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                <text>Lakshmi, R.B.; Kapadan Othayoth, Poornima; patil, Anand; Jarvinia</text>
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                <text>The Role of Social Media in Shaping Gen Zs Awareness in Understanding Social Issues</text>
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                <text>Lecture Notes in Networks and Systems;Volume;1269 LNNS;pp.215-234</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-981-96-4319-6_17" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-96-4319-6_17&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105019532581?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105019532581?origin=resultslist&lt;/a&gt;</text>
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                <text>Lakshmi R.B., School of Business and Management, Christ University, Bangalore, India; Kapadan Othayoth P., School of Business and Management, Christ University, Bangalore, India; patil A., School of Business and Management, Christ University, Bangalore, India; Jarvinia, School of Business and Management, Christ University, Bangalore, India</text>
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                <text>Many social movements (such as #Black Lives Matter Movement, #MeToo Movement and #EndAcidSale Movement) have gained momentum through social media, but there is a research gap in understanding Generation Zs individuals participation and engagement in these social movements and also the awareness they have regarding social issues through social media. This study aims to understand how social media engagement affects Gen Zs understanding of social issues and how the perceptions of Gen Z regarding social issues is influenced by it. It is crucial to look into Gen Zs engagement in these social movements and also the awareness they get regarding social issues through social media. Algorithms tend to dictate the content that reaches the users; therefore, we want to analyse whether social media algorithms is effective in ensuring Gen Z social media users get an understanding of different viewpoints regarding the social issue. Understanding Gen Zs engagement in social activism through social media requires an in depth analysis on the factors that motivate them to do so. These factors can include their belief that it would lead to a systematic change, a sense of community they get when they engage with others on social media about social issues, pressure from their social circle to engage with social media content related to social issues and the desire to be seen as socially conscious by their peers. This study also aims to find out whether this has an effect on their mental health. The findings of the study show that social media content engagement moderates the relationship between social issue awareness and both real-world activism and mental health among Gen Z. Increased social issue awareness and social media content engagement lead to higher activism, but excessive engagement is found to negatively impact mental health among Gen Z. Results from the study indicates that respondents believe in the effectiveness of social media activism but also report feeling stressed, anxious, and overwhelmed by social issue-related content.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.</text>
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                <text>Lakshmi, S.R.; Manasa, N.</text>
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                <text>Artificial Intelligence in Peace, Justice, and Strong Institutions;pp.257-282</text>
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                <text>Lakshmi S.R., Christ University, India; Manasa N., Christ University, India</text>
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                <text>In recent years, the exponential growth of e-commerce has revolutionized how businesses operate and interact with consumers. This surge in online shopping has been accompanied by a parallel rise in digital marketing strategies employed by e-commerce companies to attract, engage, and retain customers. Digital marketing encompasses various techniques, including search engine optimization (SEO), social media marketing, content marketing, email marketing, and pay-per-click advertising. The effectiveness of these strategies in enhancing a company's financial performance has become a subject of significant interest and scrutiny. Companies can boost their bottom line and achieve greater profitability by reducing customer acquisition costs, increasing customer lifetime value, and improving overall marketing efficiency. Ecommerce businesses could better reach their target audience on these channels by increasing their brand visibility and reach and driving traffic to their websites.  2025, IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>ISBN: 979-836939397-0; 979-836939395-6;</text>
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                <text>Lakshmi, S.R.; Rajimol, K.P.; Sunidu, Y.K.; Samai, Ajatashatru; Priya, R.P.; Srija, H.R.</text>
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                <text>The Role of Al in Customer Relationship Management for Tailored Financial Services</text>
