Volume 14 | Issue 6

 Abstract

Abstract -- Indoor Air Quality (IAQ) has emerged as a critical determinant of human health, comfort, and cognitive productivity, particularly as urbanization leads individuals to spend approximately 90% of their lives in enclosed environments. Conventional ventilation systems, which typically operate on static schedules or manual controls, fail to respond to dynamic fluctuations in pollutant concentrations and occupancy levels. This lack of adaptability often results in an insufficient air circulation leading to the accumulation of hazardous contaminants such as carbon dioxide, VOCs and significant energy inefficiency due to unnecessary operation. This paper presents a comprehensive study on the design and implementation of an intelligent, IoT-based Smart Ventilation System. By integrating low-cost, high-efficiency sensors such as the MQ-135 for air quality and the DHT11 for temperature and humidity, the system enables real-time environmental monitoring via a microcontroller platform. The proposed solution utilizes automated control algorithms to dynamically adjust exhaust fan speeds and air intake based on live sensor feedback, facilitating Demand-Controlled Ventilation. This project focuses on technical simplicity and low power consumption, making it a feasible intervention for residential, educational, and commercial spaces. The system bridges the gap between environmental health and energy conservation to provide a cost-effective path toward healthier indoor ecosystems.

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-- Smart Ventilation System, Indoor Air Quality (IAQ), Internet of Things (IoT), MQ135 Sensor, DHT11 Sensor, Arduino Uno, Automated Ventilation, Air Quality Monitoring, Energy Efficiency, Environmental Monitoring, Smart Building, HVAC Automation, Real-Time Monitoring.

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Prescription pattern evaluation is a useful method for examining how medicines are prescribed in healthcare settings. It helps identify prescribing trends among healthcare professionals and determines whether medicines are being used appropriately and effectively. Irrational prescribing practices, such as excessive use of multiple medicines, unnecessary antibiotic prescriptions, and inappropriate drug choices, can increase treatment costs, cause adverse drug reactions, and negatively affect patient health outcomes. This study was carried out to assess prescribing patterns in a hospital and evaluate the rational use of medicines. A cross-sectional observational approach was adopted, and prescriptions were collected and reviewed over a defined study period. Several prescribing indicators were analyzed, including the average number of medicines prescribed per patient, the use of generic and brand names, the frequency of antibiotic and injectable drug prescriptions, and the completeness of prescription information. The analysis showed that many prescriptions contained multiple medications, indicating a trend toward polypharmacy. Antibiotics were prescribed frequently, and in some cases their use appeared unnecessary, which may contribute to the growing problem of antimicrobial resistance. The study also found that brand-name prescribing was more common than generic prescribing, potentially increasing the financial burden on patients. Furthermore, some prescriptions lacked important information such as dosage instructions, duration of therapy, and other essential details required for safe medication use. The findings emphasize the need for regular monitoring and evaluation of prescribing practices. Prescription audits can help identify areas for improvement and encourage rational drug use. Overall, continuous assessment and appropriate interventions are important for promoting safe, effective, and cost-efficient medication therapy, ultimately improving the quality of healthcare services and patient outcomes.I. .

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Prescription Pattern Evaluation, Rational Drug Use, Hospital Prescriptions, Drug Utilization Study, Prescribing Practices, Medication Safety, Polypharmacy, Antibiotic Use, Generic Prescribing, Essential Medicines, Clinical Pharmacy, Healthcare Quality, Drug Therapy Assessment, Prescription Monitoring, Patient Safety, Medication Errors, Drug Interactions, Pharmacovigilance, Rational Prescribing, and WHO Prescribing Indicators.

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Hyperparameter optimization (HPO) of deep neural networks is a computationally expensive black-box problem that significantly affects model performance. Manual tuning is impractical for modern architectures, motivating the use of automated optimization methods. This paper proposes a hybrid metaheuristic algorithm that integrates the Aquila Optimizer (AO) with Genetic Algorithm (GA) operators for automated HPO of a convolutional neural network (CNN). The proposed method incorporates three mechanisms: opposition-based learning (OBL) for population initialization, a cosine-annealed mutation schedule, and distance-aware archive-guided crossover to preserve population diversity during exploitation. The optimizer searches for four CNN hyperparameters--learning rate, batch size, dropout rate, and SGD momentum--by minimizing classification error on a validation set. Experiments are conducted on four image classification benchmarks: MNIST, Fashion-MNIST, EMNIST, and CIFAR-10, using three independent random seeds and a fixed evaluation budget of 610 fitness evaluations per run. The proposed hybrid achieves accuracies of 98.87%, 89.38%, 99.08%, and 62.38% on the respective datasets, consistently outperforming the standalone AO and achieving performance comparable to the GA, with the largest improvement observed on Fashion-MNIST (+0.37%).

