Volume 12 | Issue 10 |

 Abstract

In the subject of archaeology, especially in South Asia, Sir Alexander Cunningham (1814-1893) is considered a trailblazer by many. The foundation for the methodical investigation and conservation of old Indian legacy was established by his services. After being appointed as the first Director General of the Archaeological Survey of India (ASI) in 1861 and serving in that capacity until 1865, Cunningham's extensive career began. Under his direction, the ASI began systematically exploring and cataloguing India's archeological sites, laying the groundwork for an exacting standard of archaeological practice. By using exacting survey methods and creating an organized monument inventory, Cunningham's methodology helped discover and categorize a large number of sites and objects. His work was essential in locating and interpreting important Buddhist sites, such as the well-known Sarnath and Bodh Gaya, which are essential to comprehending the historical progression of Buddhism. Apart from his fieldwork, Cunningham made major contributions to the academic debate on South Asian archaeology through his scholarly publications, such as "The Ancient Geography of India" and other studies. He also pushed for the conservation of heritage places long before contemporary conservation procedures were formalized, which has contributed to their preservation and protection. This is an instructive study with an exploratory research approach. The current study examines Cunningham's contributions to the discipline of archaeology. Finally, the conclusion of this study enhance our knowledge of Cunningham's methodologies and provide valuable insights into the understanding the contribution in the field of archaeology.

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 Keywords

Alexander Cunningham, Archaeology, Methodology, Contribution

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In the world, breast cancer is the most frequently diagnosed malignant tumour in women and the leading cause of cancer-related deaths. Around the world, the prevalence of breast cancer is steadily rising. This is why it appears vital to search for novel therapeutic approaches as well as predictive and prognostic indicators, even in the face of advancements in its identification and treatment, which translate into improved mortality rates. Depending on the molecular subtype, different treatment plans apply. Treatment for breast cancer is interdisciplinary and involves systemic therapy as well as locoregional therapy (surgery and radiation therapy). Chemotherapy, antiHER2 therapy for HER2positive disease, hormone therapy for hormone-positive disease, and, more recently, immunotherapy are examples of systemic therapies. More than 15% to 20% of all cases of breast cancer are triple negative. Because of its high invasiveness and poor responsiveness to treatment, it poses a therapeutic challenge and is hence of great study interest. Anticipated treatment approaches for breast cancer seek to tailor care to each patient and adjust the dosage and intensity of care according to the cancer's biology and early response to treatment. The article gives an overview of the literature on breast carcinoma--a disease impacting women across the world.

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Risk Factor ,Classification , Sign and Symptoms ,Diagnosis ,Treatment.

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Gentrification, characterized by the influx of affluent residents and investments into historically marginalized neighborhoods that lead to the displacement of original residents, is a pressing urban issue. The findings of this research highlight the potential of predictive modeling to inform targeted interventions and support sustainable urban development. By identifying at-risk neighborhoods, policymakers can implement measures to mitigate displacement, promote affordable housing, and preserve cultural diversity. However, challenges such as data availability, model interpretability, and ethical considerations remain significant. Predictive modeling, particularly through machine learning, offers a promising approach to understanding and anticipating gentrification trends in U.S. cities. By analyzing various data points, these models can identify key indicators associated with gentrification, allowing policymakers to develop proactive strategies My study employs a supervised learning model, specifically Logistic Regression, to predict gentrification in select U.S. cities. The model achieved an accuracy rate of 72.5%, demonstrating its effectiveness in identifying areas susceptible to gentrification. Key variables influencing the model's predictions included income levels, educational attainment, housing vacancy rates, proximity to amenities, and crime rates.

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 Keywords

Gentrification, Predictive Modeling, Machine Learning, Urban Planning, Policy Interventions

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Pratishay, commonly referred to as rhinitis in modern medicine, is a prevalent condition characterized by inflammation of the nasal mucosa. This article explores the Ayurvedic understanding of Pratishay, its etiological factors, classification, symptoms, and treatments. Ayurveda, a holistic system of medicine from India, emphasizes the balance of doshas (body energies) and the importance of lifestyle and diet in maintaining health. This paper highlights the role of Vata, Pitta, and Kapha doshas in the manifestation of Pratishay and discusses various Ayurvedic remedies, including herbal formulations, dietary modifications, and lifestyle changes. Emphasis is placed on preventive measures and the integration of modern scientific understanding with traditional practices. The aim is to provide a comprehensive overview of Pratishay, facilitating a better understanding of its management through Ayurveda.

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Pratishay,rhinitis,doshas.

