Volume 12 | Issue 8 |

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premature, ultrasonography, transient tachypnoea of the newborn, respiratory distress.

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Sahitya Aur Cinema Mein Ram: Ek Adhyayan

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Sahitya Aur Cinema Mein Ram: Ek Adhyayan

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Abstract: This comprehensive study delves into the intricate interplay between law, macroeconomics, and economic reforms in the context of India, shedding light on a complex landscape of challenges and opportunities. Findings reveal that while India's legal framework often proves cumbersome and bureaucratic, it has the potential to either facilitate or hinder the implementation of crucial economic reforms. Inefficient enforcement, political consensus-building, social equity, and regional disparities are among the challenges observed. However, proactive dialogue with political stakeholders, streamlined legal processes, and investments in infrastructure and social safety nets can pave the way for sustainable growth and enhanced economic efficiency. Integrating sustainability goals, improving data collection and research, and actively engaging in global trade dynamics are also recommended strategies. As India continues its path to economic development, addressing these challenges while capitalizing on its strengths will be pivotal for fostering a prosperous and equitable future.

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Economic Reforms, Challenges, Efficiency, Sustainability, Governance

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Technological advancements have brought new tactics and capabilities that violate established international humanitarian law (IHL) norms, resulting in a dramatic shift of modern conflict. This article explores the impact of technology on humanitarian law in contemporary combat, focusing on autonomous weapons systems, drones, cyberwarfare, artificial intelligence, robotics, nanotechnology, etc. These technological advancements raise grave concerns about public safety, legal compliance, and ethical issues. Through an analysis of current problems and the recommendation of practical solutions, this study seeks to improve understanding of how humanitarian law might be modified to regulate and mitigate the risks connected with technology warfare. Modern technological warfare presents new challenges for international humanitarian law (IHL), which has its historical roots in the ideas of proportionality in the use of force, the separation of combatants and non-combatants, and the humane treatment of captives and civilians. The technology that has quickly advanced and gained widespread use such as drones, cyberwarfare instruments, and autonomous weaponry systems has altered the character of armed conflict and raised significant ethical, legal, and practical issues. Drones, for instance, have revolutionized military operations by enabling pinpoint strikes and lowering the hazards to military people. On the other hand, there are concerns over unlawful monitoring, specific killings, and harm to civilians due to mistargeting or misuse. Similarly, conventional notions of what defines warfare and who is accountable under existing legal systems are called into question by the capacity to launch cyberattacks on essential infrastructure and civilian services. This paper examines these concerns critically in order to address the humanitarian implications of technological warfare. It offers remedies like as increased regulatory oversight, moral guidelines for the creation and application of technology, and international collaboration. By encouraging discussion and raising awareness of these challenges, this study hopes to promote advocacy and policy development campaigns that defend humanitarian principles against the realities of contemporary conflict.

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Technological warfare, humanitarian law, drones, Artificial Intelligence, Robotics, Nanotechnology, cyber warfare, autonomous weapons etc.

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Artificial intelligence (AI) has emerged as a disruptive force in the global corporate landscape, affecting strategy, operations, and competitive dynamics. This paper investigates the multifaceted impacts of artificial intelligence (AI) technologies on general corporate strategies, day-to-day business operations, and the overall state of the economy. These technologies include machine learning, computer vision, and natural language processing. As organizations use AI more and more, a new era of data-driven decision-making is emerging; this time, data is positioned as a strategic asset rather than as a byproduct of business operations. This paper examines how AI can transform organizations through real-world case studies, industry trends, and best practices. It also offers suggestions for navigating the complex digital landscape. Positive outcomes include increased productivity, better decision-making, and tailored consumer experiences; however, the report also highlights drawbacks such as job displacement, moral quandaries, and security risks. The synthesis of fifteen carefully selected articles from the literature review provides a thorough understanding of the evolving nature of work, emphasizing the significance of dynamic skills, ethical considerations, and societal implications. The application of theoretical frameworks and methodologies contributes to a comprehensive discussion by highlighting the revolutionary potential and limitations of artificial intelligence (AI) in the business domain. This paper aims to help organizations understand AI's continuous evolution and strategically adapt to it in order to ensure continued innovation and competitiveness.

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Artificial Intelligence, Business Strategy, Business Operations, Economy, Automation, Workforce Dynamics, Ethical Considerations, Security Risks.

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This research paper explores the use of Gothic elements in 19th-century literature, focusing on the seminal works of Mary Shelley, Bram Stoker, and Edgar Allan Poe. Gothic literature, characterized by its use of the supernatural, the uncanny, and the exploration of human psychology's darker aspects, played a crucial role in the literary landscape of the 19th century. This paper aims to delve into how Shelley's "Frankenstein," Stoker's "Dracula," and Poe's selected works such as "The Fall of the House of Usher" and "The Tell-Tale Heart" incorporate and enhance Gothic themes. The analysis begins with Mary Shelley's "Frankenstein," examining themes of isolation, ambition, and the grotesque, highlighting how Shelley uses the supernatural and scientific experimentation to evoke terror and moral contemplation. Next, the paper analyzes Bram Stoker's "Dracula," focusing on themes of fear of the unknown, the supernatural, and the battle between modernity and ancient evil. Stoker's portrayal of Dracula as the quintessential Gothic villain is explored, alongside the novel's setting and symbolic use of Gothic motifs. Edgar Allan Poe's works are then scrutinized for their portrayal of madness, death, and decay, with a particular focus on his unique narrative style and psychological depth. The paper concludes by comparing the Gothic elements across these authors, identifying common themes and stylistic approaches while also noting their individual contributions to the genre. The study demonstrates that Shelley, Stoker, and Poe not only defined the Gothic tradition but also expanded its boundaries, leaving a lasting impact on literature. Their works continue to resonate with readers and influence contemporary Gothic literature, underscoring the timeless nature of Gothic themes in exploring human fears and societal anxieties.

