Volume 14 | Issue 6 |

 Abstract

Background :Patellofemoral Pain Syndrome (PFPS) is one of the most common causes of anterior knee pain, especially among young adults. Several modifiable and non-modifiable factors such as BMI, Q-angle, and pain intensity may influence the occurrence and severity of PFPS. However, the relationship between these factors and functional disability remains inadequately explored in general populations. Aim: To determine the prevalence of PFPS in the general population and to examine the correlation between selected risk factors (BMI, Q-angle, and VAS) and functional disability assessed using the Kujala Anterior Knee Pain Scale. Methodology: A cross-sectional study was conducted on 100 participants aged 20-40 years in the physiotherapy outpatient department of a multispeciality hospital. BMI, Q-angle, and pain intensity (VAS) were recorded, along with functional disability using the Kujala Score. Data were analyzed using descriptive statistics and Karl Pearson correlation. Results: A strong negative correlation was found between Kujala Score and BMI (r = -0.94), Q-angle (r = -0.92), and VAS (r = -0.91). Higher BMI, increased Q-angle, and higher VAS scores were associated with poor knee function. Conclusion: The study demonstrates that BMI, Q-angle, and pain intensity are strongly associated with PFPS severity. Early identification and modification of these risk factors may help prevent functional decline and chronic knee pain.

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 Keywords

Patellofemoral Pain Syndrome, Kujala Anterior Knee Pain Scale, Body Mass Index, Visual Analog Scale.

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This study was conducted with the objective of analysing the role and impact of inter- state migrant workers in the social and economic development of Kerala. Over the last three decades, the job market in Kerala witnessing significant changes. Foreign migration, higher education and changing work tastes have reduced the participation of native workers in the workforce, and to fill this gap, inter- state workers from states like Bihar, West Bengal, Assam, Odisha, Jharkhand and UP have started arriving in Kerala. This phenomenon, known as "Replacement Migration" has created a major change in the structure of the workplace, the work model, and the method of hiring.

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 Keywords

Guest workers, Kerala, Malayalees, Replacement Migration

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Nestled in the fertile plains of the Upper Ganga-Yamuna Doab, the site of Sinauli in Baghpat district, Uttar Pradesh, unearthed in 2005 and further excavated in 2018 by the ASI, has emerged as one of the most significant Late Harappan and Chalcolithic burial grounds, representing the OCP culture. Among its many discoveries, the burials of women interred with copper antenna swords, decorated coffins, and intricate grave goods stand apart as evidence of women warriors, revealing that gender in this society was not merely a biological category but a construct deeply embedded in social, symbolic, and ritual hierarchies. This paper historically and archaeologically explores the three prominent women burials of Sinauli in contrast with the male burials of the site, examining differential funerary practices to illuminate gender roles, social stratification, and hierarchies within the late Harappan Chalcolithic milieu. Through a micro-analysis of the burial record, drawing on archaeological material as primary evidence and contextualizing it through secondary scholarly interpretations, the study interrogates questions of dynamics of power and shifting meanings of gender in proto-historic Indian society, demonstrating how Sinauli offers invaluable glimpses into a cultural landscape where gender intersects with ritual, authority, social organization, and conceptions of the afterlife.

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 Keywords

Women warriors, Women burials, Dynamics of power, Gender distinction.

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The Computer Vision-Based Queue Time Prediction and Order Recognition for Canteen Automation project presents a smart, cloud-based solution to modernize traditional institutional canteen operations by replacing manual ordering, billing, and food collection processes with a fully automated digital system. The existing manual approach often results in long queues, billing errors, order mismatches, communication delays, and poor record management, especially during peak hours. The proposed system addresses these challenges through a real-time, integrated platform that enables users to browse digital menus, place food orders remotely, make secure digital payments, and receive unique token numbers for organized food collection.The system utilizes a mobile or web application, Firebase Realtime Database, and Wi-Fi-enabled ESP8266/ESP32 controllers to establish seamless communication between customers, billing counters, and kitchen staff. Orders are instantly synchronized with the cloud, allowing the kitchen to receive them in real time without relying on paper slips or verbal communication. Automated bill calculation, token generation, and live order status updates significantly improve operational efficiency while reducing waiting time and human errors. Optional modules such as RFID authentication, QR code login, thermal token printing, and LED/Buzzer notifications further enhance the automation process.The proposed architecture is modular, scalable, and suitable for deployment in educational institutions as part of Smart Campus initiatives. It also provides centralized storage of order history and transaction records, enabling administrators to monitor operations and analyze sales data effectively. Future enhancements such as AI-based food recommendations, queue time prediction, inventory management, and robotic food delivery can be integrated without redesigning the core system.Overall, the proposed system improves service speed, transparency, billing accuracy, customer satisfaction, and operational management while promoting a contactless, paperless, and intelligent canteen environment. It offers a reliable, secure, and scalable solution for modern institutional food service automation.