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Hyperparameter Optimization, Convolutional Neural Networks, Aquila Optimizer, Genetic Algorithm, Metaheuristic Optimization, Opposition-Based Learning, Cosine Annealing.

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Background: Escherichia coli continue to be the most prevalent causal organism for UTIs, which are among the most prevalent bacterial infections observed in typical clinical settings. The dependability of traditional empirical regimens has been undermined by the increasing appearance of multidrug-resistant uropathogens. To support sensible prescribing, region-specific antibiograms are required, especially in central India where there is a dearth of available data. Objectives: To ascertain E. coli frequency in urine culture isolates and to describe its profile of antibiotic sensitivity, including the prevalence of multidrug resistance (MDR). Methods: Over the course of eighteen months, a cross-sectional research was carried out at the microbiology department of a tertiary care teaching hospital in Indore, Madhya Pradesh. Clinically suspected UTI patients provided 350 mid-stream clean-catch urine specimens. The calibrated loop technique was used to process the specimens on CLED and MacConkey agar, and >=10 CFU/mL was considered serious bacteriuria. Standard biochemical processes were used to identify E. coli.Mueller-Hinton agar was tested for antibiotic susceptibility using the Kirby-Bauer disc diffusion method in accordance with CLSI M100 (2023) criteria. Non-susceptibility to at least one agent in three or more antimicrobial classes was the definition of MDR according to the Magiorakos criterion. Results: 97 (27.7%) of the 350 specimens that were processed had substantial bacteriuria. Pseudomonas aeruginosa (9.3%) and Klebsiella pneumoniae (11.3%) were the next most common isolates, with E. coli accounting for 60 out of 97 culture-positive samples (61.9%). 62.9% of all positive cultures came from people between the ages of 20 and 49. The 60 E. Coli isolates showed the greatest levels of resistance to ampicillin (86.7%), cotrimoxazole (66.7%), ciprofloxacin (63.3%), and third-generation cephalosporins (46.7 to 60.0%). The best activity was maintained by amikacin (21.7%), nitrofurantoin (15.0%), piperacillin-tazobactam (13.3%), and imipenem (6.7%). Outpatient isolates had a slightly higher MDR rate (97.6%) than inpatient isolates (89.5%), with 57 out of 60 isolates (95.0%) meeting the criteria for multidrug resistance. Conclusions: Resistance to commonly prescribed oral agents has reached a level at which empirical use of ampicillin, cotrimoxazole or fluoroquinolones is no longer justifiable in this setting. While carbapenems, aminoglycosides, and ?-lactamase-inhibitor combos ought to be preserved for difficult or hospital-acquired infections, nitrofurantoin is still a reasonable option for simple lower UTIs in the community. A functional antimicrobial stewardship program and routine urine culture prior to starting treatment are now required, not optional.

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Escherichia coli, multidrug resistance, tertiary care hospital,urinary tract infection, central India, antibiotic resistance, and antimicrobial stewardship.

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The bilateral relationship between India and China has evolved into a paradoxical condition best described as 'stable instability'--a persistent structural state in which open conflict is avoided yet genuine normalization remains elusive. This paper analyses the systemic drivers, historical antecedents, and contemporary manifestations of this condition. Drawing on power-transition theory, complex interdependence frameworks, and constructivist perspectives on identity and threat perception, the study argues that recurring border friction, asymmetric economic integration, and competing regional orders collectively produce a self-reinforcing equilibrium of managed tension. The paper examines the 2020 Galwan Valley clash as an inflection point that crystallized the new normal, traces subsequent confidence-deficit dynamics, and evaluates the structural constraints that render full strategic rapprochement improbable. It concludes that both states have implicitly accepted the logic of competitive coexistence, and that future stability hinges on institutionalizing crisis-management mechanisms rather than resolving the underlying strategic rivalry.

