Volume 14 | Issue 3

 Abstract

An underestimated but quantifiable risk to human safety is introduced by the widespread use of infrared (IR) emitters in IoT ecosystems, including smart homes, industrial automation, and hospital settings. Though current IoT frameworks interpret IR emitters as permanently active, context-agnostic actuators, prolonged or unmanaged IR exposure accelerates device deterioration, produces cumulative thermal tissue stress, and induces increasing eye tiredness. The new autonomous safety orchestration framework Infra Shield-IoT, which integrates human-centric IR hazard governance directly into IoT device intelligence, is presented in this study. There are three suggested original contributions:(1) A multi-signal, real-time measurement model for cumulative infrared radiation at the device level is the IR Hazard Exposure Index (IHEI); (2) the Adaptive IR Emission Controller (AIREC), a cloud-free, four-mode autonomous emission management engine; and(3) the Proximity-Aware Safety Mesh (PASM), a peer-consensus sensing-based decentralised multi-device safety coordination framework. The experimental testing at smart factories and hospital wards and smart home test sites achieved a 78.4% reduction of total infrared radiation exposure together with 63.2% energy savings and 94.1% accuracy in human-proximity detection and 97.6% operational continuity during network failure situations. InfraShield-IoT transforms infrared emission into a safety standard which IoT systems must control dynamically in order to reach complete protection for human beings.

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 Keywords

Edge-Native Safety Orchestration, Proximity-Aware Safety Mesh, Human-Centric IoT Safety, IR Hazard Exposure Index, Adaptive IR Emission Control, InfraShield-IoT, Device Computability, Autonomous Duty Cycling, Smart Ecosystem Radiation Governance, and Occupational IR Mitigation.

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Chronotherapeutic drug delivery systems (CDDS) are designed to synchronize drug release with the body's biological rhythms to optimize therapeutic outcomes. Numerous pathological conditions such as asthma, hypertension, rheumatoid arthritis, peptic ulcer disease, and cardiovascular disorders exhibit circadian variation in symptom severity. Conventional dosage forms fail to accommodate these temporal changes, often leading to suboptimal efficacy or increased adverse effects. CDDS aim to provide time-programmed, pulsatile, or site-specific drug release corresponding to disease rhythm. This review highlights the biological basis of chronotherapy, formulation strategies, advanced technologies, evaluation parameters, marketed products, and future research directions. The integration of chronobiology with modern pharmaceutical engineering offers promising opportunities for personalized medicine.

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 Keywords

Chronotherapy, Circadian rhythm, Pulsatile drug delivery, Lag time, Time-controlled release, Chrono pharmaceutics.

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Abstract Population distribution displays the spatial pattern of residential population in an area, while Density is a concentration of population per unit of an area. As distribution of population shows actual locational spread of population and population density expresses the ratio between number of people and land surface area. So in this paper Pali district has been selected as the study area for assessing the impacts of population distribution and population density at administrative macro and micro level units. Pali District's population distribution according to Census 2011, manifests uneven spatial and rural-urban population. This paper aimed to assess the impact of spatio-temporal pattern of population density on land use change. The conclusion of this study can facilitate planners to make appropriate area specific eco-tourism and extention of irrigation command plans for employment generation. Keywords : Population Distribution, Population density, irrigation, employment generation.

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Population Distribution, Population density, irrigation, employment generation.

