Volume 14 | Issue 3

 Abstract

Influencer marketing via social media has transformed how brands engage consumers, emerging as a rapidly growing component of contemporary marketing strategies (Campbell & Farrell, 2020; Vrontis et al., 2021). This theoretical study examines how different social media platforms shape influencer-follower dynamics and advertising effectiveness by synthesizing evidence from recent data-driven research. Prior studies consistently indicate that influencer credibility--reflected through trustworthiness, expertise, and perceived authenticity--plays a pivotal role in shaping consumer attitudes and purchase intentions (Saima & Khan, 2020; Kim & Kim, 2021). Moreover, platform-specific features and technological affordances influence the development and intensity of parasocial relationships between influencers and followers, which subsequently affect advertising outcomes and brand evaluations (Lou et al., 2023; Ki et al., 2020). The analysis further highlights the importance of social identity and influencer-audience congruence in amplifying marketing effectiveness across platforms (Farivar & Wang, 2022; Belanche et al., 2021). Existing evidence also suggests that influencer marketing campaigns often generate higher returns on investment than traditional promotional channels, with a substantial proportion of marketers reporting favorable performance outcomes (Dimitrieska & Efremova, 2021). However, such effectiveness is contingent upon strategic alignment, including the careful matching of influencer attributes with the target audience and platform characteristics, the maintenance of influencer credibility, and the facilitation of authentic and meaningful engagement. Overall, this integrative perspective contributes to a comprehensive understanding of the current influencer marketing landscape, its critical success factors, and the potential for leveraging social media analytics to optimize influencer-driven campaigns.

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Influencer marketing; Social media platforms; Credibility; Parasocial relationships; Congruence; Consumer engagement

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This study undertakes a comparative analysis of Kazuo Ishiguro's Never Let Me Go and Valeria Luiselli's Lost Children Archive, both in terms of their treatment of the related themes of silence, exile, and belonging in contemporary literary discourse. Ishiguro's dystopian fiction presents a picture of cloned children living in a controlled environment in England, meant to donate their organs, while Luiselli's politicised fiction deals with the issue of migrant children in the border region between Mexico and the U.S. Although both fictions differ in genre, location, and narrative style, they both examine the ways in which human life is controlled and regulated. Drawing on the works of psychology, trauma, and biopolitics, this study argues that silence in both novels does not simply refer to the absence of speech but, in fact, refers to a structural condition created by power relations. In Never Let Me Go, silence is internalized and becomes a form of emotional survival that works against rebellion, despite the partial revelation of the truth. The compliance of the clones with their predetermined fate, for instance, demonstrates the nuanced violence of institutional power, where belonging is meticulously crafted but remains conditional in its very construction. Memory, especially in relation to Kathy's narrative, appears as a tenuous substitute for freedom, an intimate space wherein dignity and identity are maintained. In contrast, Lost Children Archive understands silence as something enforced through politics. The voicelessness of the migrant children is caused by the borders and the legal system. The multi-layered narrative of Luiselli, who uses documentation and testimony in the narrative, is reminiscent of the fragmentary experience of the migrant communities. Exile is understood here as physical and generational rather than existential. Belonging is still tenuous and filtered through narrative. The act of archiving is understood here as an ethical imperative and a form of resistance to the politics of disappearance. Through the juxtaposition of the two works, the study reveals the manner in which contemporary fiction brings together dystopian fantasy and political realism to address the concerns that are shared in terms of vulnerability, precarity, and the value of human life. The two works follow the trajectory of innocence to revelation, constructed belonging to irrevocable exile, and finally, the rejection of incendiary revolt in favor of endurance and the preservation of the narrative. This juxtaposition situates literature as a key site to explore the manner in which the individual navigates identity in terms of systems that commodify, displace, and silence them. In an interdisciplinary dialogue with psychoanalysis, trauma studies, and migration studies literature, this study seeks to make an additional contribution to the scholarly discussions on marginality, memory, and ethics in twenty-first-century literature. The study contends that while Ishiguro and Luiselli write from different contexts, they share a common emphasis on the human affirmation of storytelling, in terms of memory or documentation

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 Keywords

Silence, Exile, Belonging, Trauma, Psychoanalysis, Biopolitics.

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The matrix is a very useful and significant mathematical construct of contemporary society. Originally formed as a methodical way of solving linear systems of equations, matrix theory has developed into a large framework that supports many disciplines, including quantum physics, linear algebra, numerical analysis, engineering design and most recently, data science. Matrix analysis allows for the development of complex multivariable systems, through the use of a structured, compact representation of linear transformations. Matrices are important in the practical sciences as well as in theoretical mathematics. They are used to create large-scale simulations, optimization methods, and computational models. Computers also rely heavily on matrices for their ability to represent input-output and optimization models in economics, to represent quantum states and coordinate transformations in physics, and in developing machine learning techniques and computer graphic transformations. Through the combination of analytic methods and existing literature, this paper investigates the theoretical foundation, key computational methods and interdisciplinary applications of matrices. The paper illustrates that matrices will remain vital for the development of modern scientific and technological inquiry and will serve as a common mathematical language between various disciplines.

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- Numerical analysis, multidisciplinary applications, computational methods, matrix theory, and linear algebra.

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The growth of digital fashion platforms has increased the need for intelligent and personalized styling systems. This paper presents an AI-powered Smart Wardrobe that combines deep learning-based clothing classification with a hybrid recommendation engine. Users can upload garment images and receive outfit suggestions based on body type, skin tone, and wear history. A transfer learning approach using ResNet50 is applied for clothing classification. The model achieved 93.2% validation accuracy and 88.7% real-world test accuracy. The system enhances wardrobe utilization, minimizes outfit repetition, and promotes sustainable fashion through automated personalization.