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India-China relations; stable instability; border disputes; competitive coexistence; power transition; Galwan Valley; strategic rivalry

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Microplastic pollution represents a severe, escalating systemic threat to global public health and environmental integrity. These persistent polymer fragments--measuring between 1 nm and 5 mm--infiltrate biological systems via oral ingestion, inhalation, and dermal exposure. Once inside the organism, they resist standard elimination mechanisms, accumulate chronically within vital organs, and trigger low-grade tissue vitiation. This paper establishes a comprehensive conceptual bridge between the contemporary toxicology of microplastics and the classical Ayurvedic framework of Dushi Visha (attenuated, latent, or cumulative toxins). Historically defined by Acharya Sushruta as an altered, low-potency poison that evades total metabolic expulsion due to encapsulation by Kapha dosha, Dushi Visha remains dormant until environmental or metabolic triggers cause system-wide disruption.This paper analyzes classical texts (Sushruta Samhita, Charaka Samhita, and Ashtanga Hridaya) alongside modern toxicological profiles of polymers like Polyethylene (PE), Polystyrene (PS), and Polyvinyl Chloride (PVC). Our findings indicate a 90% functional alignment between the pathodynamics of microplastic bioaccumulation and the clinical stages of Dushi Visha. Both entities display identical properties of low immediate lethal potency (Alpa-veerya), high tissue affinity (Dhatu-pradushana), and aggravation by environmental shifts (Kala and Desha). This cross-disciplinary synthesis provides an innovative, integrative therapeutic model. It combines contemporary cellular detoxification strategies with traditional Ayurvedic Agada Tantra protocols (Dushivishari Gulika and Panchakarma) to mitigate the chronic burden of plastic accumulation in the human body.

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Dushi Visha, Microplastic, pollution

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Dreams provide the inner essence of an individual at the subconscious level and play an important role in homoeopathic case taking as well as Repertorization, so also in homoeopathic prescribing. This study explores the clinical utility of dreams in understanding the inner mental state of a patient and its reportorial significance. This study highlighted the role of dreams in individualizing prescriptions by analyzing recurrent, vivid, elaborate dreams that have a powerful impact on a patient. This retrospective study evaluated cases from the OPD of Shalinitai Meghe Homoeopathy Hospital, College& Research Center, Nagpur, and demonstrated how 'Dream' rubrics from Dr. Kent's Repertory and Synthesis Repertory can help in the selection of the similimum.The observations emphasize that dreams not only reflect the suppressed desires and emotions of the patient but also contributes to the Repertorial Totality, thus providing valuable insight into homoeopathic prescriptions.

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Dreams, Homoeopathy, case taking, Subconscious mental state, Individualization.

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Plant species classification and leaf disease detection are essential in modern agriculture for improving crop productivity and reducing losses. Traditional manual inspection methods are time-consuming and inefficient for bulky applications. This work presents a deep learning-based approach for automated plant species and disease classification using MobileNetV2 and ResNet50 models. MobileNetV2 is used for efficient plant species recognition, while ResNet50 is applied for accurate disease detection from leaf images. Experimental results demonstrate that the proposed system achieves high classification accuracy and better efficiency compared to conventional methods. The developed framework supports real-time crop monitoring and disease diagnosis, contributing to smart and sustainable agricultural applications.

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deep learning, CNN, MobileNetV2, image classification, smart agriculture.

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Deepfake technology uses advanced artificial intelligence and deep learning techniques to generate highly realistic manipulated videos that imitate human appearance, facial expressions, and behavior. The rapid growth of deepfake generation methods has created significant challenges related to misinformation, identity fraud, cybersecurity, and digital media authenticity. Detecting manipulated content has become increasingly difficult due to continuous improvements in visual quality and synthesis techniques. This study presents an effective deepfake video detection framework based on EfficientNet-B0 and Vision Transformer architectures. EfficientNet-B0 serves as the primary feature extraction model, capturing subtle facial artifacts such as texture inconsistencies, blending errors, and unnatural boundaries, while the Vision Transformer analyzes global contextual relationships through an attention mechanism. A structured preprocessing pipeline involving frame extraction, face detection, cropping, normalization, and data augmentation is employed to enhance model robustness and generalization. The framework is trained and evaluated using benchmark deepfake datasets containing diverse manipulation techniques. A Flask based web application is integrated for video upload and prediction. Experimental results demonstrate high detection accuracy, reliability, and effectiveness in distinguishing real and manipulated videos.