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West Bengal has a historically notable district of Murshidabad that provides a unique example of exploring sustainable tourism in a district having rich cultural background. The Murshidabad district was the seat of the administrative capital of Bengal, Bihar and Odisha in Mughal period. Other remarkable buildings which present architectural and cultural splendour in the area are Hazarduari Palace, Katra Mosque, Nashipur Rajbari and Jagat Seth Museum. Although it has a rich cultural heritage, Murshidabad is still afflicted by various problems including poor conservation, poor infrastructure, minimal community participation as well as degradation of the environment. Such constraints have curtailed the capacity of the district to use tourism as a sustainable development vehicle. Nonetheless, future hopes are high as evidenced by new policy actions, historic conservation projects, ecotourism and community-based ventures. The present research is a combination of the field-based research and national and international best practices that are used to analyze the potential and obstacles that influence sustainable tourism in Murshidabad. To enhance tourist attraction without compromising on the ecological balance and cultural authenticity, it encourages an inclusive and collaborative model that involves the entities of public and private nature and incorporation of local stakeholders. Besides providing policy suggestions that are aimed at strengthening the status of Murshidabad as an example of the heritage-based sustainable development, the results contribute to the broader topic of sustainable tourist governance.

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 Keywords

Sustainable Tourism, Heritage Conservation, Community Based Tourism, Environmental Management, Murshidabad District.

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Withania somnifera (ashwagandha) is an Ayurvedic adaptogen increasingly studied for stress/anxiety reduction and potential neuroprotective effects. This review critically examines phytochemistry, mechanisms, clinical evidence in stress and anxiety, preclinical and clinical evidence relevant to neurodegenerative disorders, and safety signals. Methods: We searched PubMed/PMC, ClinicalTrials.gov and major journals for randomized clinical trials, systematic reviews, preclinical neuroprotection studies and safety reports up to 2025. Selected high-quality RCTs, systematic reviews and mechanistic papers were prioritized. Results: Multiple RCTs and meta-analyses report reductions in perceived stress/anxiety and cortisol with ashwagandha extracts (typical doses 225-600 mg/day) versus placebo; effect sizes vary and risk of bias exists in several trials. Preclinical studies show antioxidant, anti-inflammatory, modulation of HPA axis and direct neuronal effects of withanolides; some withanolides cross the blood-brain barrier and show benefit in animal models of Alzheimer's and Parkinson's disease. Safety data is generally favorable in short trials, but recent case series and pharmacovigilance reports describe rare herb-associated liver injury and possible thyroid effects. Conclusions: Evidence supports ashwagandha's anxiolytic and stress-reducing potential; neuroprotective findings are promising but largely preclinical with limited human data. Larger, standardized, long-term clinical trials and rigorous pharmacovigilance are needed before recommending ashwagandha routinely for neurodegenerative disorders.

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Ashwagandha; Withania somnifera; Stress; Neurodegeneration; Withanolides; Neuroprotection; Anxiety; Cognitive impairment. ________________________________________

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The present study examines the level of career awareness among secondary school students and explores differences based on gender and school locale. Adopting a descriptive survey method, the study was conducted on a stratified random sample of 125 students drawn from seven blocks of Coochbehar District, West Bengal. The findings reveal that the majority of students possess an average level of career awareness, with only a small proportion demonstrating very high awareness. Statistical analysis indicates no significant difference in career awareness between male and female students. However, a significant difference was observed between rural and urban students, with urban students exhibiting higher levels of career awareness. The study highlights the need for targeted career guidance interventions, particularly in rural areas, to ensure equitable access to career-related information and opportunities.

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Career Awareness, Secondary School Students

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Teachers in rural India face challenges like limited access to quality materials, heavy workloads, and language barriers. This paper presents Shiksha Sahaayak, an AI-powered Learning and Teaching Assistant designed to improve teaching in lowresource classrooms. The system has three modules: an Automatic Worksheet and Presentation Generator that creates curriculumbased materials using NLP and Large Language Models; a Multilingual Voice Assistant and Chatbot that offers real-time support in English, Hindi, and Marathi; and a Visual Attendance Tracker that uses computer vision and facial recognition for participation analysis. Built with Django, OpenCV, and HuggingFace APIs, the platform aims to lessen teacher workload, raise instructional quality, and promote inclusive education. This conceptual study highlights the design framework, the technologies used, and the expected impact, supporting future large-scale deployment in line with India's National Education Policy (NEP) 2020.

