent staff nurses 88% of the population have heard about artificial intelligence 63% of the population source of information about artificial intelligence through internet and social media. 78% of the study population attended artificial intelligence related training and workshop. 63% of the population are using electronic health records. 43% of the study population are interested in learning about artificial intelligence in health care. Among the participants 7% of people have adequate knowledge, 60% of people have moderate knowledge, 33% of people were having inadequate knowledge. Among the participants 55% have negative attitude, 28% have moderate attitude and 17% have high attitude. CONCLUSION: The findings of the study concluded that among the participants, the level of knowledge on Artificial Intelligence was 60%, and the level of attitude towards Artificial Intelligence was 55% among nurses working in Government Hospital, Chittoor, Andhra Pradesh. Hence, continuous CNE programmers are essential to enhance awareness regarding Artificial Intelligence among nurses.

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knowledge and attitude, Artificial intelligence among nurses

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Creative Commons Attribution 4.0 and The Open Definition

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Bharatanatyam is an ancient Indian classical dance form that was formerly known as Sadhir.. During the twentieth century, it came to be known as Bharatanatyam. This dance form is a harmonious blend of abhinaya (expression), thalam (rhythm), music, spirituality, and movement. Among these elements, movement plays a vital role. The basic movements of Bharatanatyam are known as adavus. The execution of adavus requires the coordinated use of the hands, feet, and the entire body. Adavus form the foundation of Bharatanatyam training and are the first lessons taught to every student. They are not only essential for beginners but must also be practised consistently throughout a dancer's artistic journey. This article explores the concept and importance of adavus, their historical significance, and their physical and artistic benefits.

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Bharatanatyam, Classical Dance, Adavus, Thalam, Margam, Araimandi

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Creative Commons Attribution 4.0 and The Open Definition

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In today's fast-paced digital environment, the need for quick and secure information transfer without complex authentication processes has become increasingly important. Most existing cloud-based file sharing platforms require users to create accounts and log in before sharing any form of data, which can be time-consuming and inconvenient for short-term or one-time transfers. To address this limitation, this paper proposes a lightweight, network-based data sharing platform that enables users to instantly upload and share text, images, and files through a browser-based interface. The proposed system allows users to generate a unique access link after uploading content. This link can be shared with other users, who can view or download the content directly without requiring any login credentials for text and image sharing. For secure file transfers, user authentication is enforced to maintain data integrity and access control. The platform is designed to combine ease of use with essential security measures, making it suitable for quick and temporary data exchange. The system is developed using React for the front-end interface and .NET for the back-end services. Data storage is handled through Azure Blob Storage and Supabase, while PostgreSQL is used for structured data management. By eliminating mandatory login requirements for basic content sharing, the proposed solution reduces user friction and improves accessibility, offering a faster alternative to traditional cloud storage platforms such as Google Drive for instant data transmission scenarios.

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Secure Data Sharing, Link-Based Access Control, Hybrid Authentication, Time-Bound Sessions, React Web Application, Cloud Storage Integration, RESTful API Architecture

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