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Deepfake Detection, EfficientNet-B0, Vision Transformer, Deep Learning, Computer Vision, Media Forensics, Video Classification, Flask Application.

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 Abstract

?? ??? ???? ?????? ???????????? ?? ?????? ???????? ??? ???????? ???????? ??????? ?? ??????????? ?????? ?? ???????? ???? ??? 2016 ??? ??????????? ?? ???, ???? ?? ????-?????? ???????????? ?? ??????-????? ???????????? ?? ?? ???? ?? ??? ?????? ??? ?? ?????? 2016 ?? 2024 ?? ?? ???????? ???? ?? ????? ???? ?? ?????? ?? ?? ?????? ?? ? ???? ???? ????? ??????? ????????? ??? ?? ??????? ??????? ?? ???? ?? ????? ????? ??? ???? ???????? ?? ??? ?????????? ??????? ?????? ?? ?? ?????? ?? ?????? ?? ????????? ?????? ?? ????? ???? ??? ??, ?? ?????? ?? ???????? ??????? ?? ???????? ???? ???? ??? ?? ???????? ????? ??? ?? ?????? ?? ?????, ????? ?????? ????? ?? ?????????? ?? ????? ????? ?? ?????? ?? ?????? ?? ???? ??? ???????? ??? ?????? ??????? ??? ???? ??? ??? ??, ?? ??? ???? ?????? ??????? ?? ????? ???????? ???? ???????? ?? ?? ????? ???????? ???? ??? ?????, ?? ?????? ????-?????????? ?? ??? ?????? ???????? ????? ?? ?????? ???? ?? ?????? ?? ?????????? ?? ??? ?????? ??????? ??? ?? ?????? ?? ????? ?? ??? ?? ?????????? ?????? ???????? ???? ??? (?????????????? ?? ????? ???????????? ????????, 2024)?

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??????, ?????? ????????????, ??????? ???????, ????????, ?????? ??????, ??????, ????? ????????

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??????? ??? ??? ??????? ??????????? (Artificial Intelligence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??????? ???????????, ??????? ?????, MSME, ???? ???????, ?????? ????????????

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Artificial Intelligence (AI) has become an important technology in the modern banking sector. Banks are using AI to improve customer service, detect fraud, manage risks, and increase operational efficiency. AI-powered tools such as chatbots, virtual assistants, and automated loan processing systems help banks provide faster and more accurate services to customers. This research paper studies the impact of Artificial Intelligence on banking operations and customer satisfaction. The study also examines the advantages, challenges, and future opportunities of AI in the banking sector. Both primary and secondary data are used to understand how AI is transforming the banking industry in India. Artificial Intelligence refers to computer systems and machines that can perform tasks requiring human intelligence, such as learning, problem-solving, decision-making, and communication. Artificial Intelligence (AI) has become one of the most important technological innovations in the modern banking industry. AI refers to the ability of machines and computer systems to perform tasks that normally require human intelligence, such as learning, problem-solving, decision-making, and understanding customer behavior. With rapid digital transformation, banks across the world are increasingly adopting AI technologies to improve their services and operational efficiency. The banking sector has experienced significant changes due to the use of AI-based applications such as chatbots, virtual assistants, fraud detection systems, robotic process automation, and predictive analytics. These technologies help banks provide faster, more accurate, and personalized services to customers. AI also supports financial institutions in reducing operational costs, improving risk management, and enhancing cybersecurity measures. In recent years, customer expectations for quick and efficient banking services have increased. AI enables banks to analyze large amounts of customer data and offer customized financial solutions. It also helps detect fraudulent transactions in real time and improves decision-making processes related to loans, investments, and credit management. Despite its advantages, the implementation of AI in banking also creates challenges such as data privacy concerns, cybersecurity risks, high implementation costs, and possible reduction in employment opportunities due to automation. Therefore, it is important to study both the positive and negative impacts of AI on the banking industry. This research paper aims to examine the impact of Artificial Intelligence in the banking sector, focusing on its role in customer service, fraud detection, operational efficiency, and financial decision-making. The study also explores the challenges faced by banks in adopting AI technologies and suggests future opportunities for sustainable growth in the banking industry.