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Artificial Intelligence, Rural Education, Multilingual Chatbot, Computer Vision, NLP, NEP 2020

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This study takes into account the interaction between tribal identity and social mobility for the prominent tribal groups in Wayanad: the Paniya, Kurichya, Kuruma, Adiya, and Kattunaickan. Through a textual analysis of academic reports, official records, and ethnographic inventories, the analysis takes into account how education, economic change, and cultural adaptation affect mobility trends among these groups. The findings reveal dramatic contrasts: the Kurichya have achieved upward mobility through land ownership and education, while the Paniya and Adiya are marginalised by long-standing problems of illiteracy and poverty. Economic change from traditional forest livelihoods to wage labour and government schemes has dramatically improved tribal living standards, while cultural identity is increasingly shaped by mainstream social forces. The study explores the conflict between socioeconomic progress and cultural preservation, illustrating that some groups remain effective in integrating into modern society while others cannot maintain their distinctive heritage. These findings highlight the need for inclusive policy frameworks that promote tribal development without sacrificing cultural identity.

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Social mobility, Tribal identity, Wayanad tribes, Paniya, Kurichya, Adiya, Kattunaickan, Educational access, Economic transitions,

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: This paper presents CareNest, a role-based patient monitoring and management system developed to improve healthcare supervision through a secure and centralized digital platform. Conventional patient record management systems often rely on manual processes that lead to data redundancy, delayed communication, and limited accessibility. The proposed system introduces structured role-based access control to ensure that administrators, medical staff, and guardians can securely access and manage relevant information. CareNest enables medication monitoring, tablet history tracking, and restricted item management with real-time notification features to enhance transparency and communication. The system is implemented using modern web technologies and database management techniques to ensure scalability, data integrity, and operational efficiency. Experimental evaluation demonstrates improved accuracy, reduced manual errors, and faster information flow within healthcare environments. The proposed platform provides a reliable and scalable solution for institutions seeking efficient patient supervision and digital healthcare management.

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Patient Monitoring, Role-Based Access Control, Healthcare Management System, Real-Time Notification, Web Application, Digital Healthcare.

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The integration of digital tools into school has redefined teaching and learning with a notable impact on science education at the secondary level.The integration of digital media content into science instruction has emerged as a significant pedagogical innovation in contemporary education. The present study examines the impact of digital content based science learning on the scientific creativity of secondary level students. Using an experimental design with pre-test, post-test, and retention measures, the study compares the performance of students exposed to digital media content with those taught through conventional instructional methods. The investigation also sought to determine whether the integration of digital media content into classroom instruction influences students' scientific creativity and whether such influence differs across sex and SES. Measurable improvements were observed within the experimental group across testing phases. The findings indicate that digital media content contributes positively to the development and sustenance of scientific creativity by enhancing engagement, conceptual understanding, and creative scientific expression but has no impact across Sex and SES. The study emphasizes the educational value of structured digital interventions in science learning and highlights their role in promoting higher order thinking skills among adolescents.

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Digital media content, Science Education, Scientific Creativity, Secondary school students, Experimental Study, Retention, Socio Economic Status (SES).

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By enabling brands to offer highly personalised experiences that increase engagement and loyalty, AI-driven personalisation is changing consumer-centric marketing. Artificial intelligence (AI) has evolved into an essential resource for marketing strategies as consumer demand for tailored interactions expands and data-driven insights help to build more important brand-customer links. Emphasising its relevance for contemporary brand engagement, the paper investigates how artificial intelligence is transforming personalisation. Emphasising its impact on consumer engagement, this research aims to provide a thorough review of the present literature on AI-driven personalisation. The paper compiles data from several sources to examine how AI technologies such as machine learning, predictive analytics, and natural language processing improve marketing strategies by means of tailored advertising, personalised recommendations, and dynamic content distribution. This study uses journal studies and scholarly research articles for a meticulous examination of the literature. To ensure an in-depth examination of the topic, sources were selected for their relevance to AI-driven personalisation and brand interaction. Studies show that by developing deeper connections, increasing brand loyalty, and improving customer experiences, AI-driven personalisation greatly improves consumer-brand interactions. Still, major determinants of customer trust are data privacy concerns, questions of ethics, and algorithmic biases. This paper synthesises critical insights to improve comprehension of AI's function towards sustainable consumer-centric marketing and offers brands solutions to personalisation concerns. Future research should look at consumer opinions on trustworthy AI frameworks, consumer personalisation of AI, and the combination of AI with subsequent technologies to improve marketing methods