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                <text>Security Intelligence in the Age of AI: Navigating Legal and Ethical Frameworks;pp.203-221</text>
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                <text>Lakshmi S.R., Christ University, India; Rajimol K.P., Atria Institute of Technology, India; Sunidu Y.K.; Samai A., Sri Venkateshwara College of Engineering, India; Priya R.P., Sri Venkateshwara College of Engineering, India; Srija H.R., Sri Venkateshwara College of Engineering, India</text>
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                <text>Much as the financial services industry is characterised by dynamism, Artificial Intelligence (Al) is gradually transforming the Customer Relationship Management (CRM). Among the AI-related advances is the advancement of bespoke financial services that increases involvement and experience of the customers. This chapter seeks to address the following research question: how has the incorporation of Al tools influenced the CRM strategies adopted by the industry? Newer, implementing Al in CRM systems, banks can go through terabytes of customers' information looking for more about each other's preferences, tendencies and needs. This information may therefore allow for financial services, proactive customer care and consumption point marketing based on segments of the population. Information on financial organisations' successful implementation of Al-based CRM systems is provided in the chapter; in addition, challenges and ethical issues regarding the use of these technologies are also described. The findings show how the use of Al can enhance CRM in the financial services sector resulting in satisfied and loyal customers alongside more organisation productivity. As for the maximisation of CRM results, the report also suggests that financial institutions must use Al appropriately while addressing the problems associated with the latter.  2025 Lakshmi S.R., Rajimol K.P., Y.K. Sunitha, Ajatashatru Samal, Priya R.P. and Srija H.R. All rights reserved.</text>
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                <text>Artificial Intelligence; Chatbots; CRM; Financial advisory; Personalised banking; Virtual assistants</text>
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                <text>Cancer Prognosis by Using Machine Learning and Data Science: A Systematic Review</text>
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                <text>Artificial intelligence; Cancer; Data science; Decision trees; Deep learning; Machine learning</text>
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                <text>Cancer is one of the most fatal diseases in the world and the leading cause for most deaths worldwide. Diagnosing cancer early has become the need of the day for doctors and researchers as it allows them to categorize patients as high-risk and low-risk categories which will eventually help them in correct diagnosis and treatment. Machine learning is a subset of artificial intelligence that makes use of raw data to make predictions and insights. Using machine learning for cancer prognosis has been under study for a long time and several papers have been published regarding the same. Even though many papers have been published on the usage of statistical methods for cancer prognosis, it has been proved that machine learning models provide more accuracy when compared to conventional statistical methods of detection. These machines can be trained to detect abnormalities such as a tumour by looking at real-world examples. Models such as artificial neural networks, decision trees, clustering techniques, and K-Nearest-Neighbours (KNNs) are being used for cancer prediction, prognosis and also research purposes. The key aim of this article is to go through the popular key trends in using machine learning algorithms for cancer prognosis, types of input datasets to be fed, different types of cancers that can be studied and also the performance of these models.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Lakshmikanth Rajath Mohan T.; Jayapandian N.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-551, pp. 1-12.</text>
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                <text>Lakshmikanth Rajath Mohan T., CHRIST (Deemed to Be University), School of Engineering and Technology, India; Jayapandian N., CHRIST (Deemed to Be University), School of Engineering and Technology, India</text>
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                <text>Recent and past earthquakes have once again reiterated the requirement of strengthening the masonry structures to withstand both in-plane and out-of-plane loads. In this experimental investigation, biaxial polypropylene geogrid was used as a confinement reinforcement on the surfaces to strengthen masonry specimens. The masonry specimens without and with geogrid have been subjected to a compression test, flexural bond strength test and diagonal tension (shear) test as per IS 1905, ASTM E518 and ASTM E519, respectively. From the results, it has been found that biaxial polypropylene geogrid significantly enhances the strength in masonry specimens with geogrid and also reduces crack propagation in all three tests. The relationship between compressive strength and flexural bond strength, compressive strength and shear strength of masonry specimens with geogrid has been established. Furthermore, based on the cost analysis of various strengthening techniques, it was concluded that the use of biaxial polypropylene geogrid is an economically feasible alternative to other reinforcing materials, such as stainless-steel wire mesh and polyester geogrid.  The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.</text>
