Volume 13 | Issue 12 |

 Abstract

Breast self-examination (BSE) is a simple, cost-effective method for early identification of breast abnormalities, especially important for young females. This study aimed to assess the knowledge and attitude regarding breast self-examination among adolescent girls in a selected school. A descriptive research design was adopted among 100 adolescent girls selected through simple random sampling. Data were collected using a structured knowledge questionnaire and a Likert-scale attitude rating scale. Findings revealed that 58% of participants had average knowledge, 23% had poor knowledge, and only 19% had good knowledge regarding BSE. In terms of attitude, 67% showed a favorable attitude, 28% moderately favorable, and 5% unfavorable attitude. The study highlights the need for early school-based breast health education to improve awareness and promote positive attitudes toward BSE practices among adolescent girls.

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 Keywords

Breast self-examination, Adolescent girls, Knowledge, Attitude, Breast Awareness

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The evolution of technology has transformed the landscape of financial transactions, steering consumers away from traditional cash-based systems toward digital payment platforms. This study explores the ongoing shift from conventional monetary methods to digital payment systems in India, with particular attention to consumer behavior, trust, accessibility, and digital literacy. The research investigates how mobile payment applications such as Google Pay, PhonePe, and Paytm are redefining financial interactions in both urban and semi-urban regions. Drawing from a primary survey conducted among 200 respondents in Thiruvarur district, the study identifies key factors driving digital payment adoption, including convenience, speed, security, and ease of use. Statistical tools such as weighted averages, chi-square tests, and percentage analysis were employed to interpret user responses. The findings reveal that while digital payments are gaining momentum, challenges like security concerns and lack of awareness persist among certain demographics. This paper provides valuable insights into the digital transformation of money and the emerging trends in India's fintech ecosystem.

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 Keywords

Digital Payments; Traditional Transactions; Consumer Behavior; Fintech; Mobile Wallets; Financial Inclusion; Technology Adoption

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Milk production is an essential component of India's agricultural farming system; despite the area's capacity for milk and dairy products, there is always a high demand for milk and milk products among the general public. From 128 million tonnes in 2011 to 463 million tonnes in 2040-41, milk output has surged. For many years, India has maintained its top spot in the production of milk. In India, the dairy industry is expanding at a 10% annual pace. However, no long-term studies have been conducted in the area to anticipate the volume of milk production. As a result, the purpose of this study The study's goal is to determine the best forecasting technique for milk production in order to have an impact on both future production sustainability and public policy. Secondary data were utilised in the study and were gathered from NDDB (1991 to 2022) and FAOSTAT (1961 to 2022). Autoregressive Integrated Moving Average (ARIMA) and Vector Autoregression (VAR) models were utilised after the stationarity of the data had been verified using the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF). According to the findings, ARIMA was shown to be a better model for (1, 1, 1) appropriate when using the SPSS programme to forecast milk. 463 million tonnes of milk are anticipated to be produced by 2041.

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ARIMA, Milk production, Vector Autoregression (VAR), Forecasting

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Early detection of Chronic Kidney Disease (CKD) plays a vital role in delaying disease progression and preventing complications. Serum creatinine (SCr), the conventional biomarker used in clinical practice, has limited sensitivity in early CKD due to non-renal influences such as muscle mass, age, gender, and dietary protein intake. Cystatin-C, an endogenous cysteine protease inhibitor produced at a constant rate by all nucleated cells, has emerged as a more sensitive and reliable biomarker closely correlated with glomerular filtration rate (GFR). This review evaluates the diagnostic sensitivity, specificity, predictive accuracy, and clinical utility of Cystatin-C compared with serum creatinine for early CKD detection. Result Contemporary evidence demonstrates that Cystatin-C consistently outperforms serum creatinine, showing higher sensitivity (80-93%) and specificity (75-90%) for identifying early-stage CKD. Cystatin-C-based eGFR or combined creatinine-Cystatin-C equations significantly reduce misclassification and detect renal impairment earlier. Conclusion Cystatin-C is a superior biomarker for identifying early reductions in kidney function, especially among populations with variable muscle mass such as the elderly, children, females, and chronically ill individuals. Incorporating Cystatin-C into routine kidney function testing is strongly recommended for improved early CKD detection. Keywords Cystatin-C; Serum Creatinine; Chronic Kidney Disease; Early CKD Detection; Glomerular Filtration Rate; eGFRcys; Kidney Biomarkers; Renal Function Assessment; Diagnostic Accuracy; Muscle Mass-Independent Biomarker.

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 Keywords

Cystatin-C; Serum Creatinine; Chronic Kidney Disease; Early CKD Detection; Glomerular Filtration Rate; eGFRcys; Kidney Biomarkers; Renal Function Assessment; Diagnostic Accuracy; Muscle Mass-Independent Biomarker.