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Exploration of Gothic Elements in 19th Century Literature

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This case study used numerical modeling with the finite element method to analyze the slope stability of a 28-meter-high railway embankment. With a 25-ton axle loading, PLAXIS 2D CE V21 was used to calculate the factor of safety. SQ2 type soil, which has fines ranging from 12% to 50%, was used for the embankment and is abundant at the project site. Railway embankment modelling is done using field test data. rigidity The parameters of the various rail way track components were thoroughly examined. Put in place After the embankment was constructed, the results of the deformation and factor of safety were given. In the analysis, soil models for the various embankment sections were incorporated. The Mohr-Coulomb soil model was used to model the subgrade, whereas the rail and sleeper were made of linear elastic. The element of safety was significantly impacted by the SQ2 type soil's effective cohesiveness. On failure, nonetheless, it exhibits significant deformation, for which blanket material was placed beneath ballasts. Adding turf on the side slopes improved stability even more. This study involved step-by-step modeling on PLAXIS 2D CE V21.

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RVNL: Rail Vikash Nigam Limited UTS: Ultimate Tensile Strength PSC: Pre-Stress Concrete FEM: Finite Element Method RDSO: Research Designs and Standards Organization LEM: Limit Equilibrium Method CBR: California bearing ratio MDD: Maximum dry density OMC: Optimum Moisture Content FOS: Factor of Safety BC SOIL: Black Cotton Soil SPT: Standard Penetration Test Es : Young's modulus ? : Poisson's ratio, c' : Effective cohesion, ?' : effective friction angle, and ? : Dilatancy a

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The proliferation of social media platforms has transformed global communication, enabling real-time sharing of information and connecting individuals across diverse geographies. However, this digital revolution has also facilitated the rise of cyberbullying, a pervasive issue that significantly impacts individuals' mental health and well-being. In the big data era, the sheer volume and velocity of data generated on social media present both challenges and opportunities for cyberbullying detection and prevention. This study explores the application of machine learning algorithms to predict and detect cyberbullying on social media platforms. Leveraging vast datasets from various social media sources, we employ advanced data preprocessing techniques, including natural language processing (NLP) for text normalization, sentiment analysis, and feature extraction. To address the challenge of imbalanced data, we utilize oversampling, undersampling, and synthetic data generation methods. We develop and compare multiple machine learning models, including supervised learning algorithms (Support Vector Machines, Logistic Regression, Random Forests) and deep learning architectures (Recurrent Neural Networks, Long Short-Term Memory networks, Convolutional Neural Networks, and Transformers). These models are evaluated using metrics such as accuracy, precision, recall, F1-score, and ROC-AUC to determine their effectiveness in detecting cyberbullying. Our findings demonstrate that machine learning algorithms, particularly deep learning models, exhibit high accuracy and precision in identifying cyberbullying patterns in text and multimedia content. We highlight the importance of continuous learning and model updating to adapt to evolving language and behavior on social media. This research underscores the potential of machine learning in enhancing the safety and security of online environments. By providing real-time monitoring and automated detection capabilities, these systems enable timely intervention and support for victims of cyberbullying. Additionally, the insights gained from analyzing social media interactions can inform the development of robust policies and educational programs aimed at preventing cyberbullying. The study also addresses ethical considerations, emphasizing the need for privacy-preserving techniques, bias mitigation, and compliance with legal standards. By advancing the field of cyberbullying detection through machine learning, we contribute to creating safer, more inclusive digital communities and promoting positive online interactions.

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Cyberbullying Prediction, Social Media Analytics, Big Data, Machine Learning Algorithms, Natural Language Processing (NLP), Sentiment Analysis, Text Classification, Online Harassment Detection, Data Mining, Supervised Learning, Feature Engineering, Support Vector Machines (SVM), Random Forest, Neural Networks, Deep Learning, Social Network Analysis, Data Pre-processing, Model Evaluation, Real-time Monitoring, Behaviour Analysis.

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One of the main concerns for structures built on sandy soils is soil liquefaction. Liquification is the process by which tightly packed, damp granular soil near the ground's surface loses strength from severe ground trembling. Existing structures fall as a result of this phenomenon, taking lives and property with them. Thus, while constructing a foundation, it is essential to comprehend the zone of liquefaction at a particular area. In light of this, a sand-rich location in Kolkata's Sonarpur neighborhood has been chosen for the current study. The goal of the current study is to assess the soil's liquefaction potential using the SPT and CPT methods in Sonarpur, which is close to Kolkata. It has been determined how resistant soils are to liquefaction, measured in terms of the cyclic resistance ratio (CRR). The article highlights the site's distinctive liquefaction zone, which may be taken into consideration when constructing the geotechnical foundation there.

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Liquefaction Potential , SPT,CPT

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At the Market on Morality is a story in a short story book called "Ombasini" (The Last Night Morning). Urkhaogwra Brahma has was written the book in 2001. The subject of the short story in the Morality Market is written about the meeting of the public store. Where all kinds of morality are found. It includes politics, economics, business, education, and personality. There is also the morality of status in various languages. It is to them that the story is narrated. The story can be said to have had an indirect impact on political business. This is because the morality market has seen all kinds of morality. It is taken up for discussion here. This meeting was replaced by a theatre. Where the store is compared to the theatre. Hence, the narrative style has been neglected by the narrator.

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Language, Politics, Business, Education, Personality Morality

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