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                <text>ISSN: 23653159</text>
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                <text>Lakshmish Kumar S., BMS College of Engineering, Bangalore, 560019, India, Department of Civil Engineering, CHRIST (Deemed to Be University), Bangalore, 560074, India; Arunkumar A.S., BMS College of Engineering, Bangalore, 560019, India; Alex J., Department of Civil Engineering, CHRIST (Deemed to Be University), Bangalore, 560074, India; Bhalkikar A., Department of Civil Engineering, CHRIST (Deemed to Be University), Bangalore, 560074, India; Hossiney N., Department of Civil Engineering, CHRIST (Deemed to Be University), Bangalore, 560074, India</text>
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                <text>Class effectiveness; COVID-19; Digital transformation; Online classes; Teacher training</text>
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                <text>Digital technology is transforming society and business like never before. Digital technology has made inroads into all sections of society, especially with the pandemic restricting interaction and movement in the physical space. Education systems and institutions have witnessed a drastic change in their pedagogy. Education institutions adopting digital technologies can become drivers of growth and development for their ecosystems bringing significant changes in education, engagement, and management of class activities of educational institutions. The education system will have to adapt and evolve to take advantage of the new technologies and tools and develop strategies to play an active role in the digital transformation process. In the wake of the COVID-19 situation, higher education institutions have adopted digital platforms for teaching and learning. The study attempts to understand the instructors/academician/teachers training process adopted by selected higher education institutions in India to facilitate migration to digital platforms. Further, the study analyses the challenges faced in the new normal of education and the levels of training process initiated by institutions for teaching faculty. The authors have tried to analyse how this has enabled instructors to meet the challenges of conducting online classes and increase class effectiveness. The study unfolded the impact of high-level institutional training on class effectiveness and how individual digital preparedness is essential in engaging virtual classrooms. Further, the positive impact of training in reducing anxiety in engaging online sessions and the extent of motivation to continue online teaching as it has become inevitable with the second wave of the pandemic were examined across age and gender. An attempt is made to suggest few strategies for continued effective online class engagement as India battles through the second wave of the pandemic.  2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.</text>
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                <text>Lakshmypriya K.; Rai R.; Kudal P.</text>
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                <text>Public Administration and Information Technology, Vol-7, pp. 175-196.</text>
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                <text>ISSN: 25121812</text>
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                <text>FOXS HEAD OR LIONS TAIL? WORK LIFE BALANCE OF WOMEN ENTREPRENEURS IN AGRICULTURE AND FARM VENTURES AND ITS ANTECEDENT EFFECT ON QUALITY OF LIFE; [CABE DE RAPOSA OU RABO DE LE? EQUILRIO DA VIDA PROFISSIONAL DAS MULHERES EMPREENDEDORAS NA AGRICULTURA E EMPREENDIMENTOS AGROLAS E SEU EFEITO ANTECEDENTE NA QUALIDADE DE VIDA]; [CABEZA DE ZORRO O COLA DE LE? LA CONCILIACI DE LA VIDA LABORAL Y FAMILIAR DE LAS MUJERES EMPRESARIAS EN LA AGRICULTURA Y LAS EXPLOTACIONES AGROLAS Y SU EFECTO ANTECEDENTE EN LA CALIDAD DE VIDA]</text>
