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                <text>Perusal of flexoelectric effect with deformed interface in distinct (PZT-7A, PZT-5A, PZT-6B, PZT-4, PZT-2) piezoelectric materials</text>
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                <text>deformed interface; Dispersion relation; Flexoelectric influence; Mathematical Analysis; piezoelectric; surface wave vibrations</text>
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                <text>The present research article aims to describe that the flexoelectric affects the propagation of Love-type in various piezoelectric (PE) materials bars (PZT-7A, PZT-5A, PZT-6B, PZT-4, PZT-2) that rest over a silicon oxide plate under the presence of a deformed interface. With the help of material properties of these various piezoelectric, this article elucidates the impact of flexoelectric (FE) and piezoelectric (PE) on propagation characteristics of Love-type waves. Before this, the desire dispersion relation in the form of a complex, for both electrically unlocked/locked conditions, have been obtained by using mechanical as well as electrical quantities for the respective medium under suitable boundary and interface conditions. The complex dispersion relation is separated into real and imaginary terms which give Real(c) and Imag(c). Further, the effect of flexoelectric (FE) and piezoelectric (PE) on Real(c) and Imag(c) have been observed. In addition, a comparative study among various types of piezoelectric materials is also performed which serve as a major highlight of the present research work. The outcomes of this study may be very helpful in the specific problems of monitoring structural health system design with the help of simulation and alesser number of elaborate trials.  2022 Informa UK Limited, trading as Taylor &amp;amp; Francis Group.</text>
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                <text>Singhal A.; Tiwari R.; Baroi J.; Kumhar R.</text>
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                <text>Waves in Random and Complex Media</text>
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                <text>Singhal A., School of Sciences, Christ (Deemed to be University), NCR, Delhi, India; Tiwari R., Nitishwar College, Babasaheb Bhimrao Ambedkar University, Muzzaffarpur, India; Baroi J., School of Sciences, Christ (Deemed to be University), NCR, Delhi, India; Kumhar R., Department of Mathematics and Computing, Indian Institute of Technology (ISM), Dhanbad, India</text>
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                <text>Analysis of Flexoelectricity with Deformed Junction in Two Distinct Piezoelectric Materials Using Wave Transmission Study</text>
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                <text>Deformed Interface; Deformed Interface; Flexoelectricity; PZT-6B; PZT-7A; Vibrations</text>
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                <text>Analysis of flexoelectricity in distinct piezoelectric (PE) materials bars (PZT-7A, PZT-6B) with deformed interface in stick over Silicon oxide layer is studied analytically with the help of Love-type wave vibrations. Using the numerical data for PE material, then research achieves the noteworthy fallouts of flexoelectric effect (FE) and PE. The effect of flexoelectricity is compared first between biomaterials of piezoelectric ceramics. Dispersion expressions are procured logically for together electrically unlocked/locked conditions under the influence of deformed interface in the complex form which is transcendental. Fallouts of the research identify that contexture consisting of FE has a noteworthy impact on the acquired dispersion expressions. Existence of FE displays that the unreal section of the phase velocity rises monotonically. Competitive consequences are displayed diagrammatically and ratified with published outcomes. The outcomes of the present research done on both the real and imaginary section of the wave velocity. The comparative study between the two piezo-ceramics bars helps us to understand the properties of one piezo-material over the another and as an outcomes the significance of the present study helps in structural health monitoring, bioengineering for optimizing the detection sensitivity in the smart sensors.  2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.</text>
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                <text>Singhal A.; Tiwari R.; Baroi J.; Singh C.</text>
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                <text>Springer Proceedings in Complexity, pp. 1329-1340.</text>
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                <text>Singhal A., School of Sciences, Christ (Deemed to Be University) Delhi NCR, Ghaziabad, 201003, India; Tiwari R., Department of Mathematics, Babasaheb Bhimrao Ambedkar Bihar University, Nitishwar college, Muzaffarpur, 842002, India; Baroi J., School of Sciences, Christ (Deemed to Be University) Delhi NCR, Ghaziabad, 201003, India; Singh C., School of Sciences, Christ (Deemed to Be University) Delhi NCR, Ghaziabad, 201003, India</text>
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                <text>Biotechnological advancements in microplastics degradation in drinking water: Current insights and Future perspectives</text>
