Volume 14 | Issue 6

 Abstract

In mainstream educational environments, inclusive education has become a transformative method that guarantees equity, participation, and accessibility for all students. From Segregation to Participation: Advancing Inclusive Education through Multidisciplinary Pedagogy examines how multidisciplinary pedagogy enhances inclusive practices by addressing the cultural, cognitive, social, and emotional diversity of learners. In addition to discussing cutting-edge tactics like project-based learning, art-integrated learning, and cooperative learning in promoting inclusive classrooms, the study emphasises the historical shift from segregation to meaningful participation. It also highlights how crucial curriculum changes, institutional cooperation, teacher competency, and policy support are to developing fair and learner-centred learning environments. The study comes to the conclusion that multidisciplinary pedagogy is a useful strategy for encouraging holistic development, lowering learning obstacles, and guaranteeing meaningful engagement for everyone. The study comes to the conclusion that multidisciplinary pedagogy is a useful strategy for encouraging holistic development, reducing learning barriers, and ensuring meaningful participation for all learners in contemporary education.

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 Keywords

Inclusive Education, Multidisciplinary Pedagogy, Participation, Learner Diversity, Holistic Development

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Khushwant Singh's novel Train To Pakistan' unfurled a poignant depiction of the tumultuous bloodshed and hatred, consequential to the partition of India in 1947. The research article explored the uncanny themes of land, memory and displacement, entwined with the disconcerting ramification of inter-communal violence and loss of identity. It is the attachment of human emotion with one's land and the fear of displacement from it, that took a humongous toll on the memory of people belonging to the village of Mano Majra. The village provided a microcosmic view of the Indian sub-continent witnessing the destruction of home, life, history and belonging. The social structure of the fictional village stood like that of any other village, having the cultural ethos weaved with harmony in its air. The muslims and sikhs of this victimized village devastated the social fabric of society. In order to preserve one's land and dignity, they were more than eager to murder the innocence of humanity. Undoubtedly, the repercussion of partition could not be envisaged. Lakhs of people got displaced, families parted from each other, women got dehumanized and the ugliest face of human's diabolic and devilish disposition was unleashed. The Train To Pakistan investigated the varied and multi-cultural ethnic groups of inhabitants, lost in the flimsy ghostly shadows.

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bloodshed, communal, harmony, dehumanized

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Artificial Intelligence (AI) is changing the way education works today. It helps students learn better, supports teachers in their work, and makes education more organized. This study looks at how AI affects education by collecting opinions and analyzing different areas like personalized learning, automated assessment, and accessibility.Two types of analysis are considered: overall perception and aspect-based impact. Overall, perception shows whether people feel positive or negative about AI in education, while aspect-based analysis focuses on specific areas such as learning support, teacher assistance, and evaluation systems.The results show that AI improves learning speed, understanding, and engagement. However, challenges like overdependence on technology and privacy concerns still exist. The study concludes that AI has a strong positive role in education when used carefully and responsibly.

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Artificial Intelligence, Education, Sentiment Analysis (SA), Aspect-Based Sentiment Analysis (ABSA)

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The rapid growth of digital financial services has transformed the economic landscape of India, particularly among traditionally underserved segments of society. In this context, the Pradhan Mantri Street Vendor's AtmaNirbhar Nidhi (PM SVANidhi) Scheme, launched by the Government of India in 2020, has emerged as a significant initiative aimed at providing affordable working capital loans to street vendors affected by the COVID-19 pandemic. Beyond facilitating access to formal credit, the scheme promotes digital financial inclusion through cashback incentives and rewards linked to digital transactions. This study examines the role of PM SVANidhi in accelerating digital financial transformation among street vendors, with a specific focus on the effectiveness of cashback and Unified Payments Interface (UPI) incentives in encouraging digital payment adoption. The research is based on secondary data collected from government reports, Ministry of Housing and Urban Affairs (MoHUA) publications, PM SVANidhi dashboard statistics, Reserve Bank of India (RBI) reports, National Payments Corporation of India (NPCI) data, journal articles, and other relevant scholarly sources. The study adopts a descriptive and analytical approach to evaluate the scheme's contribution to increasing digital transaction volumes, enhancing financial literacy, and integrating street vendors into the formal financial ecosystem. The findings indicate that cashback incentives and digital transaction rewards have played a crucial role in motivating vendors to adopt cashless payment methods. The widespread use of UPI-based applications has increased transaction transparency, improved financial record-keeping, and strengthened vendors' access to formal financial services. Furthermore, the incentive-based framework has contributed to reducing dependence on cash transactions while fostering confidence in digital payment systems among small-scale entrepreneurs. However, challenges such as limited digital literacy, inadequate technological infrastructure, cybersecurity concerns, and regional disparities continue to affect the scheme's overall effectiveness. The study concludes that PM SVANidhi has successfully combined financial assistance with digital empowerment, creating a sustainable model for promoting financial inclusion among urban informal workers. The integration of cashback benefits and UPI incentives has not only encouraged digital payment adoption but has also supported the broader objectives of India's digital economy agenda. The research recommends enhanced digital literacy programs, improved technological accessibility, and continuous monitoring of incentive mechanisms to maximize the long-term impact of the scheme. The findings contribute to the growing literature on digital financial inclusion and provide valuable insights for policymakers seeking to strengthen digital transformation initiatives within the informal sector.