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Abstract: Since Independence, the Indian judiciary, particularly the High Courts and the Supreme Court has played a proactive role in advancing gender justice through its decisions and initiatives. The Constitution of India, along with various laws enacted by Parliament, guarantees equal opportunities for women and safeguards them from discrimination and deprivation. While the executive is responsible for implementing these provisions, the judiciary has increasingly taken on the task of ensuring their effective enforcement. Additionally, several legal reforms have been introduced due to judicial interventions. Notable cases from Jharkhand, such as Laxmi Murmu v. State of Jharkhand and Shilpa Singh v. State of Jharkhand, highlight the judiciary's role in addressing gender-based violence and upholding women's rights. This paper examines and evaluates the impact of landmark judicial rulings concerning key legislative measures designed to enhance gender justice in India. Despite the existence of robust legal frameworks and judicial activism, data on critical issues such as rape, workplace sexual harassment, child marriage, domestic violence, and child abuse indicate a rising trend in such offenses. These findings suggest that legal measures alone are insufficient to bring about fundamental changes in the status of women in Indian society. While the judiciary has been instrumental in upholding women's rights, a comprehensive and multidimensional approach is necessary. Alongside legal reforms, efforts must be directed toward social, political, economic, cultural, and technological advancements. Only through such a holistic strategy can Indian women experience true empowerment and contribute equally to societal progress.

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Key Words: Gender justice, Indian judiciary, judicial activism, women's rights, legal reforms, constitutional safeguards, social empowerment

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ABSTRACT Decrease in hardware costs and advances in computer networking technologies have led to increased interest in the use of large-scale parallel and distributed computing systems. Distributed computing systems offer the potential for improved performance and resource sharing. In this paper we have made an overview ondistributed computing. In this paper we studied the difference between parallel and distributed computing,terminologies used in distributed computing, task allocation in distributed computing and performance parameters in distributed computing system, parallel distributed algorithm models, and advantages of distributed computing and scope of distributed computing.

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Distributed computing, execution time, heterogeneity, shared memory, throughput.

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Fasciola hepatica, a trematode parasite affecting ruminants worldwide, remains a major cause of hepatic pathology in goats. This review synthesizes research published from 2000 to 2025 focusing on histopathological lesions, diagnostic advances, and comparative pathology in goat fascioliasis. A total of 27 peer-reviewed studies from PubMed and ScienceDirect were analyzed, showing a consistent pattern of hepatic fibrosis, necrosis, bile-duct hyperplasia, and calcification. Quantitative trends indicate a steady rise in research output post-2015, reflecting growing interest in immunopathological and molecular aspects. Integration of histochemistry, immunohistochemistry, and molecular diagnostics has improved lesion characterization and host-parasite interaction understanding. Persistent knowledge gaps include molecular correlates of lesion severity and breed-specific resistance. The findings emphasize the importance of continuous surveillance and advanced diagnostic integration for effective fasciolosis control in goats.

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Fasciola hepatica, histopathology, hepatica lesion, fasciolosis, goat

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Steganography in digital images has emerged as a critical cybersecurity threat, enabling attackers to embed concealed commands, data leakage channels, or malicious payloads within seemingly harmless PNG and JPEG files. Unlike traditional encryption, steganography hides information at the pixel or frequency level, making visual inspection and conventional security tools ineffective. This project introduces a deep learning-driven steganalysis framework that integrates residual preprocessing techniques and advanced Convolutional Neural Network (CNN) architectures such as EfficientNet, ResNet, and DenseNet for robust detection of hidden content. Residual feature extraction enhances subtle noise artifacts caused by embedding processes, while CNN backbones learn discriminative spatial patterns for accurate classification of cover and stego images.

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Steganography Detection, CNN, Residual Preprocessing, EfficientNet, ResNet, DenseNet, Image Forensics, Deep Learning, Cybersecurity.

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Highway infrastructure plays a crucial role for national and regional economic growth, by making accurate investment by evaluating the essential. This study compares 27 road stretches in Meghalaya using four frameworks--Cost-Benefit Analysis (CBA), System Dynamics Modelling (SDM), HDM-4, and the Hybrid Annuity Model (HAM)--based on NPV, IRR and payback period. Results show that CBA and HDM-4 provide consistent, standards-aligned assessments of economic viability, while HAM offers strong financial stability under the PPP structure with balanced risk and reliable annuity returns. Although SDM provides dynamic insights, it tends to overestimate IRR and is less reliable for final decisions. Overall, the analysis identifies HAM as the most feasible and sustainable investment option, offering balanced economic performance, financial security, and a practical payback period of about 4-8 years.

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 Keywords

Highway Investment, Payback Period, Rate of Returns.

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Creative Commons Attribution 4.0 and The Open Definition

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An intelligent framework called the Smart Space with Emotion-Adaptive Music System was created to improve human-computer interaction by utilizing adaptive response and emotional awareness. The system recognizes and deciphers real-time facial expressions and emotions, including joy, sorrow, stress, and excitement, by combining computer vision and natural language processing (NLP) technologies. It provides a customized and engrossing auditory experience by dynamically choosing and modifying music in response to these emotional cues. By gradually learning from user behavior and preferences, the system continuously improves its suggestions, guaranteeing increased precision and emotional resonance. Strong security and privacy measures are also put in place to protect user information and guarantee clear consent at all times.This study demonstrates how emotion-aware AI can enhance emotional health, boost output, and build smart environments that can adapt to human emotions naturally.

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 Keywords

Emotion adaptive, Natural Language Processing, Music System, Computer vision

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Creative Commons Attribution 4.0 and The Open Definition