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                <text>Purpose: The objective of this study was to identify the factors that influence work life balance of women entrepreneurs in the field of agriculture and allied products and how the family demands affect their work-life balance. Further, the paper explores the conflict between parental demand and running a business. Theoretical framework: Literature review points out that despite, an increase in the number of women entrepreneurs over the years, according to the (Global entrepreneurship monitor report, 2020), fewer women pursue entrepreneurship due to various challenges of managing personal and business responsibilities and striking the right balance. Work-life balance is frequently examined in the context of human resource management (Etienne St-Jean and Duhamel M.,2020)but not much has been explored in an entreprenurial context.Hence this study is to investigate and understand the influence of various factors affecting work life balance from an entrepreneurial standpoint. Design/methodology/approach: Triangulation method was used for the study by utilizing both quantitative and qualitative data. The researchers developed a questionnaire to measure work-life balance experienced by women entrepreneurs with 12 independent variables to measure the dependent variable work-life balance.The sample consisted of 450 women agripreneurs Findings: The findings reveal that the age of the children is a major determinant of the extent of parental demand a woman goes through in her life and family support systems are critical in reducing overlap and conflict between the life domains. A positive spillover between the domains significantly enhances quality of life of women entrepreneurs. Research, Practical &amp;amp; Social implications: We suggest a future research into other Personality traits and macro environmental factors which can have a bearing on work life balance of women entrepreneurs which would enable an inclusive entrepreneurial ecosystem. Originality/value: The researchers have concluded that positive spillover between the domains significantly enhances quality of life of women entrepreneurs.  2022 The authors.</text>
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                <text>Lakshmypriya K., School of Business and Management, Christ University, Bangalore, India; Rai R., School of Business and Management, Christ University, Bangalore, India; Kulkarni S., School of Business and Management, Christ University, Bangalore, India; Shankar G., School of Business and Management, Christ University, Bangalore, India; James L., School of Business and Management, Christ University, Bangalore, India</text>
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                <text>Capability building; Cultural identity; Economic inclusion; Inclusive engagement; Indigenous tribes; Indigenous values; Social inclusion; Social vulnerabilities; Sustainable livelihoods; Tribal culture</text>
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                <text>Tourism acts as a stimulant in rural poverty reduction and inclusive socioeco-nomic development. Sustainable tourism can significantly contribute to the economic diversification and local economic development of rural areas with its ability to create jobs and encourage infrastructural development focusing on preserving the environment, culture and indigenous groups. The detrimental effects of tourism on the economy, society and culture have shifted attention to sustainable travel. As a result, terms like 'tribal tourism', 'ecotourism' and 'sustainable tourism' have become popular. Inclusive engagement is a crucial agenda item in future tourism development and a major concern of many international organisations, including the United Nations. This chapter focuses on exploring the tribal communities and their involvement in sustainable tourism initiatives with an overarching focus on the role of the indigenous community and their skill sets in creating sustainable livelihoods through tribal tourism. Apart from creating direct and indirect employment opportunities,  2024 Kottamkunnath Lakshmypriya and Bindi Varghese. All rights reserved.</text>
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                <text>IOT-BASED cyber security identification model through machine learning technique</text>
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                <text>Cyber security; Internet of things; Machine learning algorithms; Meta-classifier methods; Repositories; Security</text>
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                <text>Manual vulnerability evaluation tools produce erroneous data and lead to difficult analytical thinking. Such security concerns are exacerbated by the variety, imperfection, and redundancies of modern security repositories. These problems were common traits of producers and public vulnerability disclosures, which make it more difficult to identify security flaws through direct analysis through the Internet of Things (IoT). Recent breakthroughs in Machine Learning (ML) methods promise new solutions to each of these infamous diversification and asymmetric information problems throughout the constantly increasing vulnerability reporting databases. Due to their varied methodologies, those procedures themselves display varying levels of performance. The authors provide a method for cognitive cybersecurity that enhances human cognitive capacity in two ways. To create trustworthy data sets, initially reconcile competing vulnerability reports and then pre-process advanced embedded indicators. This proposed methodology's full potential has yet to be fulfilled, both in terms of its execution and its significance for security evaluation in application software. The study shows that the recommended mental security methodology works better when addressing the above inadequacies and the constraints of variation among cybersecurity alert mechanisms. Intriguing trade-offs are presented by the experimental analysis of our program, in particular the ensemble method that detects tendencies of computational security defects on data sources.  2023 The Authors</text>