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PM SVANidhi, Digital Financial Inclusion, UPI, Cashback Incentives, Street Vendors, Digital Payments, Financial Transformation, Informal Sector, India.

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Livestock farming plays a vital role in agricultural productivity, food security, and rural economic development, but continuous animal health monitoring remains difficult because traditional supervision depends on manual observation and delayed veterinary response. This study presents an intelligent livestock health and activity monitoring system using deep learning, embedded automation, and IoT communication for early disease detection and farm management. Images of healthy cattle and cattle affected by Lumpy Skin Disease are collected from a Kaggle dataset and used to train a CNN-VGG19 classification model. The trained model is deployed in a Flask based web application for real time disease prediction using uploaded animal images. Prediction results are transmitted to an Arduino UNO through serial communication for automated decision making. When disease is detected, the system activates a chemical sprayer and displays alerts on an LCD module. Healthy cattle continue under normal monitoring conditions. Additional features include RFID based boundary monitoring, manual food and water control through the Blynk application, and LCD based system status display. Experimental analysis demonstrates improved disease response efficiency, reduced labor dependency, and effective livestock safety monitoring for modern animal husbandry applications. The proposed framework supports reliable automated livestock supervision in small and medium scale farms efficiently.

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Livestock Monitoring, Lumpy Skin Disease, CNN-VGG19, Deep Learning, Arduino UNO, Flask Application, RFID Monitoring, IoT Based Automation, Animal Health Detection.

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PCOD officially rename as PMOS (Polyendocrine metabolic ovarian syndrome) where broadness of disease is covered. This is not ovarian syndrome but multisystem disorder. P stand for polyendocrine i.e affects multiple hormone pathways, M stand for metabolic , o for ovarian i.e maintains clinical link to the ovarian.

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PMOS, atravakshya, yonivyapat, metabolic disorder

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The Garbhadhan Sanskar stands as the first and most significant among the sixteen *Sanskaras* (sacraments) of the Hindu tradition; it frames the inception of human life not merely as a biological process, but rather as a conscious, sacred, and scientific endeavor. This sacrament seeks to harmonize the physical and mental states of the parents prior to the child's birth, thereby ensuring that the offspring's life is auspicious, healthy, and prosperous. The objective of this research paper is to analyze the philosophical, spiritual, and Ayurvedic underpinnings of the *Garbhadhan Sanskar* within the context of modern science - specifically epigenetics, reproductive biology, neurobiology, and nutritional science. The study reveals that the principles expounded in the ancient Indian knowledge system resonate deeply with modern scientific findings. This research elucidates how these ancient sacraments can be re-adopted in the contemporary era, enabling us to comprehend reproduction and family planning through a balanced and holistic lens. It establishes a harmonious synthesis between these two perspectives, the spiritual and the scientific- thereby offering guidance to society in its pursuit of building healthy, prosperous, and empowered lives.

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Garbhadhan Sanskar, Modern Science, Family Planning, Reproductive Biology

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Machine learning (ML) has emerged as a transformative force in modern healthcare, enabling computers to learn from complex medical data and assist clinicians in making faster, more accurate decisions. This paper provides a structured review of how ML techniques -- including supervised learning, unsupervised learning, reinforcement learning, and deep learning -- are being applied across key healthcare domains such as disease diagnosis, drug discovery, medical imaging, patient monitoring, and genomics. We examine representative studies from the literature, compare ML algorithms with respect to accuracy and clinical utility, and discuss the practical challenges that currently hinder large-scale adoption, including data privacy, model interpretability, and regulatory compliance. We further identify open research gaps and outline promising directions for future work, including federated learning, explainable AI, and multimodal data fusion. Our aim is to offer researchers and practitioners a clear, accessible overview of the current landscape and the road ahead.

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machine learning, healthcare, deep learning, medical imaging, disease prediction, drug discovery, electronic health records, federated learning, explainable AI.