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Artificial Intelligence (AI) has become an important technology in the modern banking sector. Banks are using AI to improve customer service, detect fraud, manage risks, and increase operational efficiency. AI-powered tools such as chatbots, virtual assistants, and automated loan processing systems help banks provide faster and more accurate services to customers. This research paper studies the impact of Artificial Intelligence on banking operations and customer satisfaction. The study also exa

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The legitimisation of any authority necessitates control over institutions of knowledge and when the ruler are not native people the requirement becomes more imperative as the authority itself requires legitimization from the other people whom it tries to rule. The British power in India was a colonial power and also a foreign power so it needed to control more the knowledge system of the native people. The Colonial powers have not only been ruling through brute power but their hegemony was established more by education and institution that they established in colonies and India was no exception to this experimentation. The paper talks about how the university system was established in India from 1915 to 1947 and how gradually it gets shaped by the freedom movement that started in a big way after the arrival of Gandhi ji in India. The Calcutta University Commission Report played a central role in shaping the university education in India. The official policies were more or less guided by its policy of 'controlling mind' of the colonised populace.

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Keywords: Colonialism, Legitimacy, native people, institutions and knowledge system.

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1 Solar Panel Cleaning, 2 Automated Cleaning, 3 Arduino Based

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Mental health reflects an individual's emotional balance, behavioral insight, cognitive processes, and decision-making capabilities. The modern lifestyle has negatively impacted individuals' mental health, consequently affecting their daily behavior and routines as a result individuals suffer from mental disorders such as anxiety, stress, and depression which includes people of every age group. According to estimates by the World Health Organization (WHO), by the year 2020, approximately 20% of India's population is expected to suffer from mental disorders, and depression is the second-leading cause of disease burden globally.[1] Today, mental health stands as the greatest challenge facing the world, for even now, mental disorders are not recognized as actual diseases; instead, they are viewed merely as a form of mental weakness on the part of the individual. Previous researches indicate that mental disorders are considered a primary contributing factor to heart disease. The objective of this article is to examine the impact of bhramari pranayama on mental health, drawing upon findings from prior research and the study of classical yogic texts. Yoga plays a pivotal role in enhancing mental well-being, as this practice exerts a positive influence on an individual's holistic health. Bhramari pranayama is a specific breathing technique that positively influences an individual's thoughts and emotions. The consistent practice of bhramari pranayama helps alleviate mental disorders such as stress, anxiety, and depression. Various texts on Yoga also mention the positive impact of the regular practice of Bhramari Pranayama on mental health. Based on the findings derived from numerous studies, it is evident that the vibrations generated by Bhramari Pranayama exert a positive influence on the mind and the nervous system, thereby enhancing an individual's mental health.

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Bhramari Pranayama, Mental Health, Stress, Depression

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

???????? ??? ????? ???????? ???? ?? ??????? ??????????? ?? ?????? ?? ????? ??? ?????????? ?????? ???????? ???? ??? ?? ?????? ?? ????? ???????? ?? ????????? ???? ?? ?? AI ?????? ??????? ????? ?????, ???, ???? ?? ????? ???? ???????? ?????? ?? ??? ?????? ???????? ?? ??? ??? ??? ???? ?????? ?????????, ??????? ?? ????????? ??????? ?? ??????? ??? ???? ???????? ? ??? ??? ??? ?? ??????? AI ?????? ??????? ????? ????? ?? ???????? ?????? ???? ?? ????????? ?????? ???? ??? ??, ????? ????-??????, ????????????? ?? ??????? ???????? ?? ???? ?? ????? ?? ???? ?? ?????? ???? ?? ???? ???-?????? ?? ??? ??? ????????, ?????????? ??? ????????????? ?????? ?? ?????? ??? ??, ?????? ????? ????? ????????? ???????, ?????????? ???????, ???-??????, ?????? ??????? ??? AI ???? ????? ?????? ?? ?????? ??? ???????? ???? ??? ??? ?????? ?? ???????? ?? ??????? ??? ?? ??????? ??????????? ????? ???????? ???? ?? ??????? ??? ? ?? ??????? ???? ?? ?? ? ?? ?????? ???? ?? ??????? AI ???? ????????? ??? ????? ????? ?? ??? ??? ????-??????, ?????-??????? ?? ?????? ?????? ?????? ???? ??, ????? ????? ?????? ???????, ????????? ????? ?? ??????? ?????? ?? ????? ??? ?? ???? ??? ???? ??? AI ?? ??????? ???????? ??????? ?? ???????? ??? ???? ??, ???? ???? ???????, ????? ?? ?????????? ?????? ????? ??????? ?? ?? ??????, ?????? ?? ?????? ?? ???? ?? ???? ??? ?????????? ?? ??? ?????????? ???? ?? ?? ????? ???????? ???? ?? ?????? ?????? ??????? ?? ???????? ?????? ?? ???????? ???? ??? ??????? ??????????? ?? ??-???????? ?? ????? ????? ??? ????? ??, ???? ????? ??????? ?? ?????? ???, ??????????? ?????

