Volume 14 | Issue 4 |

 Abstract

Ruskin Bond is one of the most celebrated Indian writers known for his sensitive portrayal of childhood and his deep engagement with nature. His writings are marked by simplicity, warmth, and an intimate understanding of the emotional world of children. Having spent much of his early life in the Himalayan regions, Bond developed a close and lasting bond with the natural landscape, which continues to shape his literary imagination. His stories often unfold in small towns and hill stations, where nature is not merely a setting but a living presence. This paper explores the representation of childhood sensibilities in Bond's fiction, with particular emphasis on the relationship between children and nature. Through close textual analysis of selected works, the study examines how natural elements such as seasons, trees, animals, insects and landscapes actively shape the emotional and psychological experiences of child protagonists. It further analyses themes of friendship, love, separation, and loneliness, showing how these experiences are closely intertwined with the rhythms of the natural world. The paper argues that Bond's depiction of childhood is rooted in simplicity and authenticity, where nature serves as both companion and guide in the process of growing up. Ultimately, his fiction presents a nuanced understanding of childhood as a period of deep sensitivity, where the external environment reflects and nurtures the inner emotional life of the child.

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 Keywords

Childhood, Nature, Childhood Sensibilities, Ruskin Bond, Human-Nature Relationship, Friendship, Coming of Age, Himalayan Landscape, Eco-criticism

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Investment advisory services are essential for helping investors make informed financial decisions in a complex and changing market. In India, the rapid growth of capital markets, regulatory changes by the Securities and Exchange Board of India (SEBI), and increased financial awareness among retail investors have greatly expanded the need for professional advisory services. This study offers a practical approach to investment advisory in India, focusing on ICICI Securities, a leading financial services provider in the country. The research looks at the advisory framework used by ICICI Securities. It covers client profiling, risk assessment, asset allocation strategies, portfolio diversification, and the use of technology-based platforms for investment recommendations. It also reviews the variety of products available, such as equity, mutual funds, derivatives, insurance, and wealth management solutions. The study shows how ICICI Securities combines research insights, digital tools, and personalized advisory services to meet the diverse needs of investors.

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Investment advisory services, Securities and Exchange Board of India (SEBI), ICICI Securities, portfolio diversification, Asset Allocation Strategy.

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This study examines the impact of group behaviour on employee productivity in manufacturing units, with special reference to Jeya Enterprises. Group behaviour, including communication, leadership, cooperation, trust, and conflict management, plays a significant role in shaping employee performance. The research adopts a descriptive and quantitative approach, collecting primary data through structured questionnaires from employees. Statistical tools such as percentage analysis, mean score, and correlation are used to analyze the data.

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 Keywords

Group behaviour, employee productivity, teamwork, communication, manufacturing units, cooperation, conflict management

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Deepfake technology has advanced rapidly in recent years, making it increasingly difficult to distinguish between real and manipulated media. This paper presents an efficient and explainable deepfake detection system that leverages facial artifact analysis and deep learning techniques. The proposed system integrates spatial feature extraction using a pretrained Xception Convolutional Neural Network (CNN) with fine-grained facial landmark analysis using MediaPipe FaceMesh. Video inputs are processed through an optimized frame extraction strategy, and facial regions are isolated using MTCNN. The model is trained on FaceForensics++ and Celeb-DF datasets and evaluated on the DFDC dataset to assess generalization capability. Experimental results demonstrate strong performance with high accuracy and robustness across datasets. Additionally, explainability is incorporated through probability-based outputs and visualization techniques such as Grad-CAM. The proposed approach effectively identifies deepfake content and provides interpretable results, making it suitable for real-world forensic applications.

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 Keywords

Deepfake Detection, Facial Artifact Analysis, Convolutional Neural Network, MediaPipe FaceMesh, Explainable AI, Grad-CAM, MTCNN, Video Forensics, FACEFORENSIC++, DFDC,CELEBP-DF,XECPTION NET.

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Now-a-days, there has been a significant increase in the use of fibres in concrete for improving its properties such as tensile strength and ductility. Now-a-days polypropylene fibre, etc. use while preparing concrete. polypropylene fibre has the advantages of having higher tensile strength and compressive strength, thus reducing the loss of damage during fire accident of concrete structures. In this investigation polypropylene fibre are added to the concrete by volume fraction to determine its strength characteristics. Determination of compressive, split tensile and flexural strength of concrete. Polypropylene is a synthetic hydrocarbon polymer, the fiber of which is made using extrusion processes by hot drawing the material through a die. Its use enables reliable and effective utilization of intrinsic tensile and flexural strength of the material along with significant reduction of plastic shrinkage cracking and minimizing of thermal cracking. Comparison of the strength performance of conventional concrete was made. This is experimental study done by using polypropylene fibres without flyash in concrete and conclusion from their various strength parameters finding out the optimum quantity of polypropylene fibers required to achieve the maximum compressive strength for M40 grade concrete. From the exhaustive and extensive experimental work it was found that with increase in polypropylene fiber content in concrete there was a tremendous increase in compressive strength. The effect of the addition of polypropylene fibers on the mechanical properties of normal strength concrete is studied. The polypropylene fibers were added at concentration of 0.3, 0.4, 0.5 and 0.6 % by volume. Compression, pullout and bending tests were carried out to determine the mechanical properties such as maximum compressive strength, splitting strength. On the basis of the experimental results, it can be concluded that, ductility of concrete significantly increased and maximum compressive strength slightly increased with increasing the content of polyproplylene fibers materials. Further increase of polypropylene fibers (higher values than 0.5 vol. %) did not increase the ultimate bond strength, but it provided much more ductile bond behaviour.