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The Metaverse is no longer a speculative idea confined to science fiction. It is emerging as a network of persistent, immersive and commercially valuable virtual environments built through a convergence of virtual reality, augmented reality, gaming engines, blockchain infrastructure, artificial intelligence and digital marketplaces. These virtual environments allow users to create avatars, trade digital goods, display artworks, organise virtual performances, construct virtual architecture and monetise token-linked assets. While such developments have opened new possibilities for creativity and commerce, they have also created difficult questions for copyright law. Traditional copyright doctrine was designed around identifiable authors, territorial infringement, clear copies of protected works and relatively stable licensing arrangements. The Metaverse disrupts these assumptions because copyrightable works may be created collaboratively, generated by artificial intelligence, embedded in virtual spaces, linked to non-fungible tokens or circulated through pseudonymous blockchain transactions. This paper examines whether the existing Indian copyright framework is adequate to address copyright protection and enforcement in the Metaverse. It analyses the copyrightability of virtual assets, authorship and ownership of user-generated content, NFT-related misconceptions, AI-generated works, fair dealing, platform liability, moral rights and cross-border jurisdiction. The paper adopts a doctrinal and comparative legal methodology, relying on Indian statutory provisions, leading Indian case law, selected foreign jurisprudence and international policy materials. It argues that India does not require an entirely separate copyright statute for the Metaverse at this stage, but it does require clearer interpretive guidance, platform governance standards, transparent licensing practices, creator-awareness mechanisms and cross-border cooperation. A balanced framework must protect creators without preventing legitimate remix culture, innovation and user participation in immersive digital environments.

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Metaverse; Copyright; NFTs; Artificial Intelligence; Virtual Assets; User-Generated Content; Platform Liability; Indian Copyright Law; Moral Rights; Digital Enforcement.

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Mirza Ghalib, one of India's greatest Urdu poets, has Ghazals, Letters, and Diary Entries in his literary oeuvre. Delhi, during Ghalib's life, was tumultuous and a space undergoing continual metamorphosis. Ghalib's writings capture this transformation through his sensorial perception of the spaces that he frequents and inhabits. The dynamic interrelation between Space, Time and Literature has given rise to an explosion in the realm of Interdisciplinary studies. The study of his works in light of Polysensorality, one of the key tenets of Geocriticism helps in understanding the layered nuances in spatial comprehension, in opposition to limiting space as a mere backdrop to lived realities.

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Ghalib, Delhi, Polysensorality, Geocriticism, Spatial Comprehension

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Biophilic design is an innovative design approach that aims to reconnect humans with nature within built environments. In modern corporate workplaces, employees often experience stress, mental fatigue, reduced productivity, and a lack of connection with natural surroundings due to highly artificial and enclosed environments. This research focuses on understanding the importance and application of biophilic design principles in corporate interior spaces and how they contribute toward healthier and more sustainable workplaces. The study explores the integration of natural elements such as daylight, ventilation, greenery, natural materials, organic forms, and visual connections with nature within office interiors. It examines how these elements influence employee wellbeing, productivity, creativity, mental health, and overall workplace experience. The research is primarily based on literature studies, theoretical understanding, and comparative case study analysis of corporate environments that successfully implement biophilic design strategies. Through this study, it is observed that biophilic design positively impacts the physical and psychological wellbeing of users while also improving environmental quality and workplace efficiency. The findings conclude that biophilic design is not only an aesthetic approach but also a functional and sustainable strategy for future corporate interiors. By creating a stronger relationship between people and nature, biophilic workplaces help develop healthier, more balanced, and human-centered working environments.

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o Biophilic Design o Corporate Interiors o Workplace Wellbeing o Sustainable Design o Natural Lighting o Employee Productivity o Indoor Greenery o Environmental Psychology o Workplace Experience o Human-Nature Connection

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This study examines the relationship between macroeconomic indicators and shareholder wealth creation in Indian consumption companies, with a focus on understanding whether macroeconomic cycles translate uniformly into firm-level financial performance. The research analyses a set of six representative companies spanning different consumption sub-segments, including aspirational discretionary, cyclical retail, value-oriented retail, and fast-moving consumer goods (FMCG). Key macroeconomic indicators such as foreign portfolio investment (FPI) flows, foreign direct investment (FDI) flows, capacity utilisation, and consumption indices are evaluated alongside company-specific metrics including share price performance, Return on Equity (ROE), and Return on Capital Employed (ROCE). The methodology adopts a descriptive and comparative approach, combining visual trend analysis with firm-level financial evaluation to identify patterns between macroeconomic movements and shareholder outcomes. The findings suggest that while macroeconomic indicators influence short-term performance and market sentiment, they do not independently determine long-term wealth creation. Instead, business model characteristics--such as pricing power, capital efficiency, and operating leverage--play a more significant role in shaping sustained returns. The study highlights that discretionary businesses exhibit higher sensitivity to economic cycles, while FMCG and value-oriented companies demonstrate resilience across phases. Overall, the research reinforces the importance of integrating macroeconomic analysis with firm-level fundamentals, providing insights relevant for equity research, portfolio construction, and investment decision-making in the Indian consumption sector.