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                <text>Microplastics (MPs) have emerged as persistent toxicants in the recent decade. MPs are reported to present in different samples such as soil, water, wastewater, and human samples including placenta, urine etc. Recent studies have reported its presence in drinking water. MPs presence in the drinking water is of concern to the research because MPs are associated with several toxicities in animal models including human. The presented review is focused on understanding MPs abundance, sources, detection, analysis, and biotechnological approaches for its degradation. The paper discusses MPs sources, distribution, and transport in drinking water. In addition, it discusses the MPs identification in drinking water, and advances in biotechnological, metagenomics, system, and synthetic biology approaches for MPs degradation. Moreover, it discusses critically the major challenges associated with the MPs degradation in drinking water. Heterogeneity in the MPs size and shape makes it its identification difficult in the drinking water. Most of the methods available for MPs analysis are based on the dried samples analysis. Development of MPs in liquid samples may bring a breakthrough in the research.  2024 The Authors</text>
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                <text>Singhal B.; Kumar S.; Mehtab S.; Aggarwal U.; Kumar V.; Umesh M.; Chakraborty P.</text>
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                <text>Case Studies in Chemical and Environmental Engineering, Vol-9</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.cscee.2024.100640" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.cscee.2024.100640&lt;/a&gt;
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                <text>Singhal B., School of Biotechnology, Gautam Buddha University, U.P, Greater Noida, India; Kumar S., School of Biotechnology, Gautam Buddha University, U.P, Greater Noida, India; Mehtab S., Department of Chemistry, G.B. Pant University of Agriculture &amp;amp; Technology, Pantnagar, Uttarakhand, 263145, India; Aggarwal U., Patanjali Research Institute, (Uttarakhand), Haridwar, India; Kumar V., Bioconversion and Tissue Engineering (BITE) Laboratory, Department of Community Medicine, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS), Thandalam, Chennai, India; Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Chakraborty P., School of Allied Healthcare and Sciences, JAIN (Deemed to be University), Whitefield, Karnataka, Bangalore, 560066, India</text>
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                <text>(AMOS); Analysis of Moment Structure; job commitment; Job satisfaction; Performance and employee; Science (SPSS); Statistical Package for Social; teamwork; turnover; Work-life balance</text>
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                <text>BACKGROUND AND OBJECTIVES: An employees satisfaction and performance are linked to the companys work discipline, personal factors, and organizational culture. This paper studies these three factors in the context of Information Technology companies and their connection to employee satisfaction. Job satisfaction is a significant issue in Information Technology Companies, leading to increased labour turnover in Information Technology Companies. The study highlights the relevance of Information Technology companies to understanding the reasons behind their employees satisfaction. Until now, little is known concerning the variants of job satisfaction among Information Technology employees, enriching the understanding in this particular professional area. The study was conducted to assess the job satisfaction needs of the employees in major Information Technology companies. The study helps to know the preferences and problems of the employees. METHODS: In this study, data was collected from employees from various Information Technology companies to uncover the factors that impact the satisfaction of employees. Considering the studys goal and the literature review, the technique was analytical and interpretive. Due to large populations random sampling method is convenient for the study. The studys objectives were achieved explicitly via the questionnaires design. To test the proposed hypotheses, all data were processed using the Structural Equation Modelling, Statistical Package for Social Science (SPSS) and Analysis of Moment Structures. FINDINGS: Information Technology companies need their employees to feel satisfied to achieve the overall objectives and remain loyal to the company to achieve company success. From the responses, we learned that 31% of the respondents were satisfied with their employer about the various allowances and benefits they receive. Also, we knew that around 50% of the respondents were happy with their choice of the company because of its future commitments. 102 of the respondents highly disagreed that they were satisfied with the attitude and nature of their employees. Also, 22.26% of the male respondents have said they are only sometimes motivated to go to work. The limitation of this study was that the collected data was only of the general employees of the Indian Information Technology companies and not to specific departments of those companies. Also, no categories of companies were defined as per turnover. CONCLUSION: By recognizing the importance of job satisfaction, managers can create an environment that motivates and engages employees, leading to better performance, increased productivity and reduced employee turnover  2024 Tehran Urban Research and Planning Center. All Rights Reserved.</text>
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                <text>Singhal D.; Salunkhe H.A.</text>
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                <text>International Journal of Human Capital in Urban Management, Vol-9, No. 1, pp. 135-156.</text>
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                <text>ISSN: 24764698</text>
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                <text>Singhal D., School of Business and Management, Christ (Deemed to be University), Bangalore, India; Salunkhe H.A., School of Business and Management, Christ (Deemed to be University), Bangalore, India</text>