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                <text>Lal B.; Ravichandran S.; Kavin R.; Anil Kumar N.; Bordoloi D.; Ganesh Kumar R.</text>
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                <text>Measurement: Sensors, Vol-27</text>
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                <text>Lal B., Dept. of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur Dist, A.P, India; Ravichandran S., Department of Computer Science and Engineering, School of Technology, GITAM University, Rudraram, Telangana, Hyderabad, 502 329, India; Kavin R., Department of Electrical and Electronics Engineering, Sri Krishna College of Engineering and Technology, Tamil Nadu, Coimbatore, 641008, India; Anil Kumar N., Department of Electronics &amp;amp; Communication Engineering, School of Engineering &amp;amp; Technology, Mohan Babu University (Erst while Sree Vidyanikethan Engineering College), Andhra Pradesh, Tirupati, India; Bordoloi D., Computer Science and Engineering, Graphic Era Hill University, Dehradun, India, R/S, CSE, Graphic Era Deemed To Be University, Uttarakhand, Dehradun, 248002, India; Ganesh Kumar R., Department of Computer Science and Engineering, CHRIST (Deemed to be University), School of Engineering and Technology, Kengeri Campus, Kumbalgodu, Bangalore, 560074, India</text>
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                <text>There have been cohesive attempts at forging alliance through the sustained efforts of emergent Dalit Civil society network, Dalit academicians and the renaissance of Ambedkarite thought among the Dalit youth around the question of political representation and social justice. This has led to a renewed and greater visibility of caste-based social relations and interactions in the present millennium, which was otherwise, treated as a long-forgotten age-old tradition. The lived experiences of exclusion and atrocities faced by members of the Dalit community especially the violence against women and girls reflect the grim reality of the prevalent casteist and patriarchal society. In this background, the emergence of Dalit Womens collectives raising their voices not just on caste but also on the intersectionality of gender provides a new dimension of analysis based on the critical race theory. Thereby, the attempt has been on forging an alliance and building collective voices. The chapter seeks to highlight the numerous struggles and triumphs along the way made by Dalit Women (also with building alliances with Black Womanists and Feminists Movement) in challenging the way in which feminists discourses have been held leading to rethinking and reimagining womens collectives by way of building solidarities, recognizing the difference of experience and positioning in caste and gender ladder that have influenced access to resources, rights, political representation and decision-making power from the local governance to national level.  The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.</text>
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                <text>Lal M.P., CHRIST University, School of Business and Management, Bengaluru, India; Nagariya R., CHRIST University, School of Business and Management, Bengaluru, India; Siddh M.M., Department of Mechanical Engineering, Jaipur Engineering College and Research Centre, Rajasthan, Jaipur, 302022, India</text>
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                <text>This paper investigates to deliver an overview of literature from 2012 to 2023 on the phenomena of implementing artificial intelligence in education (AIEd). With the help of the Scopus indexing database, data from 441 articles were extracted, analysed based on the keywords and preliminary reading and synthesised according to explicit inclusion and exclusion criteria and article compilation was on the parameters of scientific procedures and rationales for systematic literature review protocol (SPAR4SLR). Drawing on the recent literature depicts that the inception of artificial intelligence in education is still in its initial stage and much research is required. This article implies that although there are benefits and challenges talked about in the article delving into the application of AIEd in higher educations system of teaching and learning that shall lead the education system to newfound intelligence and automation, however, things are at the very initial stage and filled with conjectures. The findings demonstrate that the artificial intelligence-based teaching and learning phenomenon has a bright future as educational institutes understand its upcoming impact. The greatest challenge for educational institutes now is to start planning, designing, developing and implementing artificial intelligence-based courses for multidisciplinary and holistic training for future employees. Copyright  2025 Inderscience Enterprises Ltd.</text>