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Macroeconomic Indicators; Shareholder Wealth Creation; Indian Consumption Sector; Return on Equity (ROE); Return on Capital Employed (ROCE); FDI; FPI Consumption Index; Equity Research; Business Models

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Accurate cost estimation in interior design is a complex challenge characterized by high-dimensional variables and subjective aesthetic choices. Traditional estimation methods often suffer from significant margins of error due to the non-linear relationship between spatial configurations and material costs. This paper proposes a hybrid computational framework that integrates traditional machine learning (ML) with deep learning for enhanced predictive accuracy. A dual-input pipeline is employed: first, a Convolutional Neural Network (CNN) extracts design features and material styles from 2D architectural blueprints; second, these visual features are fused with structured tabular data--such as square footage, geographical location, and material grades--to feed ensemble learning models, including Random Forest and XGBoost. Experimental results demonstrate that the hybrid framework achieves a Mean Absolute Error of 6.14%, representing a significant improvement over the traditional baseline model. The study concludes that the synergy of computer vision and regression-based ML provides a robust, scalable tool for real-time budgetary forecasting in the architectural and interior design industries.

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Interior Design, Cost Estimation, Cost Prediction, Machine Learning, Computer Vision, Convolutional Neural Network, Deep Learning, XGBoost, Random Forest, Blueprint Analysis.

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 Abstract

IoT-based real-time battery monitoring system

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Battery Management System, Internet of Things, Electric Vehicle, ESP32, Sensors, Real-Time Monitoring, Cloud Platform.

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Development of Tribal Culture Along with Eco-Tourism in Madhya Pradesh: A Global Perspective of Tourism in Alignment with Sustainable Development Goals

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Development of Tribal Culture Along with Eco-Tourism in Madhya Pradesh: A Global Perspective of Tourism in Alignment with Sustainable Development Goals

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Lymphatic filariasis (LF) is the second cause of permanent, long-term disability in the world. It is one of the world's most disabling and disfiguring disease. Filariasis, though not fatal, is an important public health problem. It prevents the afflicted from experiencing a normal working and social life, resulting in matrimonial handicap, inferiority of self, and furthering the cycle of poverty. It affects 750 million every year and in India, 450million people are at risk. Lymphatic filariasis has been identified as one of the only six diseases, which could be targeted for elimination/eradication based on considerations that human beings are the only reservoir of infection. The WHO has now called for targeting filariasis elimination by 2020. India is the largest LF endemic country and has targeted elimination by 2015. non-experimental descriptive design to assess the rural knowledge on their management of filariasis among adults. The sample for the study was 90 adults residing at selected rural communities of Sulekere P.H.C. Then house to house survey was done and found the mothers of toddlers as 8o in Sulekere, 82 in Ramsandra and 86 in Kenchanpura. The sample was selected by using simple random technique. The samples obtained were 23+37+30= 90 from the respective villages. The present study represents the Mean, S.D. and Mean percentage of aspects of knowledge on their practices of mothers of toddler. It reveals that the subjects had a maximum mean of 5.37 with a standard deviation of 0.97 and the minimum mean of 1.60 with the S.D. of 0.63 and mean percentage of 80.0% for foreign body aspiration, the mean score of 2.13 with a S.D.0.57 and mean percentage of 71% regarding cut and laceration, the mean score of 3.82 with S.D of 1.02 and mean percentage of 76.4% regarding burns, scalds and the mean of 2.52 with S.D. of 0.64 and mean parentage of 84.0% regarding drowning., the mean score of 3.24 with a S.D. of 0.78 and mean percentage of .81% regarding stings and bites, the mean score of 2.44 with a S.D. of 0.67 and mean percentage of 81.3% regarding electric shock.

