Volume 13 | Issue 6 |

 Abstract

Emotional Intelligence (EI) has emerged as a critical factor influencing employee performance in contemporary organizational settings, particularly in service-oriented sectors such as banking. This study investigates the role of EI in shaping the performance of employees working in private banks in Uttar Pradesh (U.P.), India. The research focuses on key workplace performance indicators--teamwork, leadership, decision-making, and customer relations--to assess the impact of EI dimensions on professional effectiveness. A structured questionnaire based on established EI models was administered to employees across selected private banks in U.P. The study utilized descriptive statistics, including mean and standard deviation, to analyze the data and evaluate the distribution of EI traits among respondents. Furthermore, correlation analysis was applied to explore the strength of relationships between EI components and the identified workplace factors. The findings reveal a strong positive correlation between high EI scores and improved workplace outcomes. Employees with greater emotional awareness and regulation skills demonstrated enhanced collaborative abilities, more effective leadership, rational decision-making, and superior customer engagement. These insights underscore the significance of EI as a soft skill essential for organizational success, particularly in customer-facing industries. This research contributes to the growing body of literature on emotional intelligence and organizational performance, highlighting its practical implications for human resource development, employee training, and performance management in the private banking sector. It recommends integrating EI assessment and training into HR policies to foster a more emotionally competent and high-performing workforce.

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 Keywords

Emotional Intelligence, Employee Performance, Private Banks, Teamwork, Leadership, Decision-Making, Customer Relations, Human Resource Development, Uttar Pradesh, Workplace Behavior

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This study investigates customer expectations and the difficulties related to quality control in yarn production related to Ennar Spinning Mills. Quality control is critically important in yarn manufacturing due to the requirements for consistency, durability and compliance to global standards.

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Yarn Production, Quality Control, Spinning Mills, Customer Expectation.

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Creative Commons Attribution 4.0 and The Open Definition

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The purpose of physical education is basically to make the body healthy, energetic and strong so that the body can become capable of struggle even in worldly adverse situations and can make life meaningful by becoming a means of attaining Purusharth Chatushtya.Students in physical education receive instruction in physical activities that assist keep them in shape. Students who desire to compete in sports receive specific practice sessions and preparation for contests. The capacity and confidence of a pupil to engage in physical activity are developed through physical education. It was incorporated into the academic programme by the . The major objective of putting physical education into practice and promoting it is to create physically literate people who have the knowledge and abilities to engage in healthy activities for the rest of their lives. After completing the required training, individuals can continue participating in activities without the assistance of professional trainers. The fundamental goal of physical education is to teach students about how their bodies develop and how to take care of themselves, which includes instruction in everything from basic hygiene to diet management. Knowing exactly what they are doing and why they are doing it requires knowledge.This increases their knowledge in the field of physical education.In this paper we highlight factors that make physical education so crucial and necessary, including how it promotes children's mental health, fosters a spirit of competition, and more. Physical education not only keeps the body in shape, but it also helps children stay healthy physically and mentally.

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 Keywords

Physical Education, Students, Academic curriculum,Skills, Knowledge

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 Abstract

Bhartiya Nayayik Pranali Mai Pariwarik Vivaado ko suljhane Mai Vekalpik vivaad Samadhaan ki bhumika : Ek Vidhik Adhayayan

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Bhartiya Nayayik Pranali Mai Pariwarik Vivaado ko suljhane Mai Vekalpik vivaad Samadhaan ki bhumika : Ek Vidhik Adhayayan

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The main role of faculty members towards student is to educate them and to create a society for country development. To reach these destination prominent role players that is faculty member's work and life should be in equilibrium stage. To study the level of agreement of work life balance of faculty members, an attempt was made to identify the relationship exists among the variables selected for this purpose. Ninety pertinent sample respondents contributed their views and the same was used as primary data for analysis. Collected data was analyzed using multiple regression analysis and suitable suggestions were made based on the findings of the study.

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Faculty members, work, Life, Equilibrium, Level of agreement

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Creative Commons Attribution 4.0 and The Open Definition

