Volume 13 | Issue 6 |

 Abstract

This study explores the relationship between emotional intelligence (EI) and the quality of hospital services, focusing on Apollo Specialty Hospitals, OMR. Utilizing primary data from 160 respondents and secondary sources, it employs statistical tools such as correlation and ANOVA to analyze how nurses' emotional intelligence influences patient satisfaction and service outcomes. Results indicate that high EI among healthcare workers significantly enhances patient care, communication, and stress management. Recommendations include targeted EI training to improve service quality and employee well-being.

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 Keywords

Emotional Intelligence (EI), Quality of Hospital Services, Apollo Super Specialty Hospital, Self-Awareness, Empathy, Self-Regulation, Motivation, Social Skills

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Creative Commons Attribution 4.0 and The Open Definition

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Workplace stress has become a major concern in modern organizations, significantly affecting employee performance and overall productivity. This research focuses on Sunburgs Industries, Chennai, investigating the correlation between job-related stress and employee output. Using quantitative methods such as questionnaires and statistical tools (Chi-square, ANOVA, Correlation, Regression), the study identifies key stressors like workload, job insecurity, long working hours, and organizational pressure. The findings show that stress moderately impacts productivity and suggest that effective stress management strategies and flexible working conditions can enhance employee well-being and efficiency.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Work stress, employee productivity, organizational pressure, workload, stress management, Sunburgs Industries.

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Creative Commons Attribution 4.0 and The Open Definition

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Workplace absenteeism, defined as the failure of employees to report to work as scheduled, poses significant challenges for organizational efficiency and employee performance. This study focuses on Generation Z (Gen Z) employees, examining the factors influencing absenteeism, its impact on individual and team performance, and strategies to mitigate its effects. Through a survey of 120 respondents at Lifestyle Pvt. Ltd. Chennai branches, key findings reveal that personal responsibilities, mental health issues, and work-related stress are primary drivers of absenteeism. This research highlights the importance of flexible work policies, mental health support, and effective leadership in addressing absenteeism and enhancing performance.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Workplace absenteeism, Gen Z employees, employee performance, mental health, flexible work policies, organizational efficiency

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Creative Commons Attribution 4.0 and The Open Definition

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This analysis explores the performance and strategic role of large-cap, mid-cap, and small-cap mutual funds, alongside long-term equity and gold trends, to guide effective investment planning. Notable funds such as Nippon India Large Cap, Motilal Oswal Midcap, and Nippon India Small Cap exhibit strong risk-adjusted returns, as indicated by high Sharpe ratios and alpha values. Cost- efficiency, demonstrated by lower expense ratios in funds like ICICI Prudential Bluechip and HDFC Midcap Opportunities, further enhances investor gains. While large-cap funds provide stability, mid and small-cap funds offer higher growth potential, albeit with increased volatility-- necessitating alignment with individual risk profiles. Diversification, including a 10-15% allocation to gold, adds portfolio resilience due to gold's historical performance during economic crises. A disciplined strategy involving Systematic Investment Plans (SIPs), regular portfolio rebalancing, and goal-aligned investing supports sustainable wealth creation over the long term.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Mutual Funds, Risk-adjusted Return, Sharpe Ratio, Alpha, Diversification

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Creative Commons Attribution 4.0 and The Open Definition

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The growing involvement of third-party vendors in clinical trials--ranging from labs and imaging providers to ePRO systems and decentralized technologies--has introduced both opportunities and complexities in clinical data management. This review investigates the role of third-party vendor reconciliation, highlighting its impact on data quality, trial timelines, and regulatory compliance. Through analysis of empirical results, workflow models, and best practices, the paper underscores the limitations of manual reconciliation processes and the benefits of adopting AI-driven, standards-based, and automated approaches. It also outlines future directions, including interoperability enhancements, blockchain applications, and global regulatory harmonization. Ultimately, this review presents vendor reconciliation as a strategic component of clinical trial execution that deserves investment, innovation, and institutional prioritization.

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 Keywords

Vendor reconciliation, clinical data management, AI in clinical trials, data interoperability, CDASH, SDTM, decentralized clinical trials, audit readiness, third-party vendors, FHIR, regulatory compliance.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Politics is the art of controlling power and managing public affairs, often framing an enemy to unify a group. Democracy has shifted this focus toward ethical governance, recognizing citizens' equality, though it complicates the political process. Politicians frequently apply 'othering' to create distinctions between groups, thus reinforcing social hierarchies and power imbalances. Additionally, clientelism persists in many political systems, facilitating relationships with emerging groups while undermining democratic values. This study explores the interplay of 'othering' and 'clientelism' in state-society relations through various geopolitical case studies.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Othering, Clientelism, Political Power, Inclusive Governance, State-Society relations, Political Power