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Graph theory provides a robust framework for analyzing and understanding complex social networks, where nodes represent individuals and edges denote their interactions. This paper explores various applications of graph theory in social network analysis , focusing on network structure , community detection, influence modeling, and recommendation systems. We begin by discussing fundamental concepts such as centrality and network metrics, which help identify influential nodes and measure their impact. Next, we delve into algorithms for detecting communities within networks, enabling a deeper understanding of group dynamics and structures. Additionally, we examine how graphtheoretic approaches model the spread of information, behaviors, and trends, offering insights into viral phenomena and marketing strategies. Finally, the paper addresses the use of graph theory in enhancing recommendation systems through personalized content and friend suggestions. By integrating theoretical concepts with practical applications, this study demonstrates the value of graph theory in analyzing and optimizing social networks, ultimately contributing to more effective and insightful network-based solutions.

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Social Networks, Community Detection, Algorithms, Viral Phenomena.

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The purpose of this study is to compare the online and offline grocery shopping experiences and identify the advantages and disadvantages of each method. This study aims to provide a comprehensive understanding of the online and offline grocery shopping experiences and their impact on consumer behavior, satisfaction, and loyalty. The findings of this study may help grocery retailers to develop effective marketing strategies to attract and retain customers in an increasingly competitive market.

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Grocery shopping, Online shopping, Offline shopping, Growth, Advantage and Disadvantage.

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In the rapidly evolving landscape of online marketplaces, credibility has emerged as a cornerstone of consumer trust and decision-making. The digital age has transformed traditional shopping behaviors, with consumers increasingly relying on online reviews and ratings to guide their purchasing choices. Credibility in this context is multifaceted, encompassing the authenticity, reliability, and transparency of information provided by both sellers and previous buyers. Positive reviews and high ratings serve as powerful endorsements, validating product claims and enhancing consumer confidence. Conversely, negative reviews, while potentially detrimental to sales, contribute to a transparent and trustworthy marketplace by highlighting potential issues and fostering informed decision-making. The role of credibility extends beyond individual transactions, influencing the overall reputation of online platforms. Marketplaces that prioritize the integrity of their review systems and actively combat fraudulent activities are more likely to cultivate long-term consumer loyalty. This trust is built through consistent and genuine feedback mechanisms, where consumers feel their voices are heard and valued. The psychological concept of social proof plays a significant role here, as potential buyers are swayed by the experiences and opinions of their peers. This collective wisdom not only aids in product selection but also reinforces the credibility of the marketplace itself.

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Consumer credibility, Transparency, Fraud prevention, Customer ratings and reviews, Feedback mechanisms.

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Listening, the component of communication, pilots the activity of interaction through words. The participation in listening outwits the entire lifespan where the reaction towards the words comprehended matters a lot in the decision of their life tastes. Most often the circumstances are mishandled by the deprived listening. Competent communication is additionally troubled by the inefficient handling of the hearing activity. The ineffective handling of the controversial conversation turns out to be the topsy-turvy of their choices. The chances and the choices the listener make in the conversation decides the life story of the person. The study brings out the gaps in the communication through listening in the annals of Shakespeare's tragedies. It also asserts to the understanding that the tragical endings of all the heroes are the outcome of their ineffective listening. The introspection makes the clear proponent that misled listening causes the great fall in life.

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Communication; Listening; Introspection; Conversation; competency; Methods

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ABSTRACT Social media has become a daily habit in the lives of many people. People of all age groups participate in social media and an average Indian spends around 2.8 hours a day on this activity. People can express their concerns and share their thoughts on social media. When it comes to understanding social media, one must first understand the concept. Users can communicate with each other, share information, ideas, thoughts, photos and videos through online services called "social media". To access content, share content with other users of the social media platform, and chat with other users of the social media platform, one must first register for an account and then log in to the account. Facebook, Twitter, WhatsApp, Snap Chat, Telegram, and LinkedIn are just a few of the most popular and trending social networking sites today, especially because most of these social networking sites have a non-conformist user base. In India, youth between the ages of 13 and 19 constitute 35% of all social media users (Statista, 2022). The majority of Facebook and Instagram users in India are between the ages of 18 and 24. In this study, we take a descriptive and analytical stance while discussing social media and its good and bad impact on young people. We rely on MAXQDA, a multi-content analysis tool, to reach our conclusions. We discuss all aspects of social media, including its positive and negative impacts. We focus on specific areas such as business, education, society, and youth.

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Youth, Social Media, Society, Impact, Education etc.

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: This study explores the impact of Artificial Intelligence (AI) on the banking sector, focusing on its transformative role in enhancing the operational efficiency, customer services, and decision-making processes. AI technologies like machine learning, natural language processing, and robotic process automation, are gradually being integrated into banking operations to streamline tasks, improve risk management, and deliver personalized customer experiences. By analyzing the data collected from banking professionals, the research highlights the benefits and challenges of AI adoption, such as regulatory compliance, data privacy, and workforce adaptation. The findings suggest that while AI significantly enhances job performance and service delivery, successful implementation requires strategic planning, ongoing training, and a robust ethical framework. This study contributes to the understanding of AI's potential in reshaping the future of banking, providing insights for managers and policymakers aiming to leverage these technologies for competitive opportunity

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 Keywords

ARTIFICIAL INTELLIGENCE ., BANKING SECTOR

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