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Smart Wardrobe, Deep Learning, ResNet50, CLIP, Visual Embeddings, Personalized Recommendation, Computer Vision

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The people has seen fast alterations in anti- technology over the last few decades, and with the rise of cloud computing, the way we develop applications has changed quickly. This has made it easier to build applications that are both efficient and scalable. In recent years, the digital world has introduced many new innovations, especially with the use of Artificial Intelligence, or AI. This paper looks at how AI and cloud computing work together to help modernize applications by offering better services and infrastructure. By using both AI and cloud technologies, companies can now manage resources more smartly, use predictive analytics, automate deployment and scaling, and improve security, which helps them offer better solutions to their customers. Additionally, using cloud and AI technologies allows businesses to save money and deliver better services. The paper also talks about some challenges, like protecting personal data, and how strong AI governance can help solve these issues.

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AI, Cloud Computing

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Although comparative oncologists two decades ago may have tended to be on the defensive when arguing that fish, which are water-dwelling, poikilothermic vertebrates of greatly diverse form, might be of interest to cancer investigators, justification of their use no longer seems necessary. As testified by the increasing number of publications on fish tumors appearing in international journals, various fish species have now become widely accepted as useful tools for cancer research with, in some cases, distinct advantages over models using rodents or avian species. In particular, the study of tumors in lower aquatic animals has recently gained considerable importance as a means of detecting injurious agents in the environment. Investigation of fish tumors is also integral part of the basic biological approach to understanding possible common mechanisms involved in cancer development at various phylogenetic levels. The finding that tumors can be readily induced at various sites in fish species by different chemical carcinogens or viruses was of central significance in this context. Also if such fish is eaten by humans what are the possibilities of effect of such fishes can be further studied.

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fish, cancer, tumor, pathomorphology, tumorigenesis

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A medicinal compound's physicochemical characteristics, stability, manufacturability, and ultimately its therapeutic efficacy are all significantly influenced by its solid-state crystal structure. Detailed knowledge of molecular arrangement, intermolecular interactions, and polymorphism in drug substances has been made possible by advances in structural characterization techniques, particularly single-crystal and powder X-ray diffraction. This study examines the connection between pharmaceutical performance and crystal structures, emphasizing the effects of hydrogen bonding networks, polymorphism, solvate formation, and crystal engineering techniques. In contemporary pharmaceutical development, case studies of clinically important medications demonstrate how structural insights inform formulation design, regulatory choices, and lifecycle management.

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Solid-state crystal structure, Medicinal compounds, Pharmaceutical performance, physicochemical properties, Polymorphism, Hydrogen bonding networks, Solvate formation, Crystal engineering, Single-crystal X-ray diffraction

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Nanocavity Zeolite Y Encapsulated M(II) (M= Co, Ni, Cu & Zn) ternary complexes of L-Tyrosine and L-Histidine in situ in Na-Y Zeolites were synthesized using the ion exchange and flexible ligand methods. Initially, the metal ions were introduced into the zeolite framework through ion exchange with Na? ions, followed by diffusion of the amino acid ligands tyrosine and histidine into the super cages of the zeolite, where coordination with the metal centers occurred to form encapsulated ternary complexes by the reaction of ion exchanged process and flexible ligand method. The geometry and binding modes were explained by using various characterization techniques such as TGA, XRD, ESR, SEM, EDX, UV and IR spectroscopy

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 Keywords

Zeolite-Y, L-Tyrosine, L-Histidine, Flexible ligand synthesis, Encapsulation

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Artificial Intelligence (AI) has become the new technological paradigm that changes the industry of healthcare, finance, education, manufacturing, and autonomous systems. The strategic choice of programming languages is the main aspect of AI creation as it has a direct impact on the system performance, scalability, development efficiency, and deployment possibility. The paper is an analytical review of the programming languages in relation to Artificial Intelligence, the discussion of their development from symbolic AI to machine learning and deep learning models in modern times. The article assesses high-level languages such as Python, R, C++, Java, Lisp, and Prolog covering their paradigms, strengths, weaknesses, and areas of use. The research is comparative and descriptive in nature as it examines the suitability of language in fields of AI, including machine learning, deep learning, natural language processing, computer vision and robotics. The results have shown that high-level languages have high prototyping speed and large ecosystem advantages, whereas low-level languages offer better execution speed and hardware-level accessibility. The paper adds up to the conclusion that there is no single programming language that can fit all AI requirements; a hybrid and multi-language architecture is the best approach to the development of modern AI systems. The study offers advice to researchers, developers, and higher learning institutions on the suitable programming language that can be used, depending on the complexity of the project, the performance, and the scaling aspects of the project.

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Artificial Intelligence, Programming Languages, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Python, R, C++, Java, Lisp.

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Driven by the need for financial sustainability, global aviation has shifted toward privatization, with private airports now managing 41% of global passengers despite making up only 14% of facilities worldwide. This study evaluates the impact of this transition on operational performance, revealing that private sector involvement--especially through Private Equity--can increase passengers per flight by 20% and overall traffic by up to 84% compared to government-run hubs. By integrating 2026 "digital-first" technologies like biometric tunnels, these airports have successfully reduced passenger processing times and boosted non-aeronautical revenue, which is projected to grow at a CAGR of 8.7% through 2030. Ultimately, while privatized airports excel in asset utilization and capacity growth, the research concludes that robust regulatory oversight is essential to prevent monopolistic pricing and ensure private profit aligns with public interests and carbon-neutrality targets.

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Airport Privatization, Operational Performance, Industry 4.0, Non-Aeronautical Revenue, Public-Private Partnership (PPP), Asset Utilization.

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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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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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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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 Abstract

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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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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