Volume 14 | Issue 4

 Abstract

Colon cancer is one of the most life- threaten- ing and highly spreadable cancers. The old technologies and methods used for identifying colon cancer were done by doctors using scan images or histopathological images, and it needs expertise in the field to identify the cancer, which may take hours or days. Some may even result in errors, leading to delayed diagnosis, and some may even miss early- stage detection. To reduce these problems, we have created a website that can find the cancer and its percentage in an instant, and to obtain this, we use a CNN (Convolutional Neural Network), which helps in extracting the spatial and needed features from scan images or histopathological images. The image pro- cessing technique includes resizing t he image, noise removal, normalisation, and data augmentation. Then the model will be trained to detect whether the image is cancer- ous or non-cancerous, and the percentage of cancer.

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 Keywords

Colon Cancer Detection, Colorectal Cancer, Deep Learning, Convolutional Neural Networks (CNN), Medical Image Processing, Histopathology Images, Colonoscopy Images, Image Classification, Computer-Aided Diagnosis, Early Cancer Detection, Artificial Intelligence in Healthcare.

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Agricultural modernization encompasses the adoption of improved technologies, mechanized farm equipment, micro-irrigation systems, high-yielding variety (HYV) seeds, and institutional credit mechanisms to enhance farm productivity and farmer income. Kolhapur district of Maharashtra, characterised by fertile black and laterite soils, abundant river networks, and a dominant sugarcane-agro-industrial complex, presents a compelling case for studying the economic impact of modernization at the district level. The district has witnessed a measurable growth in area under cultivation from 250,000 ha in 2018 to 288,000 ha in 2022, while food grain production rose from 1.2 million to 1.58 million tonnes during the same period. Irrigation coverage expanded from 60% to 80%, and aggregate farmer income grew from INR3,500 crore to INR5,500 crore. Sugarcane, the dominant cash crop, demonstrated a yield surge from 27 MT per acre under traditional flood irrigation to 55-60 MT per acre under automated drip irrigation, as documented from the Karbharwadi model village in Karveer taluka. Drawing entirely on secondary data from official Government of Maharashtra records, the NABARD Potential Linked Credit Plan for Kolhapur (2023-24), the Ministry of Agriculture and Farmers Welfare Annual Report (2024-25), and peer-reviewed journal articles, this paper evaluates five dimensions of agricultural modernization: irrigation expansion, mechanization, credit access, crop diversification, and government scheme penetration. The findings affirm a strong positive relationship between technology adoption and farmer income, while identifying persistent structural constraints, including land fragmentation, smallholder credit gaps, and post-harvest infrastructure deficits.

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Agricultural Modernization, Kolhapur District, Farmer Income, Sugarcane, Drip Irrigation, NABARD, Maharashtra, Micro-irrigation, High-Yielding Varieties.

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Jaundice is a caused by increased level of bile pigments, typically bilirubin and its conjugates, characterized by yellow discoloration of eyes and skin. In this article, metabolism of bilirubin, types, causes and patho-physiology of jaundice, clinical symptoms, investigations and management of jaundice with totality of symptoms in homoeopathy giving it a holistic approach has been reviewed.

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Jaundice, Holistic, Homoeopathy, Individualization, Totality of symptoms

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Obesity is a modern lifestyle disease caused due to excessive accumulation of fat in the body occurs when BMI is >= 25 in a person according to his/her age, sex, height, weight, or often considered as an important risk factor for the development of diabetes, non-alcoholic fatty liver disease, hypertension. Obesity is a major health concern because of its increasing prevalence. This article describes causes clinical classification, types complications, management of obesity along with review of homoeopathic medicines indicated for obesity,

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Obesity, Fat metabolism, Homoeopathic Medicines, Non - Alcoholic Fatty Liver Disease.

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ABSTRACT Background: Chronic bronchitis is a major component of Chronic Obstructive Pulmonary Disease (COPD) and is strongly associated with long-term smoking. Smoking cessation is the most effective intervention to slow disease progression. However, knowledge and attitude toward smoking cessation among patients remain inadequate in many settings. Objectives: 1. To assess the knowledge regarding smoking cessation among chronic bronchitis patients. 2. To assess the attitude toward smoking cessation among chronic bronchitis patients. 3. To determine the association between knowledge and attitude scores with selected demographic variables. Methods: A descriptive cross-sectional study was conducted among 100 chronic bronchitis patients in selected hospitals of Indore, Madhya Pradesh. A structured knowledge questionnaire and Likert attitude scale were used. Data were analyzed using descriptive and inferential statistics. Results: The findings revealed that 58% of patients had moderate knowledge, 28% had inadequate knowledge, and 14% had adequate knowledge. Regarding attitude, 62% showed a favorable attitude, 25% moderately favorable, and 13% unfavorable attitude. A significant association was found between knowledge and education level (p < 0.05). Conclusion: The study concludes that although patients have a moderately favorable attitude toward smoking cessation, knowledge levels remain insufficient. Structured educational interventions are recommended.