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Concrete, Strength, polypropylene fibre, durability

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The research field utilizes cancer cell lines that originate from tumors to investigate cancerous processes and test new treatment methods. The TP53 gene functions as a crucial genetic element because it governs three fundamental cellular processes, which include cell cycle management, genomic restoration, and programmed cell death. Researchers must establish the TP53 mutation status of their samples because it directly affects their ability to obtain trustworthy experimental results. Researchers propose a machine learning technique to predict and assess TP53 mutation status within human cancer cell lines. The UMD TP53 database provides data which undergoes preprocessing to maintain both consistency and accuracy. The Logistic Regression model functions as a supervised classification system, which enables researchers to distinguish between mutant and wild-type cell lines based on their mutation characteristics. The proposed system combines all necessary components for data preprocessing and feature extraction and model training and evaluation into a unified operational process. The experimental results demonstrate how the model successfully detects mutation patterns while the existing datasets contain verification errors. The study demonstrates that cancer research needs validated mutation data to conduct reliable research while machine learning methods improve this reliability.

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TP53, machine learning, cancer cell lines,

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 Abstract

Background and Objective: Chronic obstructive pulmonary disease is a diverse lung disease defined by chronic respiratory symptoms (dyspnea, cough, expectoration and /or excerbations) due to abnormalities of the airways (bronchitis, bronchiolitis) and/or alveoli (emphysema) that cause persistent, typically progressive, airflow obstruction There are airway clearance techniques like resistive respiratory device and threshold inspiratory muscle training techniques have been proposed as an adjunct to conventional therapy to treat COPD. Both the techniques have been proved in increasing inspiratory muscle strength and quality of life in COPD and the literature is limited on their comparison Hence need of the study arises. Methods: A quasi-experimental study design. 80 subject with FEV1/FVC<70% with clinical diagnosis of COPD were randomly allocated into two groups. In Group -A subjects (n=40) were treated with Resistive respiratory muscle trainer (breather) device and conventional physiotherapy training whereas in Group-B subjects (n=40) threshold inspiratory muscle training and conventional physiotherapy. The participants were given intervention thrice a week for 6 weeks. The Outcomes of this intervention was measured in terms of maximum inspiratory mouth pressure and st. George respiratory questionnaire. Results: Independent 't' test was used to compare the mean significance difference between continuous variables Paired 't' test was used to assess the Statistical significance difference between pre and post test scores. Statistical analysis of data revealed that within the group comparison both groups showed significant improvement in all parameters. Where as in between group comparison breather Device technique showed better improvement compared to threshold inspiratory muscle trainer. Conclusion: After 6 weeks of interventions both resistive respiratory muscle trainer and threshold inspiratory muscle trainer were shown statistically significant in improving inspiratory muscle strength and quality of life. However, resistive respiratory muscle trainer showed greater improvement in pi-max and SGRQ. Hence, we conclude that breather is a convenient, easy to use and Safe, in improving inspiratory muscle strength along with quality of life in subjects with COPD.

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 Keywords

Chronic obstructive pulmonary disease, inspiratory muscle strength, quality of life, maximum inspiratory mouth pressure, St. George respiratory questionnaire, breather device, threshold device.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Students often face academic challenges and social isolation due to a lack of proficiency in the medium of instruction in multilingual education environments [1],[5]. In the existing model, there is a Traditional language support model where they separate such students into particular dedicated language classrooms, which results in a delay of subject learning and difficulty in inclusive participation .To address this problem, we propose this project, An AI-Based Real-Time multilingual Class room assistance System which enables instant translation of instructions said by the teacher within the mainstream classrooms. This proposed system of the project integrates Artificial Intelligence (AI), Automatic Speech Recognition (ASR), and Natural Language Processing (NLP) to give instant translation of the teacher's speech into live text, and it also translates into multiple target languages in real time. Here, in this proposed system, follows a client-server architecture with role-based access for students and teachers. The Teacher speaks through a microphone-enabled interface, while students register on the web page and select their preferred language. In this, we proposed an AI engine that processes the spoken input, does the speech-to-text conversion, and applies neural machine translation to generate multilingual outputs, and gets instantly displayed on the devices of students using real time communication protocols.

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 Keywords

Artificial Intelligence (AI), Inclusive Education, Multilingual Classrooms ,Natural Language Processing (NLP), Real-Time Translation, Speech Recognition (ASR).

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The study adopts a descriptive research design and is based on primary data collected from 135 respondents using a structured questionnaire through convenience sampling. Statistical tools such as percentage analysis, weighted average method, correlation, chi-square test, Kruskal-Wallis test, and Mann-Whitney U test are applied for analysis.

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 Keywords

Digital Platforms, Bio Bags, Consumer Behaviour, Sustainable Marketing, Awareness

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The rapid growth of digital banking systems has led to an increase in fraudulent financial transactions, posing a serious threat to both customers and financial institutions. This paper presents a machine learning-based approach for detecting fraudulent transactions in banking data. The system utilizes various classification algorithms to analyze transaction patterns and identify anomalies that indicate potential fraud. The dataset is preprocessed to handle missing values, normalize features, and improve model performance. Techniques such as Logistic Regression, Decision Trees, and Random Forest are used to classify transactions as legitimate or fraudulent. The proposed model achieves high accuracy and precision, enabling early detection and prevention of fraud. The system helps financial institutions minimize financial losses and enhance security by providing a reliable and automated fraud detection mechanism.

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 Keywords

Machine Learning, Fraud Detection, Banking Security, Classification Algorithms, Data Analysis

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Creative Commons Attribution 4.0 and The Open Definition