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??????? ???????????, ????? ???????? ????, ?????? ???????, ?????? ?????????, ???????, ???????, ????? ?? ???????, ????????? ??????

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This article undertakes a postcolonial reading of Salman Rushdie's Shalimar the Clown (2005), foregrounding its complex engagement with radicalisation, imperial violence, and the fractured identities of the post-9/11 world. While existing criticism often treats the novel as a narrative of terrorism and revenge, this study argues that Rushdie constructs terrorism not as isolated ideological extremism but as a historical and political continuum rooted in colonialism, militarisation, and the global geopolitics of the War on Terror. Drawing on theoretical frameworks from Edward Said, Homi Bhabha, Frantz Fanon, Gayatri Spivak, Achille Mbembe, Aamir Mufti, and Ananya Jahanara Kabir, the article demonstrates how the novel makes visible the psychic and material conditions under which violence emerges. The paper proposes that Shalimar the Clown maps radicalisation through three intersecting forces: (1) postcolonial trauma and imperial residue in Kashmir, (2) fractured diasporic and hybrid identities in the era of globalisation, and (3) the necropolitical logics of Western counter terror discourses after 9/11. By integrating postcolonial theory directly into literary interpretation, this article situates Shalimar the Clown as a key text in understanding how personal grief, cultural dislocation, and historical injustice converge into political violence in the twenty-first century.

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Salman Rushdie; Shalimar the Clown; postcolonialism; Kashmir; radicalisation; terrorism; diaspora; identity; necropolitics; 9/11; globalisation; empire.

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Keywords: Structural Equation Modeling; Technology Acceptance; UTAUT2; TPACK-AI; Mixed-Methods Research

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Arthritis is a chronic musculoskeletal disorder characterized by joint pain, inflammation, stiffness, and reduced mobility, significantly affecting the quality of life of patients. Osteoarthritis (OA) and Rheumatoid Arthritis (RA) are the most common forms of arthritis requiring long-term pharmacological management. Various classes of drugs such as Non Steroidal Anti-Inflammatory Drugs (NSAIDs), corticosteroids, analgesics, and Disease Modifying Anti-Rheumatic Drugs (DMARDs) are widely used in the treatment of arthritis. However, prolonged use of these medications may lead to adverse drug reactions (ADRs), resulting in complications and reduced patient safety.

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Osteoarthritis , Rheumatoid Arthritis, Drug Utilization, Adverse Drug Reactions, NSAIDs, DMARDs

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This study focuses on the formulation and evaluation of a multipurpose herbal hair oil using natural ingredients known for their hair care benefits. The primary aim is to develop a stable, effective, and consumer-friendly oil that promotes hair growth, prevents dandruff, strengthens hair shafts, and improves overall scalp and hair health. The formulation incorporates coconut oil, almond oil, hibiscus, amla, and brahmi, enhanced with Vitamin E and lavender essential oil. The final product was evaluated for physicochemical properties, stability, organoleptic characteristics. Results indicated a stable and aesthetically acceptable product suitable for topical application, showing promising results in hair nourishment and scalp conditioning.

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Herbal hair oil, amla, hibiscus, brahmi, hair growth, dandruff, natural formulation.

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