Volume 13 | Issue 4 |

 Abstract

Afghanistan Mein Bharat Ki 'Soft Power' Ranniti Aur Pakistan Ki Vifalta

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Afghanistan Mein Bharat Ki 'Soft Power' Ranniti Aur Pakistan Ki Vifalta

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BACKGROUND: Tuberculosis is specific infectious disease caused by Mycobacterium tuberculosis. The disease primarily affects the lungs and causes pulmonary tuberculosis. It can also affect other body parts such as intestine,meninges,bones and joints, lymph gland,skin and other body parts.DOTS remain central to public health approach to tuberculosis control, which is now presented as Stop Tuberculosis strategy to ensure cure by providing the most effective medicine and confirming that it is taken. It is only strategy, which has been documented to be effective worldwide on a programme basis. ASHA workers are designated as DOTS providers, they go house to provide the DOTS medicines to the community peoples. OBJECTIVES: The study aims to assess the effectiveness of Planned teaching Programme on level of the knowledge regarding DOTS therapy among ASHA workers. STUDY DESIGN AND METHODOLOGY: For this study a Pre -experimental design was selected with non prabability purposive sampling tecnique. Data was collected from 200 ASHA workers of Primary Health Centre,Misrod Bhopal, Madhyapradesh .Tool consists of part -I sociodemographic Variables and Part -II consists of knowledge questionnaire collecetd data was analyzed by descriptive and inferential statistics. The difference between the Pre-test and Post -test mean knowledge score of ASHA workers regardig DOTS therapy was statistically significant. CONCLUSION: It concluded that Planned Teaching Programme (PTP) was effective in enhancing the knowledge of ASHA workers regarding DOTS therapy.

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tuberculosis, mycobacterium tuberculosis, pulmonary tuberculosis, dots, public health, asha workers, planned teaching programme, knowledge assessment, primary health centre, bhopal, madhyapradesh, pre-experimental design, non-probability sampling, knowledge questionnaire, statistical significance

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Road maintenance is a critical aspect of infrastructure management to ensure safety and efficiency in transportation networks. Traditional manual methods of detecting road cracks are labor-intensive, time-consuming, and prone to human error. To address these challenges, this study proposes an automated road crack detection system leveraging advanced image processing and deep learning techniques, specifically Convolutional Neural Networks (CNNs). The workflow includes collecting road surface images, preprocessing through resizing, normalization, and data augmentation, and training a CNN-based model for crack detection. The model is fine-tuned using hyperparameter optimization and validated for generalization to unseen data. Once deployed, the system performs real-time crack detection, evaluates crack severity, and generates comprehensive reports. The detected cracks are stored in a database to facilitate maintenance planning, prioritization, and repair scheduling. This automated approach significantly improves detection accuracy, reduces processing time, and enables scalable road infrastructure management. The proposed system demonstrates the potential to enhance road safety and optimize maintenance strategies through intelligent and efficient crack detection mechanisms.

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Road Crack Detection, Image Processing, Deep Learning, Convolutional Neural Networks (CNNs), Machine Learning, Surface Defects, Edge Detection

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Technology is seen as an advancement to reduce the burden. Digitalization is the trend of the era. Day to day work in every area of work is not only enabling the working crowd to perform their work easier but also making results more accurate and reliable unlike the traditional process. This process has been taken over by the present digitalization where many software applications are in use to make the process faster and more efficient in contrast to traditional decision making which involve long process and many panels of discussion to come up with the best decision. Digitization leverages technologies and digital tools to enhance or redefine business processes and models. As technology continues to shape the workplace, employers are adopting strategic approaches to ensure the effective integration of new tools to make decisions more effective without much affecting the finance of the business. Through an analysis of current trends this article provides insight into how various digital tools are contributing to strategic decision-making process of the management. how it can contribute to more inclusive and sustainable job creation. The aim of this article is to figure out how digital tools are playing a pivotal role in decision making process of the management in recent years and has brought a tremendous change in the Business scenarios.

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Digitalization, Decision making, Digital tools, Management

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Adolescence is a time of increased vulnerability to mental health problems, including depression, anxiety, and peer pressure. Many adolescents have difficulty expressing their emotions effectively, which leads to low self-esteem, relationship problems, and low self-esteem. This systematic review aimed to examine the effectiveness of art therapy in improving adolescent mental health. The PICOTS (Population, Intervention, Comparison, Outcome, Time, and Setting) framework guided the identification of relevant research studies. Results from the American Art Therapy Association show that art therapy has a positive effect on overall mental health; regardless of previous art experience. Art therapy has shown promising results in treating a variety of mental health issues. Future research should examine the long-term effectiveness of art therapy for specific mental health diagnoses, examine its integration into treatment plans and educational settings, and evaluate its cost-effectiveness. Art therapy offers a valuable non-verbal therapeutic approach for adolescents. It provides a safe and supportive space for emotional expression, self-disclosure, and the development of coping mechanisms.