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Personalization, Artificial Intelligence, Ethics, Brand Engagement, Sustainability, Consumer-Centric Marketing, Consumer-Brand interactions

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Extraction of valuable bioactive compounds from plant matrices and food by-products is essential for developing value-added products in nutraceuticals, pharmaceuticals, cosmetics, and functional foods. This study represents the various extraction techniques helps to extract the compound, majorly it classified into conventional (traditional solvent-based) and non-conventional (modern, often green) techniques. The traditional technique like maceration, percolation, soxhlet extraction are widely used, they often require longer extraction times, higher solvent volumes, and greater energy input. In contrast, non-conventional techniques including ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE), supercritical fluid extraction (SFE), natural deep eutectic solvents (NADES), are presented as advanced, sustainable alternatives. These offer superior efficiency, reduced solvent and energy use, shorter times, better preservation of thermolabile compounds, and environmental benefits, though challenges like equipment costs and scale-up persist. The study also compares the sustainability, scalability, economic feasibility, and application potential of each method. Overall, the transition from conventional to innovative green extraction technologies reflects the growing demand for environmentally friendly, high-efficiency, and industrially viable processes for bioactive compound recovery.

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Bioactive compound, Extraction, Green Technology, Eco-friendly

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The term civil service in India first emerged during the administration of the East India Company. The Civil Servants were initially engaged in trade; however, as the Company commenced its territorial acquisitions, it progressively evolved from a commercial entity into an administrative government, thereby transforming its 'civil servants' from mere traders into competent administrators. This paper examines the establishment of Fort William College in 1800 and its role in transforming the East India Company's civil servants from commercial agents into administrators of a territorial empire. Founded under Richard Wellesley, the College reflected the Company's transition from trade to governance, as its officials assumed judicial, revenue, and diplomatic responsibilities across diverse Indian societies. Wellesley envisioned a structured program of education that would equip civil servants with linguistic competence, legal knowledge, and moral discipline suited to their expanded authority.

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East India Company; British civil servants; Fort William College; Colonial Civil Servant; language studies; colonial administration;

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In the contemporary health care system, to effectively manage the patients, it is imperative to make right forecasts of the diseases like heart disease and diabetes, among others. This article provides a Hybrid Quantum-Classical System which makes use of Quantum Variational Classifier (QVC) to predict illnesses in medicine. The suggested system takes advantage of the capabilities of quantum computing to investigate high-dimensional spaces that are generally difficult to find by classical machine learning models. Combination of quantum variational circuits and classical machine learning methods allows the effective classification of the clinical data, including age, glucose levels, and BMI. This type of system is tested by using medical datasets, and the outcomes reveal that this system is more robust, especially in the presence of noise or in case of smaller training sets. The QVC demonstrates the improvements in prediction accuracy that are promising when compared to the traditional models such as Support Vector Machines (SVM), Logistic Regression, and Neural Networks. Such a framework preconditions the next-generation quantum-powered medical diagnostics, which will be more computationally efficient and future predictions, despite limited or noisy data.

