Volume 13 | Issue 6 |

 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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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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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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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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Evaluate, Respiratory care bundle, Dyspnoea

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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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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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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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In the era of cloud computing, efficient Virtual Machine (VM) placement plays a pivotal role in optimizing resource utilization, improving performance, and maintaining robust security within data centers. This research paper presents an implemented algorithmic approach tailored for VM placement in Microsoft Azure cloud environments, aiming to enhance both operational features and key security aspects of modern data centers. The proposed solution focuses on dynamic resource allocation, load balancing, and minimization of latency while incorporating security constraints such as isolation, data integrity, and compliance. By mixing policy-aware scheduling and brainy placement heuristics, the algorithm enhance scalability and mitigates susceptibilities associated with multi-tenant structures. Experimental results demonstrate significant improvements in resource efficiency, response times, and adherence to security benchmarks when compared to traditional VM placement strategies with PM. This study contributes toward developing more secure, cost-effective, and performance-optimized cloud data centers using Azure's capabilities.

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Virtual Machine Placement, Azure Cloud, Cloud Computing, Data Center Optimization, Resource Allocation, Load Balancing, Cloud Security, Algorithm Implementation, VM Scheduling, Multi-Tenancy, Isolation, Data Integrity, Performance Enhancement, Secure Cloud Infrastructure, Policy-aware Placement.

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ABSTRACT: The present study was carried out from June 2023 to May 2024. During the study period water quality studied. Various quality parameters are measured including pH, air temperature, Water Temperature, DO, free. All water parameters are within the permissible limit and suitable for biodiversity. The result indicated and discussed.

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Key Words: Parameter, Lahanewadi temperature

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Conflict, social media, Combating Misinformation, Disinformation, fake news

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