Volume 11 | Issue 9 |

 Abstract

Presented herein are in the analytical studies of hydrodynamic lubrication of micro-polar fluid in symmetric rollers. The load capacity have been examined for different values of parameter ?x, ?/?, and k_v/?_v . The load capacity depends different values of parameters. It has been observed that the load capacity increase with the increase of axial distance

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Micro-polar fluid, coupling constant, load capacity, axial distance.

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Purpose of the study: Main purpose for which study has been undertaken that to check and evaluate the liquidity position of selected steel companies in India and also to know the short term solvency of selected sample. Research methodology: This research is completely based on secondary nature and data has been collected from respective companies' annual financial report. Sample that has been selected for the study which are based on total asset of the company and also those sample are selected which are listed in NSE (NATIONAL STOCK EXCHANGE) as on 11 august 2023. Sample selection has been based on non-probability technique and also in non-probability technique researcher has used judgemental technique. Conclusion/ findings of the study: JSW steel has comparatively high current ratio, quick ratio and also high cash ratio. So researcher conclude that JSW steel has high liquidity capacity to pay off its current obligation of companies than TATA steel.

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Current ratio, Quick ratio, Cash ratio, TATA steel, JSW steel

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It is our duty to protect the environment, what nature has given to human life. In such a situation, man has constantly attacked the environment for his personal benefit. If this situation continues like this, our destruction will take place before our very eyes. If this does not happen, it is important to take care of the environment in today's time. There is no need to set aside our work for the protection of the environment. If we follow certain steps in our daily life, it will help in the survival of the environment.

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Parisara Maalinya, Parisara Jeevigalu, Sasyagala Upayoga

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Abstract: One of the most dangerous viruses of the 20th century is COVID-19, automated diagnosis has become one of the most fashionable research topics to achieve faster mass screening. Deep learning-based approaches have been found to be the most promising methods for finding this type of disease. However, this paper proposes a two-step deep CNN-based method to detect COVID-19 from chest X-ray images to achieve optimal performance with limited training images. In the first step, an encoder-decoder-based autoencoder network trained on unsupervised lung X-ray images is proposed, and the network learns to reconstruct the X-ray images. In the second step, an encoder network is proposed, which consists of different layers of the encoder model and then the encoder. Here, the encoder model is initialized with the weights learned in the first step, and the outputs of the different layers of the encoder model are effectively used by combining them into the proposed component network. An intelligent functional redundancy system is implemented in the proposed redundancy network. Finally, the link network of the encoder is trained to extract the detected features from the X-ray images, and the resulting features are used in the classification layers of the proposed architecture. Considering the final classification task, the EfficientNet-B4 network is used in both stages. Full training is performed on datasets covering the following categories: COVID-19, Normal, Bacterial Pneumonia, Viral Pneumonia. The proposed method gives a very satisfactory performance compared to the state-of-the-art methods and achieves 91.23 accuracy in 4-class, 95.72% in 3-class and 98.87% in 2-class classification.

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COVID-19 diagnosis; Medical Image Analysis; X-ray; Neural Network; Autoencoder; Deep Learning;

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This research paper investigates the role of translanguaging in the sales sector in India, with a focus on its influence in expediting deal closures and strengthening client relationships. Leveraging a mixed-method approach that integrates case studies and interviews with sales executives from various industries, the study aims to empirically validate the hypothesis that translanguaging serves as a potent linguistic strategy. Initial findings suggest that translanguaging not only facilitates more nuanced and effective communication but also engenders a more trustful and collaborative client-salesperson dynamic. The research adds to the burgeoning literature on applied linguistics in professional settings and offers actionable insights for sales training programs.

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Translanguaging, Sales, Business Communication, Client Relationship

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Story telling is most interesting and engaging activity to nurture the Preschool child's personality. A story is a narrative account of an event or a sequence of events. A good story always has a core element of truth and moral. The story must be consistent and authentic. Storytelling is an interactive art of using words and actions to reveal the elements and images of a story while encouraging the listener's imagination. However, this traditional method of early childhood learning has faded somewhere in this techno-oriented world. We depend on gadgets to tell stories to children. But despite advancements in technology, gadgets remain devoid of the 'human touch. And one disheartening fallout is that the importance of storytelling for children is slowly diminishing. Hence there is an urgent need to take an initiative to redefine this method again. The objective of the present paper is to analyse the importance of story telling and help the Pre-school children for their al round development with the help of management, teachers and parents.