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 Keywords

Hybrid Quantum-Classical System, Quantum Variational Classifier, Medical Disease Prediction, Heart Disease, Diabetes, Quantum Computing, Clinical Data Classification, Noisy Data, Quantum Variational Circuits, Computational Efficiency

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Rapid access to patient medical information is critical in emergency situations where timely clinical decisions can greatly affect the outcome of treatment. However, there is still a large portion of the population without readily accessible digital health records, and many of the solutions are internet-dependent and battery-powered, which limits their reliability in a critical situation. In this paper, a secure battery-free wearable and cloud-based framework for on-the-spot emergency medical information retrieval is presented. The proposed system combines a battery-free wearable device that is embedded with Near Field Communication (NFC) and Quick Response (QR) technologies to achieve fast and contactless access to encrypted patient information. A cross-platform mobile application written in the Dart language (Flutter) and a cloud backend (Firebase) for secure storage, authentication and real-time synchronization of medical records. The framework has the provision for both online and offline access to ensure the availability of crucial medical data even in low-connectivity environments. Encryption mechanisms are implemented to ensure the security of sensitive patient information and to ensure controlled access to that information. Experimental evaluation shows system is able to access critical medical data in seconds and helps to improve emergency response efficiency and digital healthcare accessibility in resource constrained environments.

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Emergency medical information retrieval, Battery-free wearable devices, NFC-based healthcare, Cloud-based medical records, Secure health data systems, Offline-first access.

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Self-efficacy plays a vital role in achievement in mathematics. This study is an attempt to study the relationship between self-efficacy and achievement in mathematics. The sample was comprised of 200 secondary students studying in Government Senior Secondary School, Bajakhana, and Hans Raj Memorial Senior Secondary School District Faridkot, Punjab. For the data collection, Self-efficacy Scale by Mathur and Bhatnagar (2012) and the marks obtained by student in Xth (P.S.E.B.) considered as their achievement scores in mathematics were used by investigator. T-test was used to ascertain the difference of means between variables. The analysis revealed that school students studying in Private schools had greater self-efficacy mathematics as compared to school students studying in Government schools. It was also found that urban students had higher self-efficacy as compared to rural students. There was a positive and significant relationship between self-efficacy and achievement in mathematics.

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Self-efficacy, achievement in mathematics, rural and urban, government and private, secondary school students.

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The rapid digitization of modern infrastructures has significantly expanded the scale and complexity of cyber threats. Traditional security mechanisms, primarily dependent on rule-based detection and centralized monitoring, are increasingly inadequate against sophisticated attacks such as advanced persistent threats (APTs), zero-day exploits, ransomware variants, and AI-driven intrusions. In response to these evolving challenges, this study proposes an intelligent cybersecurity framework that integrates Artificial Intelligence (AI) and Blockchain technology to create a decentralized, adaptive, and resilient security architecture. Artificial Intelligence enhances cybersecurity by enabling real-time anomaly detection, predictive threat intelligence, and automated incident response through machine learning and deep learning models. However, AI-based systems often rely on centralized data repositories, making them vulnerable to manipulation and single points of failure. Blockchain technology addresses these limitations by offering decentralized trust management, tamper-proof logging, immutable audit trails, and smart contract- based policy enforcement. The proposed hybrid framework combines AI's analytical capabilities with blockchain's distributed integrity mechanisms. The architecture includes layered components comprising secure data acquisition, AI-driven intelligence processing, decentralized consensus validation, and administrative control interfaces. The system is evaluated using simulated cyberattack scenarios and benchmark intrusion datasets to assess detection accuracy, response latency, system reliability, and resistance to data tampering. Results indicate that the integrated AI-Blockchain model improves detection precision, reduces false positives, enhances log integrity, and minimizes centralized vulnerabilities compared to standalone AI or blockchain solutions. The research concludes that hybrid intelligent architectures represent a promising direction for next-generation cybersecurity systems capable of protecting critical digital ecosystems.