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Art Therapy, Anxiety, Depression, Self-Expression, Colour, Emotion, Intervention, Mental Health, Therapy, Adolescents

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Leukemia, also known as blood cancer is a dangerous disease that arises in the bone marrow and overproduces malformed white blood cells. These cells make blood unhealthy and weaken body's ability to fight with infection. Leukemia is categorized based on speed of progression [Acute and Chronic] and the types of white blood cell affected [lymphocytic or myeloid]. Due to high risk factor, it requires accurate and timely diagnosis for effective treatment. Current advancements in Machine learning (ML) have revealed promising diagnostic results. This study aims to provides a complete overview of different Machine learning and Deep learning Techniques applied for the diagnosis of leukemia, highlighting the parameters like accuracy and number of features extracted, using different segmentation techniques.The paper explores the application of various Machine Learning (ML) algorithms, with Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), and Image Processing techniques, demonstrating outstanding results in a specific area. These algorithms have shown outstanding success in tasks like image classification, object detection, and medical image analysis. Our review highlights the capability of ML in enhancing leukemia diagnosis accuracy, reducing diagnosis time, and improving patient outcomes

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Leukemia, image processing, Machine learning, SVM.

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In today's global society, skilled cross-cultural communication is crucial, as language connects individuals, businesses, and nations, necessitating efficient translation systems. This review analyzes AI-driven translation, discussing advancements, challenges, and ethical considerations while exploring key debates, methodologies, and unresolved questions in the field. It highlights innovations and limitations in AI translation, emphasizing its impact on multilingual communication and cultural understanding. Ensuring accuracy, adaptability, and inclusivity in machine translation is essential for ethical AI development. The study underscores the importance of responsible AI practices, advocating for transparency and fairness in translation technologies. Future research aims to enhance cross-lingual adaptability and improve AI-driven translation systems. Inclusion and cultural awareness remain central priorities in the evolution of AI translation, shaping its role in global communication.

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Artificial intelligence, Language translation, Machine translation, Neural Machine Translation, Statistical Machine Translation, Natural Language Processing

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This research paper looks into the various aspects of educational empowerment for tribal women in India, focusing on the challenges they face, the social and political factors at play, and the impact of government policies. The study focuses on three main objectives: To study the major barriers restricting tribal women from accessing and continuing education, To study the role of political representation and social norms in tribal women's educational progress, To study the innovative strategies and government policies that support the educational empowerment of tribal women. This study employs a conceptual and analytical framework, integrating academic literature, policy documents, and specific contributions from relevant thematic studies to identify trends of marginalization and resilience. Research shows that even though programs like affirmative action and government initiatives such as Sarva Shiksha Abhiyan, Kasturba Gandhi Balika Vidyalaya, and NEP 2020 have helped make education more accessible, serious issues like social and economic inequality, traditional gender roles, and differences between regions still hold back progress. The study highlights that meaningful participation in politics, participating in the community, and using education that respects different cultures are really important for addressing these issues. Moreover, new approaches like vocational training, boarding schools, online programs, and initiatives led by NGOs are starting to prove effective, especially when they match local requirements and are backed by the leadership of tribal women. The study concludes that helping tribal women through education needs more than just access; it also needs strategies that focus on quality, inclusivity, and giving them a voice. Educational empowerment is essential for development and is also crucial for achieving social justice in India's journey towards fairness and inclusion.

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Tribal, Gender, Tribal Women, Social Inclusion, Political Representation, Empowerment, Education

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Microfinance has emerged as a powerful tool for poverty alleviation and women's empowerment, particularly through Self-Help Groups (SHGs). This study examines the impact of microfinance on women's development in Coimbatore City, focusing on how SHGs contribute to economic independence, social empowerment, and improved quality of life. Using a mixed-method approach, the research analyzes primary data collected from women beneficiaries of SHG-linked microfinance programs, along with secondary data from reports and case studies. The findings reveal that microfinance enhances women's financial literacy, income-generating capabilities, and decision-making power within households. However, challenges such as limited access to higher loan amounts and socio-cultural barriers persist. The study concludes that while microfinance significantly promotes women's development, a more holistic approach--including skill training and awareness programs--can further amplify its positive effects.

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Microfinance, Self-Help Groups (SHGs), Women's Empowerment, Economic Development, Coimbatore.

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The Objective of present study involves preparation of herbal hair growth and premature greying hair mask by using various herbs like Flaxseed, Fenugreek, Hibiscus, Curry leaves, Black sesame seeds, etc. Herbal hair mask are chemical-free products that promotes hair health. It aims to nourish the scalp, moisturize hair, reduce hair fall, prevent grey hair and promote hair growth. This hair mask is suitable for various types of hair without damaging the hair. The product meets quality standards for a natural, non-irritating hair styling solution suitable for regular use. Hence, it is concluded that the mask is beneficial in maintaining good growth of hairs and prevent premature grey hairs. All prepared formulation is evaluated using parameters like pH, Viscosity, Spreadability, Solubility, Washability, Skin Irritation test. The results shown that herbal hair mask formulation number F3 is more stable and elegant as compared to other formulation.

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Herbal hair mask, herbs, natural ingredients, hair care, flaxseed, hair growth, grey hair.

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