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Storytelling, Pre school children, moral stories, pre school education.

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Medicinal From ancient times, plants have been used in traditional medicines for the treatment of different ailments. Plants are one of the richest bioresources for traditional and folk medicines to date. Jasmine is botanically known as Jasminum sambac or Jasmininie and belongs to the olive family of Oleaceae. Literature reports suggest that Jasmine is analgesic, antidepressant, antiseptic, expectorant, aphrodisiac, sedative, stomachic, diuretic, depurative, astringent, stimulating, anti-oxidizing, anthelmintic, and anti-inflammatory. The objective was to study the antibacterial activity of Jasminum sambac extracts against mouth ulcer-causing organisms. The antibacterial activity has been studied against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Bacillus subtilis & Enterococcus faecalis by agar well diffusion method. Leaves extract of J. sambac gives effective results against oral pathogens causing mouth ulcers. Acetone and Ethanol extracts displayed good antibacterial activity. The phytochemical studies revealed the presence of Carbohydrates, Proteins, Steroids, Alkaloids, Flavonoids, Phenols, Saponins, Glycosides, and Tannins. J. sambac may prove to be an effective medicine for the treatment of ulcers.

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Jasminum sambac, Antibacterial activity, Phytochemical analysis, Oral Pathogens.

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India is a country of rich traditional knowledge. The people of this land, through their indigenous knowledge, have been able to understand and use the complexities of life to find the best possible solutions over time. They had an innovative approach to addressing the challenges of different life forms. Dharamapala's works represent the knowledge system that prevailed in India before the European invasion. People who came from different places also started to spread the knowledge in their countries. It's a known fact that environment and ecology comprising air, earth, water, plants and animals play a very significant role imperative in sustaining human life and civilization. Human civilization can flourish only if there is consistent harmony among various stakeholders in making optimum sustainable use of the world natural resources and take responsibility to protect the environment from any degradation and damage. Indian presidency adopted an action-oriented approach and the G20 explored mechanisms that can support timely and adequate mobilization of resources for climate finance, facilitating access to multilateral climate funds and enhancing their leverage and ability to mobilize private capital has also been the focus.

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Sustainability, Inclusiveness, responsibility, ancient wisdom, cultural economy, global economy

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The adoption of renewable energy sources in modern India has significant implications for ecology, environment, and tourism. This paper provides a comprehensive overview of the potential benefits and challenges associated with renewable energy projects in India. We discussed the environmental impact of renewable energy sources, the social and economic impact, and the impact on tourism. We also explored several examples of renewable energy projects and their impact on different aspects of Indian society. In conclusion, we emphasized the importance of a sustainable and socially responsible approach to the adoption of renewable energy sources in India, and the need for policies and regulations that prioritize environmental protection and the rights of local communities.

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Ecology, Environment, and Tourism

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The field of biosciences have progressive to a higher extent and have generated large amounts of information from Electronic Health Records. This have given rise to the acute need of knowledge generation from this enormous amount of data. Data mining methods and machine learning play a major role in this aspect of biosciences. Chronic Kidney Disease (CKD) is a condition in which the kidneys are damaged and cannot filter blood as they always do. A family history of kidney diseases or failure, high blood pressure, type 2 diabetes may lead to CKD. This is a lasting damage to the kidney and chances of getting worse by time is high. The very common problems that results due to a kidney failure are heart diseases, anemia, bone diseases, high potassium, and calcium. The worst-case situation leads to complete kidney failure and necessitates kidney transplant to live. An early detection of CKD can increase the quality of life to a greater extent. This calls for good prediction algorithm to predict CKD at an earlier stage. Literature shows a wide range of machine learning algorithms employed for the prediction of CKD. This paper uses data preprocessing, data transformation and various classifiers to predict CKD and proposes best Prediction framework for CKD. The results of the framework show promising results of better prediction at an early stage of CKD.

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Chronic Kidney Disease, Machine Learning Approaches, Kidney Disease Prediction.

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