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 Keywords

: Canteen Automation, Queue Time Prediction, Computer Vision, Firebase Realtime Database, Internet of Things (IoT).

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Data protection has emerged as one of the defining commercial and regulatory challenges of the digital age. This paper examines how privacy governance shapes consumer trust, corporate transparency, and cross-border trade in modern e-commerce. Drawing on primary regulatory frameworks -- including the EU General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA/CPRA), and India's Digital Personal Data Protection Act (DPDP) -- alongside empirical data from IBM, Cisco, Usercentrics, DLA Piper, and Surfshark, the paper analyses the financial, reputational, and operational consequences of data breaches and non-compliance. Key findings include: the global average breach cost of $4.44 million in 2025 (IBM); over EUR7.1 billion in cumulative GDPR fines since 2018; a data privacy market valued at $175.3 billion and growing at 16.8% annually; and evidence that 75% of consumers will not purchase from organisations they do not trust with their data. The paper further explores the emerging risk posed by ungoverned artificial intelligence adoption, including "shadow AI" practices that cost organisations an average of $4.63 million per breach. Strategic recommendations are provided for both organisations and individuals, covering governance frameworks, technical safeguards, third-party risk management, and consumer best practices. The analysis concludes that data protection is no longer merely a legal obligation but a measurable source of competitive advantage and a prerequisite for sustainable participation in global digital commerce.

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Keywords: data protection; e-commerce; consumer trust; GDPR; CCPA; data breaches; privacy regulation; cybersecurity; AI governance; digital trade; transparency; personal data; compliance; information security; shadow AI; third-party risk

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continuous sensing, communication, and data exchange across diverse application domains. However, conventional IoT systems often encounter limitations in handling massive volumes of heterogeneous data, making intelligent decision-making, real-time analytics, and autonomous operation increasingly challenging. The integration of Artificial Intelligence (AI) with IoT, commonly referred to as the Artificial Intelligence of Things (AIoT), has emerged as a transformative paradigm that enhances the intelligence, adaptability, and efficiency of connected systems. This review presents a comprehensive analysis of recent advances in AI-driven IoT technologies and explores their applications, enabling technologies, research challenges, and future directions. The review examines the integration of machine learning, deep learning, reinforcement learning, computer vision, natural language processing, edge intelligence, cloud computing, blockchain, digital twins, federated learning, and explainable artificial intelligence within AIoT environments. Furthermore, the study discusses the adoption of AIoT in smart healthcare, precision agriculture, industrial automation, smart cities, intelligent transportation, environmental monitoring, and energy management. A systematic literature review methodology based on the PRISMA framework was adopted to identify, screen, evaluate, and synthesize recent peer-reviewed publications from major scientific databases. The collected literature was critically analysed to identify technological developments, application trends, research gaps, and emerging opportunities. The review indicates that AIoT significantly improves automation, predictive analytics, operational efficiency, resource utilization, and decision support across multiple sectors. Nevertheless, several issues--including cybersecurity, privacy preservation, interoperability, scalability, explainability, energy efficiency, and ethical governance--continue to hinder large-scale implementation. The paper concludes by presenting future research directions focusing on edge intelligence, federated learning, multimodal AI, digital twins, sustainable AIoT architectures, and trustworthy intelligent systems. The findings provide researchers and practitioners with a consolidated understanding of the current AIoT landscape and identify promising avenues for future investigation.

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Keywords: Artificial Intelligence, Internet of Things, AIoT, Machine Learning, Deep Learning, Edge Computing, Smart Healthcare, Smart Cities, Industrial IoT, Digital Twin, Federated Learning, Explainable AI, Intelligent Systems, Systematic Review.

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ABSTRACT: The welfare state means that everyone is taken care of. Everyone should be able to get their basic needs met, no matter how much money they have or where they come from. The main goal is to make society more fair and equal by lowering poverty and inequality. The welfare state is also based on the idea of social justice; A welfare state is a system where the government undertakes the primary responsibility for protecting and promoting the economic and social well-being of its citizens. It operates on the principles of equal opportunity, equitable wealth distribution, and public responsibility for those unable to care for themselves A welfare state is a system where the government takes responsibility for the well-being of its citizens.

