Volume 14 | Issue 5 |

 Abstract

Asthma is a heterogeneous, complex, chronic respiratory disorder, which is marked by variable obstructions of airflow, hyperresponsiveness of the airways, and the presence of persistent inflammation, which changes considerably in the lifespan. Its pathogenesis is complex with genetic predisposition, immune deregulation, and exposure to the environment, resulting in varying clinical phenotypes and endotypes. The purpose of the study is to combine the existing information on immunopathology of asthma, environmental allergens, and specific treatment approaches into an overall systems-based approach. The evidence-based approach adopted is a systems-oriented integrative review that will synthesize the recent literature on the subject, which concentrates on the molecular pathways, environmental determinants, and specific treatment modalities. The discussion identifies the presence of immune processes including Th2-mediated inflammation, cytokines signaling, and airway remodeling and the effects of environmental influences including allergens, pollution, and lifestyle factors. Moreover, the developments of precision medicine, such as biologic therapies and biomarker-based interventions are discussed in terms of their ability to positively influence disease outcomes. The results indicate that the endotype-driven and phenotype-specific therapeutic interventions can be of great benefit in asthma treatment. Finally, personalized and lifecycle-based approach is the key to optimizing the management of asthma, enhancing patient outcomes, and managing the variability of this complex disease.

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 Keywords

Asthma; Immunopathology; Environmental Triggers; Precision Medicine; Phenotypes; Endotypes; Systems Biology

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 Abstract

Digital Banking has transformed the banking sector by providing customers with fast, secure, and convenient financial services through digital platforms. It significantly impacts customer satisfaction by improving accessibility, reducing transaction time, and enhancing the overall banking experience through personalized and efficient services.

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Digital BankingCustomer SatisfactionService QualityFinancial Technology (FinTech).

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This paper will look at how the use of Theatre in Education (TIE) can be applied in secondary schools in Delhi based on the National Education Policy (NEP) 2020. Although the policy promotes the inclusion of experiential and arts based learning, its institutional implementation is still disproportional. The study applies an interdisciplinary paradigm of integrating critical pedagogy, applied theatre, experiential learning, and policy implementation theory in order to examine the level of stakeholder awareness, institutional practices, and the perceptions. Surveys were conducted on students, teachers, parents, and theatre practitioners of the city of Delhi to collect primary data. The results also show high perceived benefits of theatre-based pedagogy, especially in the improvement of communication, confidence, and socio-emotional learning. Nevertheless, there are still important implementation gaps that can be attributed to academic pressure, insufficient training of teachers, ineffective infrastructure and insufficient policy clarity. The analysis finds that the integration of theatre can be symbolic and not systematic. It concludes that policy practice gaps will be bridged only through organized curricular structures, institutional back up and sustained capacity building exercises

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 Keywords

Theatre in education, NEP 2020, experiential learning, arts-integrated learning, policy implementation, secondary education, Delhi.

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6.2 CLASS DIAGRAM The provided class diagram illustrates the core components and workflow of a Convolutional Neural Network (CNN) for image classification. The process begins with a dataset, divided into training and new data sets. The training data is fed into the CNN algorithm, which learns to recognize patterns and features within the images. This learning process results in the creation of a CNN model. When new data isintroduced, the trained CNN model processes it, extracting features and assigning class labels based on its learned knowledge. Ultimately, the predicted outcome, or classification, is generated for each new image, demonstrating the model's ability to accurately categorize unseen data. The provided class diagram outlines the fundamental steps involved in training and utilizing a Convolutional Neural Network (CNN) for image classification. The training dataset serves as the foundation for the CNN algorithm to learn intricate patterns and features within images. Once trained, the CNN model becomes adept at classifying new images by accurately assigning them to appropriate categories. This process showcases the power of CNNs in extracting meaningful information from visual data and making informed decisions based on learned patterns.