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                <text>The role of guilt-shame proneness and locus of control in predicting moral injury among healthcare professionals</text>
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                <text>ethical dilemma; frontline workers; healthcare professionals; moral conflict; pandemic</text>
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                <text>Despite the advances in studies conducted among healthcare professionals to explore the impact of the pandemic on their mental health, a large population still continues to display COVID-19 related psychological complaints. There has been recent awareness of moral injury related guilt and shame among doctors and nurses. However, the factors associated with moral injury have not received much attention, due to which the issue still persists. This study aims to explore the role of guilt-shame proneness, and locus of control in predicting moral injury among healthcare professionals. MISS-HP, PGI Locus of Control, and GASP scales were administered to a sample of 806 healthcare professionals. Pearson correlation coefficient indicated a significant positive relationship between moral injury and guilt-shame proneness, as well as the locus of control. Regression analysis indicated a significant role of guilt-shame proneness and locus of control in predicting moral injury. In conclusion, while studying moral injury, it becomes equally important to consider these factors to understand the concept better.  2023 The Author(s). Published by Informa UK Limited, trading as Taylor &amp;amp; Francis Group.</text>
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                <text>Singhal K.; Chukkali S.</text>
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                <text>Cogent Psychology, Vol-10, No. 1</text>
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                <text>&lt;a href="https://doi.org/10.1080/23311908.2023.2264669" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1080/23311908.2023.2264669&lt;/a&gt;
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                <text>ISSN: 23311908</text>
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                <text>Singhal K., Department of Psychology, Christ Deemed to be University, Delhi NCR, India; Chukkali S., Department of Psychology, Christ Deemed to be University, Delhi NCR, India</text>
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                <text>Psychometric Properties of the Moral Injury Symptom Scale Among Indian Healthcare Professionals</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="101310">
                <text>frontline workers; moral conflict; moral dilemma; pandemic</text>
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                <text>The spread of the novel coronavirus has led to a rise in morally conflicting situations for healthcare professionals. Doctors and nurses who were serving as frontline workers, require special attention to alleviate the long-lasting impact of the potentially morally injurious events. The current study aims to validate the Moral Injury Symptom Scale-Healthcare Professionals (MISS-HP) among Indian healthcare workers. The 10-item MISS was administered to 150 doctors and 150 nurses using the purposive sampling method. Firstly, reliability was assessed using internal consistency measure. Secondly, item discrimination index was assessed by calculating the point biserial correlation for each item. Cronbach alpha indicated high internal consistency (0.77). The point biserial correlation value for each item indicated good discrimination. Finally, confirmatory factor analysis (CFA) was performed to replicate the factor structure. CFA results suggested a good fit to the data. In conclusion, MISS-HP is a reliable and valid tool to assess moral injury among Indian healthcare professionals in India.  2023 Hibino et al.</text>
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                <text>Singhal K.; Chukkali S.</text>
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                <text>Psychology Research and Behavior Management, Vol-16, pp. 1439-1444.</text>
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              <elementText elementTextId="101314">
                <text>Dove Medical Press Ltd</text>
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                <text>&lt;a href="https://doi.org/10.2147/PRBM.S404094" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.2147/PRBM.S404094&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160070666&amp;amp;doi=10.2147%2FPRBM.S404094&amp;amp;partnerID=40&amp;amp;md5=e0c2ff24bb62f7adddf1cc42df2975c2" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160070666&amp;amp;doi=10.2147%2fPRBM.S404094&amp;amp;partnerID=40&amp;amp;md5=e0c2ff24bb62f7adddf1cc42df2975c2&lt;/a&gt;</text>
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                <text>ISSN: 11791578</text>
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                <text>Singhal K., Department of Psychology, CHRIST (Deemed to be University), Delhi NCR, Ghaziabad, India; Chukkali S., Department of Psychology, CHRIST (Deemed to be University), Delhi NCR, Ghaziabad, India</text>
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                <text>Impact of Machine Intelligence on Clinical Disease Outbreak Prediction</text>
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                <text>algorithmic bias; artificial intelligence; disease outbreak prediction; public health</text>