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Artificial Intelligence, Blockchain Technology, Cybersecurity Framework, Intrusion Detection, Decentralized Security, Smart Contracts, Anomaly Detection, Distributed Ledger, Threat Intelligence, Secure Logging

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In the field of education, Cognitive Style plays a pivotal role in shaping the teaching and learning process of future educators. The present study, titled " A study on Locality-based Variation in Cognitive Style among Secondary Student Teachers," was undertaken to investigate the cognitive patterns of those preparing for the secondary teaching profession. To achieve this, the researcher adopted the Survey Method. A total sample of 150 secondary student teachers (64 Rural and 86 Urban) was selected using the Simple Random Sampling Technique. Data were collected using a validated Self-made Cognitive Style Inventory which measures Cognitive Style in five dimensions namely Knowing, Planning, Creative, understanding and Thinking style. The statistical analysis revealed that there is no significant difference in the overall cognitive style of secondary student teachers based on their locality.

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Cognitive Style, Secondary Student Teachers, Locality Variation, Cognitive Style Dimensions.

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In today's world, digital technology has become an integral part of people's daily lives.With the increasing dependance on the internet, smartphone, social media and online services personal information has now become an important asset. In this situation the question of privacy has emerged as not only a moral or social issue but also a method of constitutional right. Article 21 of the Constitution of India which guarantees the right to life and personal liberty has been expanded over time to judicial interpretation. The landmark judgement of the supreme court in the case of Justice KS Pattaswami vs. Union of India in 2017 is an important milestone in this evolution. A nine judge bench unanimously declared that privacy is a fundamental right to shrink in article 21 of the constitution. This judgement let the Constitutional foundation for the protection of citizens data in the digital era This paper analyzed the historical evolution of article 21, the need for privacy in the digital era, State surveillance, cyber security and the events of the digital personal data protection Act 2023. The conflict between personal freedom and national security is also discussed. The study seeks to show that privacy is an essential constitutional value for protecting human dignity in the digital era.

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Article 21, Right to Privacy, Indian constitution, Digital era, Fundamental Rights, Data Protection

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The rapid advancement of Artificial Intelligence (AI) has significantly transformed governance mechanisms and policy-making processes across the world. Governments are increasingly integrating AI-driven technologies to enhance efficiency, transparency, and participatory governance. In democratic societies, the effectiveness of public policy depends not only on institutional capacity but also on citizen participation and collaborative governance mechanisms. Artificial Intelligence offers new possibilities for evidence-based policy formulation, efficient implementation, continuous monitoring, and systematic impact assessment. In India, the expansion of digital infrastructure has created an enabling environment for the application of AI in governance. One of the most significant welfare initiatives in the health sector is the Ayushman Bharat Yojana, which aims to provide financial protection and healthcare access to economically vulnerable populations. Managing such a large-scale healthcare program requires sophisticated systems capable of handling vast amounts of data related to beneficiaries, healthcare providers, treatment outcomes, and financial transactions. Artificial Intelligence has the potential to strengthen policy processes in such programs by enabling predictive analytics, fraud detection, automated verification, and real-time monitoring of healthcare delivery systems. Additionally, AI-enabled digital platforms can facilitate citizen engagement through grievance redressal mechanisms, feedback systems, and participatory decision-making processes. This research paper examines the role of Artificial Intelligence as a tool for constructive public policy that promotes participative governance. Using Ayushman Bharat Yojana as a case study, the study analyzes how AI can enhance policy formulation, policy implementation, policy monitoring and evaluation, impact assessment, and citizen participation in governance processes. The study also highlights the ethical challenges and governance concerns associated with AI-driven policy systems. The findings suggest that AI can significantly improve policy effectiveness, transparency, and responsiveness while strengthening collaborative governance structures. However, the successful integration of AI in public policy requires robust institutional frameworks, data protection measures, and accountability mechanisms to ensure democratic and ethical governance.

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Artificial Intelligence, Public Policy, Participative Governance, Digital Governance, Health Policy, Welfare Schemes, Data Governance

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