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6.2 CLASS DIAGRAM The provided class diagram illustrates the core components and workflow of a Convolutional Neural Network (CNN) for image classification. The process begins with a dataset, divided into training and new data sets. The training data is fed into the CNN algorithm, which learns to recognize patterns and features within the images. This learning process results in the creation of a CNN model. When new data isintroduced, the trained CNN model processes it, extracting features a

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Creating a single platform for managing Club and Event Activities on College Campuses is one of the primary goals of transforming colleges into digital institutions. Many colleges still use outdated manual methods for managing events which can lead to unorganized, disjointed systems to create, approve and track events. This survey will provide information about current systems available in the marketplace to Colleges and Universities utilizing automated event and club management systems, focusing on architecture / functionality/ scalability/limitations of various systems. This evaluation will also look at existing systems that utilize Role Based Access Control, Real Time Notification Systems, Automated Approval Process' and database driven Event Participation Tracking Mechanisms [1],[2],[4],[9],[10]. Based on our evaluation, we will also outline how modular each of these systems are; strategies to provide users with engaging experiences; and difficulties in integrating these systems within current College and University infrastructure. Additionally, we will focus on the benefits of having a single dashboard for Students, Club Leaders and Administrators to increase the transparency and efficiency of operations on college campuses. Our contributions include A Classifying System for Existing Systems; A Comparative Analysis of Implementation Techniques; A Verification of Research Gaps; Recognition of New Trends Such as Artificial Intelligence Driven Personalization [3],[8]; and Enhancement of Physical Security Solutions. Ultimately, through this research, we will provide higher education professionals with knowledge about the current state and future direction of centralized platforms for communicating campus information and managing campus events effectively.

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 Keywords

Campus Event Management System, Web-Based Application, Role-Based Access Control (RBAC), Automated Event Approval Workflow, Real-Time Notification System, College Club Management, RESTful API Architecture, Database-Driven Participation Management

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ABSTRACT: Students today handle large volumes of academic material such as PDFs, handwritten notes, assignments, and reference documents, which are often scattered across different folders and applications. Locating specific information inside large files becomes extremely time-consuming, especially during exam preparation. The lack of a unified system for organizing study resources and extracting relevant content creates unnecessary stress and reduces productivity. To address this challenge, this project introduces SmartStudy, an intelligent mobile application designed to organize subject-wise study materials and provide accurate responses based solely on the user's uploaded documents.SmartStudy allows students to select a subject and upload all related PDFs, notes, and assignments into a dedicated space. These materials are permanently stored within the application, ensuring that even if the original files are deleted from the device, they remain safely accessible. The system processes the uploaded content, separates topics automatically, and enables quick access through an AI-powered search feature. Users can simply type any question or keyword, and the app generates precise answers, summaries, or key points derived strictly from their own study materials. This ensures information that aligns with the student's syllabus, teacher instructions, and institutional requirements.By integrating document organization, topic extraction, intelligent search, and persistent storage, SmartStudy transforms scattered resources into a structured, easy-to-use digital learning system. The app reduces the time students spend searching through files and significantly enhances study efficiency. This project provides a practical and innovative solution to a real academic problem, making SmartStudy a reliable digital companion for students preparing for exams and assignments.

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 Keywords

Keywords:SmartStudy, Mobile Application, PDF Extraction, Intelligent Search, Topic Segmentation, AI-Based Learning, Multilingual Support, Academic Assistance System.

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ABSTRACT Rice is one of the most important crops in the world, feeding more than half of the global population. However, rice plants are highly vulnerable to diseases, and if these are not detected early, they can lead to serious crop losses. Traditionally, farmers identify diseases by visually inspecting leaves, but this process can be slow, inconsistent, and error-prone--especially in the early stages. To solve this problem, this work presents an automated and efficient system for detecting rice leaf diseases using deep learning. The model is built using a lightweight Convolutional Neural Network (CNN), specifically MobileNetV2, which is known for its speed and low computational requirements. The system is trained on a dataset containing three common rice diseases: Narrow Brown Spot, False Smut, and Leaf Smut. To improve performance, image preprocessing and data augmentation techniques are applied, allowing the model to handle variations in lighting, orientation, and background. In addition to predicting the disease, the system also provides treatment suggestions, making it more useful as a practical tool for farmers. The model achieves an accuracy of around 75-80%, with good precision, recall, and F1-score. Due to its lightweight design, it can run efficiently on devices with limited resources, such as smartphones. A simple web interface is also developed, enabling users to upload images and receive instant results. Overall, this system provides a fast, scalable, and practical solution for crop disease detection and has the potential to be extended to more diseases and real-time agricultural applications..