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                <text>This research paper examines the utilization of Artificial Intelligence (AI) in disease outbreak prediction and its importance in public health. It explores the hurdles associated with predicting disease outbreaks, including data quality and accessibility, ethical considerations, algorithmic bias, and integration and interpretability challenges. The paper presents an overview of AI techniques applied in healthcare and their relevance to forecasting disease outbreaks. Case studies demonstrate the efficacy of AI -based models in predicting infectious diseases, vector-borne diseases, and epidemics/pandemics, employing diverse data sources. The limitations and future prospects of AI in disease outbreak prediction are addressed, accompanied by recommendations for enhancement. In conclusion, the paper highlights AI's potential to revolutionize disease outbreak prediction, leading to proactive public health interventions and improved response strategies.   2023 IEEE.</text>
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                <text>Singhal M.; Mishra S.; Sharma V.; Anand K.; Alkhayyat A.</text>
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                <text>2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering, UPCON 2023, pp. 1020-1025.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Sinha A., Ignou, Department of Computer Science and Information Technology, New Delhi, India; Sharma V., Christ University, Institute of Information Technology, India; Gupta M., Rungta College of Engineering and Technology, Department of Physics, CG, Bhilia, India; Rao G.M., Koneru Lakshmaiah Education Foundation, India; Raj A., Galgotias University, School of Computing Science and Engineering, Greater Noida, India; Kumari A., Rkdf University, India; Alkhayyat A., The Islamic University, College of Technical Engineering, Najaf, Iraq</text>
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                <text>Sinha C., Christ University, Department of Psychology, Hosur Road, Bangalore Karnataka, 560029, India</text>
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                <text>The social representations of academic achievement and failure</text>
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                <text>This study tried to explore the ways in which the construct of academic achievement and failure is conceptualized and represented among different social categories based on educational roles. It was indicated that social representations of academic achievement and failure function in broader social contexts. Findings also suggested that academic achievement and failure are not the antinomies and have multidimensional aspects which collaborate and have greater bearing on the future social outcomes.  National Academy of Psychology (NAOP) India 2015.</text>
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                <text>Sinha C.; Kumar Mishra A.</text>
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                <text>Psychological Studies, Vol-60, No. 2, pp. 160-169.</text>
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                <text>ISSN: 332968</text>
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                <text>Sinha C., Department of Psychology, Christ University, Bangalore, India; Kumar Mishra A., Zakir Husain Centre for Educational Studies, Jawaharlal Nehru University, New Delhi, India</text>
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                <text>The illusion of social class identity and academic performance: Exploring the role of father education as an indicator of socioeconomic status</text>
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              <elementText elementTextId="138865">
                <text>Academic achievement; Identity processes; Social class; Socioeconomic status</text>
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                <text>The academic achievement of low social class students has been attributed to lack of ability and their socioeconomic Status (SES). However, a recent meta-analysis reported decreasing relationship between SES and academic achievement in the U.S. population (Sirin, 2005). The present study attempted to explore the relationship between social class identity processes and academic performance in an Indian context. The study took students' self report on all indicators of SES and separated high and low social class students on the basis of their fathers' education. The result showed that social class based identity process has less important role in explaining the existing academic achievement gap. Thus the need arises to explore other identities that may collaborate with the social class identity in an educational domain.</text>
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                <text>Sinha C.; Mishra A.K.</text>
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              <elementText elementTextId="138868">
                <text>Journal of Psychological and Educational Research, Vol-22, No. 1, pp. 34-56.</text>
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            <elementTextContainer>
              <elementText elementTextId="138869">
                <text>Universitatea din Oradea</text>
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                <text>ISSN: 22471537</text>
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                <text>Sinha C., Christ University, Department of Psychology, Bangalore, Hosur Road, India; Mishra A.K., Jawaharlal Nehru University, Department: Zakir Husain Centre for Educational Studies, New Delhi, India</text>
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          <element elementId="50">
            <name>Title</name>
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            <elementTextContainer>