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Keywords: Chronic bronchitis, Smoking cessation, Knowledge, Attitude, COPD

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Background: Pittaj Mukhapaka is a commonly encountered inflammatory and ulcerative condition of the oral cavity, characterized by burning sensation, pain, altered taste, and ulceration. Ayurveda describes it as a Pittaja Nanatmaja and Rakta Pradoshaja Vikara. Although several Ayurvedic formulations and local therapies have been studied for Mukhapaka, limited evidence exists comparing classical Ayurvedic Gandusha therapy with standard modern topical agents. Objective: To evaluate and compare the clinical efficacy of Triphaladi Kashaya Gandusha and Tannic Acid-Choline Salicylate Gel local application in the management of Pittaj Mukhapaka. Methodology: A randomized controlled clinical trial was conducted on 60 patients diagnosed with Pittaj Mukhapaka, divided equally into two groups. Group A received Triphaladi Kashaya Gandusha, while Group B received Tannic Acid- Choline Salicylate Gel for 5 days. Assessment was done using subjective and objective parameters on Day 1, Day 3, and Day 5. Statistical analysis was performed using paired and unpaired tests. Results: - Both groups showed statistically significant improvement (p < 0.05) in all parameters. Group A demonstrated higher percentage relief in Asya Daha, Asya Ruja, Asya Vairasya, and number of Vrana compared to Group B. Conclusion: Triphaladi Kashaya Gandusha showed superior clinical efficacy compared to Tannic Acid-Choline Salicylate Gel in the management of Pittaj Mukhapaka, with no adverse effects observed.

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Gandusha; Oral ulcers; Pittaj Mukhapaka; Triphaladi Kashaya.

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A Product Rating System plays a crucial role in helping users make informed purchasing decisions in modern e-commerce platforms. Traditional rating systems often rely on simple averaging methods, which fail to capture complex user preferences and product characteristics

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Product Rating System, Deep Learning, Recommendation System, Sentiment Analysis, Rating Prediction

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Keywords: Chronic bronchitis, educational intervention, self-care, prevention, adults.

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The rapid evolution of Artificial Intelligence (AI) and mobile technologies has significantly reshaped the dynamics of English communication and language education. This research paper examines how digital environments are transforming linguistic practices, learning methodologies, and cultural frameworks associated with English. The study moves beyond the conventional perspective of technology as a neutral tool and instead conceptualizes it as an active force that influences communication patterns and educational structures. Using a qualitative and interpretive approach, the study explores key developments such as multimodal communication, AI-driven learning platforms, and smartphone-based linguistic interactions. These innovations have enhanced accessibility, flexibility, and learner autonomy, enabling users to engage with English beyond traditional classroom settings. However, the research also highlights critical concerns, including the decline of formal language structures, overdependence on automated systems, and reduced engagement with deep reading and analytical writing. The findings suggest that English is increasingly becoming a flexible, context-driven language shaped by digital interactions and global cultural exchanges. The study concludes that educational systems must adopt a balanced approach that integrates technological advancements while preserving critical thinking, linguistic accuracy, and cultural diversity. Such an approach is essential to ensure meaningful and sustainable language learning in the digital age.

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Digital Communication, Artificial Intelligence, English Language Learning, Mobile Learning, Cultural Transformation, Linguistic Practices

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Fiber Reinforced Concrete, Fly Ash, Steel Fiber, Compressive Strength, Sustainable Concrete.

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Offline signature verification is an effective biometric authentication method with widespread applications in areas including finance, law, and security. However, because of variations in the way that each person writes, as well as the existence of highly skilled forgeries, distinguishing real from false signatures can be very difficult. As a result, a number of researchers have proposed various methods for investigating the validity of signatures by applying principles of image processing and machine learning. Typically, researchers will preprocess the image of the signature, extract features related to it, and then classify these features to determine if a signature is either real or false. Historically, researchers have used many different methods to accomplish signature verification, including Support Vector Machines, Artificial Neural Networks, Hidden Markov Models, and Dynamic Time Warping, as well as more recently developing sophisticated detection models using deep learning architectures like Convolutional Neural Networks to improve accuracy. The purpose of this paper is to provide a survey of the current methods for offline signature verification to detail the advantages and disadvantages of each method. In addition, by comparing the strengths and weaknesses of their methodologies, researchers and practitioners can gain insight into what types of improvements can be made to signature verification systems in order to enhance their accuracy and dependability.

