Volume 12 | Issue 10 |

 Abstract

The wireless technology demands efficient antenna which could radiates at multiple frequencies. The 2x2 MIMO system has been developed, analyzed, designed and presented. The FR4 material has been utilized as a substrate to consider the proposed structure for cost effective industry applications. The slots are created over the top surface of the presented antenna. This will increase the current distribution and exhibits the optimum radiation. The partial ground plane is created to achieve the Ultra Wide Band (UWB) response from the presented MIMO system. When a couple of radiators are positioned nearer to each other, there is a mutual coupling effect which significantly drop down the antenna performance. To reduce this effect, isolating geometry has been engineered and united with the ground plane. The output parameters such as ECC, CCL and MEG were received and presented. The values of output parameters and reflection coefficient make the antenna suitable for WiMAX, WLAN and C band communications.

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 Keywords

MIMO, wireless communications, UWB antenna

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Ksharasutra is a widely used Ayurvedic technique for treating fistula-in-ano and hemorrhoids. Traditionally prepared using Snuhi ksheera, Apamarga Kshara, and Haridra, the preparation has evolved with advancements such as Guggulu and Papaya-based Ksharasutras. These innovations aim to enhance therapeutic outcomes, reduce discomfort, and provide year-round accessibility. This review discusses traditional and alternative preparation methods, their clinical efficacy, and the role of modern formulations in enhancing Ksharasutra therapy and also historical evolution of Ksharasutra, its development through centuries, multifaceted mechanisms underlying Ksharasutra's effectiveness, including mechanical strangulation, chemical cauterization, and localized drug delivery and its modern application.

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 Keywords

Ksharasutra, Guggulu, Fistula-in-ano, Hemorrhoids, Parasurgical, Ayurveda

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Creative Commons Attribution 4.0 and The Open Definition

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Web of Things (IoT) with profound learning (DL) is definitely developing and assumes a critical part in numerous applications, including clinical and medical care frameworks. It can assist clients in this field with getting a benefit as far as upgraded touchless verification, particularly in spreading irresistible illnesses like Covid sickness. To beat these issues, IoT-based keen control clinical validation frameworks utilizing DL models are proposed to improve the security element of clinical and medical services puts actually. This work applies IoT with DL models to perceive human appearances for verification in savvy control clinical frameworks. We use Raspberry Pi (RPi) on the grounds that it has minimal expense and goes about as the principal regulator in this framework. The subsequent step is the characterization step which should be possible utilizing a help vector machine (SVM) classifier. Just ordered face as veritable prompts open the entryway; in any case, the entryway is locked, and the framework sends a notice email to the home/clinical spot with identified face pictures and stores the recognized individual name and time data on the SQL data set.

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Face (M/F), Recognition, Bot, IoT, SQL data set, vector machine, validation, camera module.

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Abstract This paper explores the transformation of India's tax system since the early 1990s, driven by significant changes in tax policies across various countries. It evaluates the introduction of novel direct and indirect tax structures, examining their impact on revenue and fairness. The analysis also highlights the accomplishments and challenges encountered during their implementation. In conclusion, the paper underscores that, despite eight years of reform efforts, enhancing India's tax system remains a formidable task.

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 Keywords

Keywords: tax reform, india taxation, revenue impact

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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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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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Creative Commons Attribution 4.0 and The Open Definition

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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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Creative Commons Attribution 4.0 and The Open Definition