              <elementText elementTextId="153841">
                <text>Efficacy of Artificial Neural Networks (ANN) as a Tool for Predictive Analytics</text>
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          <element elementId="49">
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            <description>The topic of the resource</description>
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              <elementText elementTextId="153842">
                <text>Artificial Neural Network (ANN); Decision-making; Forecasting; Output prediction; Predictive analytics</text>
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              <elementText elementTextId="153843">
                <text>Predictive analytics could also be defined as the application of statistical techniques and mathematical modeling to anticipate the future performance and expected return on investments. Predictive analytics examines the most recent and the historical data to see if the same pattern is likely to reoccur or not. This gives an opportunity to businessmen and financial investors to make an appropriate decision about their investments and expected returns. Ever since the development of ANN technique, researchers have tried to create a number of predictive models using ANN. The chapter is focused on defining predictive analytics and the tools used in predictive analytics, with a special orientation on Artificial Neural Networks. The objective of the chapter is to establish ANN as an effective technique for making appropriate predictions and thereby contributing toward the decision-making in various spheres using the outcomes from various researches. The chapter also aims to explain the step-by-step process of ANN in outcome prediction with the help of example.  The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.</text>
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              <elementText elementTextId="153844">
                <text>Sinha D.; Sarangi P.K.; Sinha S.</text>
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              <elementText elementTextId="153845">
                <text>Analytics Enabled Decision Making, pp. 123-138.</text>
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                <text>Springer Nature</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-981-19-9658-0_6" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-19-9658-0_6&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171511956&amp;amp;doi=10.1007%2F978-981-19-9658-0_6&amp;amp;partnerID=40&amp;amp;md5=d1fa562df36d8892ada5af694bd85888" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171511956&amp;amp;doi=10.1007%2f978-981-19-9658-0_6&amp;amp;partnerID=40&amp;amp;md5=d1fa562df36d8892ada5af694bd85888&lt;/a&gt;</text>
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              <elementText elementTextId="153849">
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                <text>ISBN: 978-981199658-0; 978-981199657-3</text>
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              <elementText elementTextId="153854">
                <text>Sinha D., CHRIST (Deemed to be University), Delhi NCR, India; Sarangi P.K., Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India; Sinha S., CHRIST (Deemed to be University), Delhi NCR, India</text>
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                <text>Decoding the alchemy of employee retention: A case of the manufacturing sector of the National Capital Region, India</text>
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              <elementText elementTextId="143274">
                <text>The ability of a company to retain its staff is referred to as employee retention. It may also be referred to as a decrease in employee attrition or employee turnover rate. Employee retention is one such mechanism which ensures that the human capital stays with the organisation for a longer duration. The study focusses on identifying the drivers of employee retention in the manufacturing industry with respect to certain factors such as mentoring, career development, work environment, job autonomy, and compensation. This research has used the descriptive research design with some elements of exploratory research design. The sample size for the study was 122. Primary data has been collected with the help of a prevalidated questionnaire with multiple-choice closed-ended questions on a five-point Likert scale. The collected data was analysed using Excel and SPSS with statistical tools like T-test, ANOVA, multiple linear regression, etc. A direct positive relation has been found between mentoring, work environment and compensation, and the employees' intention to stay.  2024, IGI Global.</text>
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              <elementText elementTextId="143275">
                <text>Sinha D.; Sinha S.; Jain S.</text>
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                <text>Global Practices on Effective Talent Acquisition and Retention, pp. 77-95.</text>
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                <text>Sinha D., Christ University, Bengaluru, India; Sinha S., Christ University, Bengaluru, India; Phutela N., Symbiosis Centre for Management Studies, Symbiosis International (Deemed University), Noida, Pune, India; Grover P., Symbiosis Centre for Management Studies, Symbiosis International (Deemed University), Noida, Pune, India</text>
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                <text>Sinha D., Christ University, Bengaluru, India; Sinha S., Christ University, Bengaluru, India; Shukla M., Bharati Vidyapeeth?s Institute of Management Studies, Navi Mumbai, India</text>
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