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Knowledge, management, Filariasis, Adults, Eductational Media, and Urban area

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Abstract: A 25 years old male runner walked in with a complaint of pain over the right knee joint and pain gets extended down to the leg for past 2 weeks. The severity of the pain started increasing during mid half of running. he dint complaint of sleep disturbance due to this pain. He did find some relief in cold packs and application of analgesic, but it was just a short duration of relief. He has been diagnosed to have patellofemoral joint syndrome by performing Clark test and squatting and patient is asked to fill Kujala patellofemoral scale (Anterior knee pain scale). since patient had investigations report it was easy to rule out other pathologies like meniscus tear, arthritis or knee instability conditions. As a treatment protocol patient underwent 6 weeks of functional strength training to get a complete recovery from patellofemoral pain syndrome(PFPS).

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KEYWORDS: Patellofemoral pain syndrome, Knee joint, Kujala patellofemoral scale, Functional training

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ABSTRACT In the modern world, different kinds of philosophical concepts are existed. As the part of Indian philosophical contributions are inevitable to the world. Sree Narayana Guru and his philosophical contributions are deeply rooted to Indian society especially in Kerala. Advaita( non-dualist) is the core compound of Sree Narayana Guru's philosophy.

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Keywords:Sree Narayana Guru, Philosophy, Temple, Social Reformations.

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Polycystic Ovary Syndrome (PCOD) is one of the most common endocrine and metabolic disorders affecting women of reproductive age. It is often associated with hormonal imbalance, irregular menstrual cycles, insulin resistance, weight gain, stress, and reduced quality of life. Due to the increasing interest in natural healthcare approaches, herbal nutraceutical formulations have gained attention as supportive alternatives for managing PCOD-related symptoms.The present study focuses on the formulation and evaluation of Aayuherbo Prash, a herbal nutritional preparation developed to support women's wellness and hormonal health. The formulation was prepared using a blend of medicinal herbs and nutrient-rich ingredients including Amla, Fenugreek, Cinnamon, Spearmint, Shatavari, Ashwagandha, Turmeric, Flax Seed, Chia Seed, Pumpkin Seed, Fennel, Honey, and Dry Fruits. These ingredients were selected based on their traditional medicinal importance and potential benefits in supporting metabolism, hormonal balance, antioxidant activity, stress management, and overall nutritional health.The prepared formulation was evaluated for various physicochemical and quality control parameters such as organoleptic properties, pH, homogeneity, moisture content, ash value, extractive value, phytochemical screening, microbial quality, and stability. The formulation exhibited a pleasant herbal aroma, mildly sweet taste, smooth semi-solid consistency, and satisfactory stability under recommended storage conditions. The pH of the formulation was found to be 5.8, indicating its suitability as a herbal nutraceutical product.The results suggest that AAYUHERBO PRASH may serve as a promising herbal nutritional formulation for supporting women's health and the management of PCOD-related concerns. Further clinical studies are required to establish its therapeutic effectiveness and long-term safety.

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PCOD, Herbal Nutraceutical, Women's Wellness, Hormonal Balance, Aayuherbo Prash, Herbal Formulation, Phytochemicals.

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Epilepsy is a chronic neurological disorder characterized by recurrent seizures resulting from abnormal neuronal activity and remains a significant global health concern. Although several antiepileptic drugs are available, treatment resistance and adverse drug reactions continue to limit their effectiveness in many patients. Natural products represent an important source of bioactive compounds with potential therapeutic applications in neurological disorders. Luteolin, a naturally occurring flavonoid isolated from the rhizomes of Cyperus rotundus, has been reported to possess antioxidant, anti-inflammatory, and neuroprotective properties. The present study investigated the potential anticonvulsant activity of luteolin through an in silico molecular docking approach against selected epilepsy-associated protein targets. Luteolin was isolated and purified from the rhizomes of Cyperus rotundus, and molecular docking studies were performed against key epilepsy-related targets, including GABA-A receptor (GABRA1), protein kinase B (AKT1), tumor necrosis factor-alpha (TNF-?), and cyclooxygenase-2 (COX-2/PTGS2). Three-dimensional structures of the target proteins were obtained from the Protein Data Bank, and docking analyses were conducted using standard molecular docking software to evaluate binding affinities and ligand-protein interactions. Luteolin demonstrated favorable binding interactions with all selected targets, forming stable ligand-protein complexes through hydrogen bonding and hydrophobic interactions. The observed binding affinities suggest the potential of luteolin to modulate neurotransmission, neuroinflammatory pathways, and neuronal survival mechanisms associated with epileptogenesis. These findings indicate that luteolin may serve as a promising natural candidate for anticonvulsant drug development. Further experimental studies are warranted to validate its antiepileptic efficacy and elucidate the underlying molecular mechanisms.

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Luteolin; Cyperus rotundus; Epilepsy; Anticonvulsant activity; Molecular docking; GABA-A receptor; AKT1; TNF-?; COX-2.

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