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This article examines the economic ramifications of persistent geopolitical tensions between India and Pakistan, two nuclear-armed neighbours with a complex history of conflict and fragile diplomacy. Despite numerous bilateral and multilateral efforts to improve relations, recurrent episodes of political and military standoffs--ranging from cross-border skirmishes to trade suspensions--have consistently disrupted economic cooperation and regional stability. Using a mixed-methods approach that incorporates macroeconomic indicators, trade data, foreign direct investment (FDI) flows, and geopolitical risk indices from 2000 to 2024, this study assesses how heightened political tensions have influenced each country's economic health. Our analysis reveals that surges in bilateral tensions often coincide with sharp declines in trade volumes, investor confidence, and tourism, particularly impacting sectors reliant on cross-border cooperation. India, with a more diversified and resilient economy, demonstrates greater insulation against short-term geopolitical shocks. In contrast, Pakistan exhibits more acute vulnerability, with marked fluctuations in currency value, stock market performance, and external financing terms during periods of heightened conflict. Furthermore, defence spending spikes during such periods lead to fiscal imbalances, diverting resources from developmental priorities in both nations. The findings highlight a significant economic cost to unresolved political disputes and underscore the need for confidence-building measures, regional trade integration, and sustained diplomatic engagement. Policy recommendations include structured dialogue platforms, economic diplomacy initiatives, and leveraging regional institutions like SAARC for economic cooperation, even amid political strains. The article concludes that while geopolitics may continue to dominate the bilateral narrative, economic pragmatism must guide future engagement to foster stability and growth in South Asia.

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 Keywords

India-Pakistan tensions, geopolitical risk, economic impact, bilateral trade, foreign direct investment, defence spending, economic diplomacy, regional stability, macroeconomic indicators, SAARC

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Creative Commons Attribution 4.0 and The Open Definition

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The paper provides a detailed review of ad- vanced machine learning and deep learning algorithms applied to brain tumor detection and classification from MRI images. The paper aims to assess the performance of various AI-based approaches to enhance the diagnosis ac- curacy with improved efficiency. We discuss the application of CNNs and other deep learning models and describe their strengths and weaknesses regarding processing MRI data. Our results show significant increases in the accuracy of the detection of tumors, especially when working with high- quality images and diverse datasets. The study necessitates the integration of advanced AI techniques: future research directions would be to overcome the current challenges existing in the dataset diversity, real-time processing, and the standardization of the evaluation metrics.

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Brain tumor detection, Brain tumor clas- sification, MRI images, Machine learning, Deep learning CNNs, AI-based approaches, Diagnosis accuracy, Efficiency Dataset diversity, Real-time processing, Evaluation metrics

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Evaluate, Respiratory care bundle, Dyspnoea

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Creative Commons Attribution 4.0 and The Open Definition

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This paper presents a critical political study of contemporary Indo-U.S. relations, tracing their evolution from the Cold War era to the present strategic partnership. It analyzes key dimensions of the relationship, including defense cooperation, diplomatic engagement, trade dynamics, and multilateral collaboration. The study highlights the growing strategic convergence between the two democracies, particularly in the context of the Indo-Pacific region and global geopolitical shifts. Using a qualitative and analytical approach, the paper draws on official documents, scholarly literature, and policy reports to assess both achievements and challenges in bilateral ties. While areas of friction remain such as trade disputes and differing foreign policy orientations India and the United States have demonstrated a shared commitment to fostering a stable, multipolar world order. The study concludes that sustained engagement, mutual respect, and adaptive diplomacy are essential for strengthening this vital partnership in the 21st century.

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 Keywords

Indo-U.S. Relations, Strategic Partnership, Foreign Policy, Indo-Pacific, Bilateral Cooperation

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Artificial Intelligence ("AI") is revolutionizing and restructuring the entire landscape of international arbitration by offering new tools that not only automate many administrative tasks but also ease the streamlined process of document review, and even it aids in the composition of awards. By using the system of advanced machine-learning algorithms effectively, parties to arbitration can anticipate probable outcomes with higher degrees of accuracy, better tailor their choice of arbitrators, and handle vast quantities of data far more efficiently than ever. But the use of AI also raises some basic questions and concerns about key issues such as transparency, accountability, and ensuring the preservation of key arbitral norms, such as due process and confidentiality. This paper tries to offer a comprehensive and exhaustive analysis of the current and potential uses of AI in the context of arbitration, and the attendant risks, such as "black-box" opacity and algorithmic bias, and the attendant legal and ethical implications that arise under existing institutional rules as well as national laws. Drawing on leading institutional reports, meticulous scholarly researches, and comparative regulatory efforts, it makes a compelling case that while AI promises significant efficiency gains and increased access to justice, the creation of strong governance frameworks and calls for explainability are critical to ensuring fairness and upholding legitimacy in the arbitral process.

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 Keywords

Artificial Intelligence (AI), International Arbitration, Machine Learning, Predictive Analytics, Award Drafting, Algorithmic Bias, Black-Box Opacity, Due Process, Confidentiality, Legal and Ethical Implications, Governance Frameworks, Transparency.

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Creative Commons Attribution 4.0 and The Open Definition