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welfare state, Social Security, welfare of prisoners, from 200 AD to 500 AD, Democratic Foundation, Equal Wealth Distribution, Social Justice and Dignity, Maternity Benefit Act 1929, Garibi Hatao, 2014 Pradhan Mantri Jan Dhan Yojana

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Abstract This research paper explores the multiple aspects of the leadership of Adivasi women in India, particularly looking into ways in which they resist, reform and transform their communities. Using decolonial feminist epistemologies and recent scholarship on the subject, the paper discusses three main domains of the leadership of Adivasi women land rights activism and politics, formal political representation through constitutional quotas and community based economic and environmental governance. The discussion is grounded on the cases of struggles in Muthanga and Chengara in Kerala, emergence of leaders like C.K Janu and Dansari Anasuya Seethakka, and community projects involving the leadership of Kondh women's management of forests, and tribal cooperative initiatives among others. This paper seeks to highlight the fact that leadership of Adivasi women is complex and multidimensional, intersecting the realms of caste, indigeneity, gender and class. It further shows how the leadership of Adivasi women is defined by its distinctive epistemology which is characterized by struggle resistance to state developmentalism and patriarchal practices within their communities.

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Keywords: Adivasi women, leadership, resistance, political representation, decolonial feminism, Panchayati Raj, land rights, forest governance

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 Abstract

भारतीय दर्शन परंपरा का चरम लक्ष्य 'मोक्ष' या 'कैवल्य' की प्राप्ति है, जिसे सर्वकालिक दुखनिवृत्ति माना गया है। पातंजल योगदर्शन का केंद्रीय सिद्धांत 'चित्तवृत्तिनिरोधः' है, जिसे सिद्ध करने के लिए समाधिपाद में 'अभ्यास' और 'वैराग्य' का विधान है। किंतु, यह उच्च मार्ग केवल तीव्र संवेग वाले साधकों के लिए सुलभ है। सांसारिक विक्षेपों, चंचलता और अशुद्धियों से घिरे मध्यम एवं मंद श्रेणी के साधकों के लिए साधनपाद का 'क्रियायोग' (तप, स्वाध्याय और ईश्वरप्रणिधान) मोक्ष-साधना की अनिवार्य पूर्वपीठिका बनता है। तत्वमीमांसीय दृष्टि: योग दर्शन की पुरुष-प्रकृति द्वैतवादी तत्वमीमांसा के अनुसार, अविद्या जनित 'संयोग' ही बंधन का कारण है, जिससे चित्त में पंचक्लेश (अविद्या, अस्मिता, राग, द्वेष, अभिनिवेश) उत्पन्न होते हैं। क्रियायोग इन क्लेशों पर सीधा आघात कर इन्हें 'तनूकृत' (क्षीण) करता है। मोक्ष में अनिवार्यता: 'तप' के बिना चित्त और इंद्रियों की अशुद्धि का क्षय असंभव है; 'स्वाध्याय' सात्विक बुद्धि का विकास कर 'विवेकख्याति' (पुरुष-प्रकृति भेदज्ञान) का मार्ग प्रशस्त करता है; तथा 'ईश्वरप्रणिधान' व्यष्टि अहंकार का विसर्जन कर नए कर्माशयों और संस्कारों के चक्र को तोड़ देता है। क्रियायोग अष्टांगयोग से पृथक कोई मार्ग नहीं, बल्कि उसकी आधारशिला है। इसके बिना संसारी चित्त का समाधि की योग्यता प्राप्त करना और अंततः मोक्ष (कैवल्य) तक पहुँच पाना सर्वथा असंभव है। अतः मोक्ष-साधना के व्यावहारिक क्रियान्वयन में क्रियायोग की तत्वमीमांसीय अनिवार्यता अकाट्य है।

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 Keywords

पातंजल योगदर्शन, क्रियायोग, तप, स्वाध्याय, ईश्वर प्रणिधान, कैवल्य

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India is increasingly using artificial intelligence (AI) and Machine Learning (ML) in the public sector to improve efficiency, governance and public service delivery. These technologies are being used in areas such as welfare schemes, predictive policing, taxation systems, healthcare, and smart cities projects. While ai can make administration faster and more data driven, it also creates serious concerns regarding accountability and transparency. This paper examines the various issues arising from the use of ai based decision making systems in the Indian public sector. One major concern is that many ai systems operate as "black boxes, where it is difficult to pinpoint and understand how decisions were made. This opaqueness and lack of transparency along with other issues can affect important constitutional principles such as equality, fairness, right to information, privacy, etc under article 14 and 21 of the constitution. This study also highlights lack of proper laws and regulatory mechanisms governing AI in India. This paper argues that India needs a strong regulatory framework to ensure responsible use of ai in governance. It suggests measures such as the use of Explainable AI(XAI), independent auditing of algorithms and stronger human oversight in decision making. These safeguards are necessary to ensure that technological advancement does not weaken constitutional rights, public accountability, and citizens trust in government institutions.

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 Keywords

accountability, transparency, public sector, Artificial Intelligence, Automated Decision making Systems, Machine Learning, legal Framework, use of AI in India

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