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 Keywords

Index Terms-- Deep Learning, MobileNetV2, Rice Disease Detection, CNN, Image Classification, Precision Agriculture, Decision Support System.

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The present study aimed to formulate and evaluate a polyherbal dusting powder as a topical antimicrobial agent for the management of minor skin infections and moisture-related skin conditions. The formulation was prepared using natural and pharmaceutical ingredients including talc, kaolin, starch, magnesium stearate, almond oil, and clove oil. Clove oil was incorporated for its potent antimicrobial and antifungal activity, while almond oil acted as an emollient and skin-conditioning agent. The dusting powder was prepared by simple mixing and trituration method followed by sieving to obtain a fine and uniform formulation. The prepared formulation was evaluated for organoleptic properties, pH, particle size, abrasiveness, bulk density, tapped density, angle of repose, Carr's index, Hausner ratio, moisture content, and antimicrobial activity using bread slices. The formulation showed satisfactory organoleptic characteristics with a smooth texture, pleasant odor, and non-gritty nature. The pH was found suitable for topical application. Antimicrobial studies demonstrated inhibition of microbial growth in the treated sample compared to the control, indicating effective antimicrobial activity. The study concluded that the formulated polyherbal dusting powder possesses good topical properties and promising antimicrobial potential, making it a safe, economical, and effective herbal formulation for topical use.

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 Keywords

Polyherbal dusting powder, antimicrobial activity, Clove oil, Almond oil, Topical formulation, Herbal formulation, Moisture absorption, Skin infections.

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Jewellery retail showrooms in the contemporary world, specifically in 2025, are significantly influenced by the fusion of sustainability, minimalism, and technological incorporation to improve spatial experience and business performance. The purpose of this research paper is to create an integrated design framework that incorporates all three key elements to improve the planning and execution of Jewellery retail showrooms. The study highlights the importance of integrating sustainable design, such as recycled materials, green lighting systems, and modular display systems, to improve spatial experience and business performance. The importance of integrating minimalistic design principles to create an uncluttered spatial experience is also discussed. Additionally, the incorporation of modern technologies, such as digital interfaces, smart security systems, and interactive display systems, is discussed to improve spatial experience and business performance. The study evaluates various strategies to create an optimized spatial experience, improve sustainability, and enhance business performance. The results of this study show that an eco-minimalistic approach to designing Jewellery retail showrooms, with the incorporation of modern technologies, can improve spatial experience, sustainability, and business performance. This paper contributes to the field of interior design and retail design by providing an approach to create future-ready Jewellery retail showrooms.

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 Keywords

Jewellery, Minimalism, Sustainability, Technology, Design

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The piston in an internal combustion (IC) engine is subjected to several forces before transmitting power to the crankshaft. The main objective of this study is to analyze the stress distribution and deformation of a diesel-CNG dual-fuel engine piston when exposed to the gas pressure generated during combustion. An aluminum alloy piston was selected for the analysis, and suitable design parameters were assumed to develop the piston geometry. The stress and deformation caused by the maximum combustion pressure were analyzed using FEA-based software. The boundary conditions considered different peak combustion pressures corresponding to various CNG substitution rates acting on the piston. The results reveal that the piston crown experiences the highest deformation, with a maximum value of 0.075 mm, while the maximum Equivalent [von-Mises] Stress is found to be approximately 300 MPa, when tested with zero CNG substitution and pure diesel used and the lowest deformation of 00.062mm at 80% CNG substitution rate with maximum Equivalent [von-Mises] Stress is found to be approximately 240 MPa.

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Piston Stress Analysis, Diesel-CNG Dual-Fuel Engine, Finite Element Analysis, CNG Substitution Rate

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