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Signature verification, Forgery detection, Biometrics, Image processing, Machine learning.

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Adolescents' psychological adjustment and overall well-being are influenced by attachment relationships and coping mechanisms. Due to being impacted by things such as parental deployment, frequent relocation, and parents being temporarily separated from them, children of defence personnel are more frequently thought to be at higher psychological risk than other children. Despite these assumptions, empirical research does not support this assumption with inconsistent findings. Therefore, the purpose of this study was to investigate attachment relationships, coping mechanisms, and psychological well-being among adolescents from both civilian and defence families. Quantitative cross-sectional data (comparing two groups of children) were collected. The sample included 30 children of defence personnel compared to 30 civilians (aged 14 - 18). The samples were compared using independent sample t-tests on the following standardized measures: Attachment Style, Brief COPE, and Psychological Well-Being (PWI) measures. No statistically significant differences were found between civilian versus defence personnel children regarding attachment, coping mechanisms, or psychological well-being. Thus, the findings suggest that a parent's occupational background does not solely determine the emotional adjustment of adolescents. This research highlights the role of familial and social supports in promoting adolescent well-being.

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attachment style, coping mechanisms, psychological well-being, adolescents, defence families.

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Physical laws, Principles, Physical Expressions, Mathematical Formulation.

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UniAccess is a low-cost, multi-modal accessibility assistant that enhances digital interaction for users with physical, motor, and speech impairments. It integrates eye-tracking, voice commands, and hand gesture recognition into a single platform, enabling seamless mode switching. Using technologies like OpenCV, MediaPipe, and SpeechRecognition, it allows real-time, hands-free control, improving accessibility, flexibility, and user independence.

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eye-tracking, voice commands, and hand gestures

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Developing an effective model to identify uncertainties in real-world situations has been challenging due to incomplete, inconsistent, or ambiguous data. This research paper presents a new framework (FPNSM) basedon a five-component membership structure that extends current neutrosophic soft matrixes by enhancing and/or increasing uncertainty breakdown into levels of truth, contradiction, uncertainty, hesitation or falsity; enables users to create a more detailed and dynamic description of an undetermined (uncertain) piece of data. The FPNSM is developed by combining three theoretical components (fuzzy sets, neutrosophic sets and soft set theory). It systematically defines the matrix structure, fundamental operations, and applicable properties of the various algebraic structures associated with the FPNSM. It provides an evaluative basis through the establishment of score/accuracy functions that allow an evaluator to rank their alternatives in a variety of uncertain, dynamic environments. A decision algorithm based on the FPNSM is provided to assist in making decisions based on multiple criteria. In addition, the effectiveness of the FPNSM methodology has been demonstrated through a case study; therefore, this research demonstrates how using the FPNSM can enhance the precision of the output produced when evaluating alternative options relative to an objectively and systematically determined standard of performance compared with existing processes. Subsequently, this research represents an important advancement in uncertainty modeling and provides an avenue for further research into the fields of decision support systems, engineering applications, and data analysis under variable/complex conditions.

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 Keywords

soft set, Pentapartitioned neutrosophic soft set, fuzzy pentapartitioned neutrosophic soft set, fuzzy pentapartitioned neutrosophic soft matrix

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This work introduces the conceptual design of a RAG Based Learning Management System that harnesses semantic PDF analysis, vector-indexed storage, and intelligent module synthesis to offer each student a tailored study experience. Students supply two PDF inputs-- a set of Previous Year Questions (PYQ) and subject-specific study notes--which the system tokenises, chunks, and encodes into a persistent vector store through dense semantic embeddings. A Retrieval-Augmented Generation pipeline driven by the Gemini 2.5 large language model then cross-references retrieved chunks to produce cohesive study modules, each bundling curated YouTube video links, concise AI-drafted revision summaries, time-bounded MCQ assessments, and an interactive progress dashboard. A document-grounded conversational agent complements these modules by letting learners pose free-form questions against their own uploaded content. The overall stack pairs a FastAPI service layer with a React SPA presentation tier built with Vite and the YouTube Data API to yield a modular, scalable digital learning environment. Upon deployment, the system is anticipated to cut study-preparation overhead substantially while broadening syllabus coverage and sustaining higher learner engagement relative to conventional static platforms.

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Retrieval-Augmented Generation (RAG), Personalized Learning, Learning Management Systems (LMS), Vector Databases, Semantic Embeddings, PDF Analysis, Adaptive Learning, Large Language Models (LLMs), FastAPI, React.js, Gemini API.