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                <text>The rapid progress in the scientific innovations and the hunt for the renewable energy increases the urge for producing the bio electronic products, solar cells, bio batteries, nano robots, MEMS, blood less surgical tools which can be possible with the aid of the micromachining. This article helps us to understand the evolution and the challenges faced by the micromachining process. Micro machining is an enabling technology that facilitates component miniaturization and improved performance characteristics. Growing demand for less weight, high accuracy, high precision, meagre lead time, reduced batch size, less human interference are the key drivers for the micromachining than the conventional machining process.  Owned by the authors, published by EDP Sciences, 2015.</text>
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                <text>Lalakiya M.R.</text>
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                <text>Lalakiya M.R., Christ University Faculty of Engineering in Bengaluru, India</text>
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                <text>Therapeutic clowning uses humor and play to minimize the stress for patients and their families during hospitalization. This study aims to explore the subjective meaning of therapeutic clowning through clowns perspective, understand why they continue clowning and interpret how it has impacted them. The research design takes a qualitative approach using phenomenological paradigm. Nine therapeutic clowns between 20 and 60years with clowning experience of 6months-4years from Compassionate Clowns, located at Bangalore were interviewed. The results reflected that the journey of being a therapeutic clown has been equally therapeutic for the clowns. Based on the thematic data analysis network, it was found that clowning has instilled many values in the way they think. It has given them a platform to learn new things from the children they clown. Therefore, looking at these results it could be said that therapeutic clowning serves as a medium for community service and in maintaining personal wellbeing.  2020, Springer Science+Business Media, LLC, part of Springer Nature.</text>
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                <text>Lalantika V.; Yuvaraj S.</text>
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                <text>Current Psychology, Vol-41, No. 3, pp. 1131-1138.</text>
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                <text>Lalchand B., Institute of Astronomy, National Central University, 300 Zhongda Road, Zhongli, Taoyuan, 32001, Taiwan; Chen W.-P., Institute of Astronomy, National Central University, 300 Zhongda Road, Zhongli, Taoyuan, 32001, Taiwan, Department of Physics, National Central University, 300 Zhongda Road, Zhongli, Taoyuan, 32001, Taiwan; Biller B.A., SUPA, Institute for Astronomy, University of Edinburgh, Blackford Hill, Edinburgh, EH9 3HJ, United Kingdom, Centre for Exoplanet Science, University of Edinburgh, Edinburgh, United Kingdom; Albert L., Institut de Recherche sur les Exoplanes (IREx), Universitde Montrl, Dartement de Physique, C.P. 6128 Succ. Centre-ville, Montrl, H3C 3J7, QC, Canada; Allers K., Department of Physics and Astronomy, Bucknell University, Lewisburg, 17837, PA, United States; Dubber S., SUPA, Institute for Astronomy, University of Edinburgh, Blackford Hill, Edinburgh, EH9 3HJ, United Kingdom, Centre for Exoplanet Science, University of Edinburgh, Edinburgh, United Kingdom; Zhang Z., The University of Texas at Austin, Department of Astronomy, C1400, 2515 Speedway, Austin, 78712, TX, United States; Liu M.C., Institute for Astronomy, University of Hawai'i, 2680 Woodlawn Drive, Honolulu, 96822, HI, United States; Jose J., Indian Institute of Science Education and Research (IISER) Tirupati, Rami Reddy Nagar, Karakambadi Road, Mangalam (P.O.), Tirupati, 517 507, India; Damian B., CHRIST (Deemed to Be University), Hosur Road, Bengaluru, 560029, India; Sharma T., Institute of Astronomy, National Central University, 300 Zhongda Road, Zhongli, Taoyuan, 32001, Taiwan; Bonnefoy M., Univ. Grenoble Alpes, CNRS, IPAG, Grenoble, F-38000, France; Oasa Y., Faculty of Education, Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama, 338-8570, Japan</text>
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                <text>Lalitha P., Geetanjali College of Engineering and Technology, Department of Computer Science and Engineering, Hyderabad, India; Nooka Raju G., GMR Institute of Technology, Department of Electronics and Communication Engineering, Rajam, Andhra Pradesh, Vizianagaram, India; Sindhu V., Christ University, Department of Computer Science, Karnataka, India; Sujatha C.K., St. Joseph's College for Women(A), Department of Mathematics, Andhra Pradesh, Visakhapatnam, India; Mandal P., RIMT University, Department of Forensic Science, Punjab, Mandi Gobindgarh, India; Arulkarthick E.K., Nandha Engineering College, Department of Electronics and Communication Engineering, Tamil Nadu, India</text>
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