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Creative Commons Attribution 4.0 and The Open Definition

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Due to their moderate labor concentration, micro, small, and medium-sized businesses offer greater options for overhauls per unit of capital. Effective labor force management is necessary in order to offer employment opportunities. Numerous benefits for both the company and human resources would be ensured by the skilled management of human resources under its purview, including steadily rising productivity, preventing accidents, developing sound earnings of guiding principles in effective training of growing morale and profession satisfaction, preventing labor turnover and absenteeism, managing labor indiscipline and effective accusation management, etc. The study aims to investigate the management and effective use of human resources in Micro, Small, and Medium-Sized Enterprises (MSMEs) in India during the country's economic reforms. These reforms allowed for significant changes in the economy's structure, where MSMEs play a significant role. The research will demonstrate human resource management and the dynamics of its development as a crucial strategy in business development by presenting a viewpoint that many economists hold regarding a sense of competitiveness and globalization tendencies. Micro, small, and medium-sized businesses now confront difficulties in their operations, such as the human resources management process, as a result of one such extensive reform. What a step. Nonetheless, it has established a solid foundation for the development of procedures for Macedonia's market economy, which is required for the effective management and use of human resources.

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MSMEs, Labour Turnover, Globaliztion

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Creative Commons Attribution 4.0 and The Open Definition

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The aim of this paper is to introduce a new type of maps called Fuzzy wgr?-irresolute maps,strongly Fuzzy wgr?-continuous maps and study some of these properties

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Creative Commons Attribution 4.0 and The Open Definition

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Fuzzy wgr?-closed-sets,Fuzzy wgr?-open-sets, Fuzzy wgr?-continuous-maps,Fuzzy wgr?-irresolute maps,stronglyFuzzy wgr?-continuous maps.

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid advancement of Artificial Intelligence (AI) has transformed the e-commerce sector by enhancing operational efficiency, improving consumer engagement, and enabling data-driven decision-making. In this context, the present study titled *"A Study on Artificial Intelligence Applications in E-Commerce in Karnataka"* examines the role and impact of AI adoption on various aspects of e-commerce performance, with a special focus on consumer perceptions and city-wise differences. The major objective of the study is to analyze how AI applications influence operational efficiency, consumer experience, and sustainability practices in the state's e-commerce sector. The research employed a descriptive methodology, collecting primary data from 250 respondents across five cities in Karnataka (Mysore, Bangalore, Mangalore, Hassan, and Mandya) using a structured questionnaire on a five-point Likert scale. Descriptive statistics, regression analysis, and ANOVA were applied to test the hypotheses. The findings revealed that AI adoption significantly enhances efficiency (? = 0.42, p < 0.000), consumer experience (? = 0.48, p < 0.000), and sustainability (? = 0.21, p = 0.032). Further, ANOVA results indicated notable city-wise differences in adoption and satisfaction, with urban centers reporting higher acceptance and trust. The study concludes that while AI-driven personalization and recommendations strengthen consumer satisfaction, concerns regarding data security remain critical. The research holds importance as it provides actionable insights for businesses and policymakers while highlighting the scope for future research on generative AI and emerging e-commerce models.

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 Keywords

Artificial Intelligence, E-commerce, Consumer Experience, Operational Efficiency, Karnataka

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Creative Commons Attribution 4.0 and The Open Definition

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The integration of Artificial Intelligence (AI) in education has emerged as a transformative approach to enhance assessment accuracy, efficiency, and student learning outcomes. This study investigates the impact of AI on educational assessments in Karnataka, addressing the growing need to understand its effectiveness, adoption, and associated challenges within local academic institutions. The research aims to examine students' and educators' perceptions of AI-driven assessment tools, identify regional and demographic variations in acceptance, and explore ethical considerations influencing implementation. A descriptive research design was adopted, with primary data collected through a structured questionnaire administered to 150 respondents from Mysore, Bangalore, and Hassan. Data were analyzed using descriptive statistics, ANOVA, and regression analysis to identify trends, differences, and relationships between demographic factors and AI perceptions. The findings indicate that AI significantly improves assessment accuracy, reduces evaluation time, and positively influences learning outcomes, while ethical concerns and regional disparities affect adoption levels. Income and city of residence were found to significantly shape respondents' perceptions, and the null hypothesis of no significant impact of AI was rejected. The study highlights the relevance of AI in contemporary education and provides insights for institutions to implement ethical, context-sensitive, and effective AI-based assessment practices.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence, Educational Assessment, Karnataka, Learning Outcomes, Ethical Challenges

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Creative Commons Attribution 4.0 and The Open Definition