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Object detection is an important issue in computer vision. It enables computers to find objects in images and video streams automatically. This capability is crucial for many applications, including surveillance systems, self-driving cars, medical imaging, and automation. Traditionally, object detection relies on complex processes that involve proposing objects, extracting features, and classifying them. These processes can be resource-intensive. Recently, the field has progressed with the introduction of single-stage object detectors like YOLO (You Only Look Once). These detectors have significantly increased the speed of object detection while keeping accuracy high. This paper introduces a new object detection framework called VisionX. VisionX is a web-based system that uses deep learning object detectors and modern web technologies. Its goal is to create a unified framework for various object detection applications. The framework uses YOLOv8 for object detection. It supports multiple input sources, including images, video streams, and webcam feeds. VisionX is built with React for the frontend and Flask for the backend. It includes key features such as object model selection, dataset management, real-time detection, filtering objects based on confidence levels, and identifying suspicious objects for security purposes. The system processes input data through a series of steps, including data preprocessing, object detection with YOLOv8, filtering results, and visualizing the objects. Experimental results indicate that this object detection framework is effective in terms of accuracy and speed. It effectively connects machine learning object detectors with user applications. VisionX can be applied in various scenarios, such as surveillance systems, smart object monitoring, and AI-driven automation.

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Object Detection, YOLOv8, Computer Vision, Deep Learning, Real-Time Detection, React, Flask, Web-Based System, Surveillance Systems, Machine Learning.

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This study aimed to compare the physical and physiological characteristics of youth football players aged 15-17 years from Kerala and Lakshadweep. A total of 200 male players (100 from each region) participated in this cross-sectional study. Anthropometric variables, body composition, physical performance (agility, sprint, power, and flexibility), and physiological capacities (intermittent endurance and aerobic fitness) were assessed using standardized field-based tests. Independent samples t-tests were used to determine differences between groups. The results revealed no significant differences in anthropometric characteristics between the groups. However, Kerala players demonstrated significantly better performance in agility, linear sprint, curve sprint, flexibility, and intermittent endurance. In contrast, Lakshadweep players exhibited significantly higher aerobic capacity (VO?max). These findings suggest that while body composition remains comparable, performance-related attributes are influenced by region-specific factors such as training exposure and environmental conditions. The study highlights the importance of targeted training interventions to optimize performance in youth football players.

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Football, Agility, Sprint, VO2max

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Abstract: Banaphul is a renowned figure in the landscape of 20th-century Bengali literature. Although he is primarily recognized for his contributions to fiction, he was equally a successful artist in the realm of dramatic literature. 'Dashabhan' (1944) is a collection comprising ten of his one-act plays. From this anthology, we have selected three plays--'ShikKabab', 'Lehya', and 'Jal'--for the purpose of this analysis. In the play 'ShikKabab', the playwright vividly portrays the inner anguish of women within the patriarchal social structure of that era. Through the character of Soudamini, the dramatist depicts the attitude of certain hedonistic men toward the women of that time. Employing the metaphor of the dish Shik Kabab, he successfully encapsulates--within the concise scope of a one-act play--the moral degradation of men who lust after the female body like predatory beasts. The characters--the Zamindar, his sycophant Pannalal, and Jibandhan--serve as representatives of that very society. In the second play, 'Lehya', he presents a tableau of a social reality where young people are not required to demonstrate their competence to secure employment; rather, mere sycophancy toward leaders occupying high positions is sufficient to achieve success. Job seekers manage to obtain appointments--specifically for the post of Private Secretary--by merely "licking the boots" of those in power, without offering any proof of their actual qualifications. Here, Banaphul highlights the plight of educated Bengali youths--both male and female--residing outside Bengal, specifically in the region of Bihar. In the third play, 'Jol', he depicts the communal conflicts prevalent in colonial India in a novel and unique style. Through a scientific lens, he portrays this dialectical backdrop using the metaphor of hydrogen and oxygen atoms. This conflict, in essence, serves as a microcosm of the discord between the Hindu and Muslim communities. At the conclusion of the play, the dramatist envisions a union between the two communities--a reconciliation akin to the scientific process wherein hydrogen and oxygen atoms combine to form the new compound: water. This research paper will explore how the multifaceted nature of contemporary social reality is reflected in these plays.

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 Keywords

Keywords: One-act play, social realism, 'Shikkabab', women's inner anguish, 'Lehya', unemployment problem, 'Jol', communal conflict.

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Satire, Social Commentary, American culture, Conformity, Individuality

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