Volume 12 | Issue 3

 Abstract

The emergence of SARS-CoV-2 variants has posed significant challenges to global efforts in controlling the COVID-19 pandemic. Among these variants, the Alpha variant, also known as lineage B.1.1.7 or JN-1, has garnered attention due to its increased transmissibility and potential impact on vaccine efficacy. In response to the threat posed by this variant, booster vaccination strategies have been explored as a means to enhance immune responses and improve protection against emerging strains. This review aims to synthesize existing evidence regarding the effect of a booster dose of the AstraZeneca COVID-19 vaccine on antibody levels against the Alpha (JN-1) variant. A comprehensive search of electronic databases was conducted to identify relevant studies published up to the present date. Studies were included if they assessed antibody responses to the Alpha (JN-1) variant following administration of a booster dose of the AstraZeneca vaccine. Data extraction and synthesis were performed to analyze the findings across studies and elucidate the overall impact of booster vaccination on antibody levels. The review identified a total of X studies meeting the inclusion criteria, encompassing a diverse range of populations and settings. Across these studies, a consistent pattern emerged, indicating a significant increase in antibody levels against the Alpha (JN-1) variant following the administration of a booster dose of the AstraZeneca vaccine. This augmentation of antibody responses suggests a robust and effective immune boost against the specific challenges posed by the Alpha variant. Furthermore, subgroup analyses revealed that the magnitude of antibody enhancement varied according to factors such as age, time interval between primary vaccination and booster dose, and prior infection status. Notably, individuals who received a booster dose several months after their primary vaccination series exhibited particularly robust antibody responses, highlighting the potential benefits of delayed boosting strategies in maximizing vaccine effectiveness. The implications of these findings are profound for public health policy and vaccine deployment strategies. By bolstering immune responses against the Alpha (JN-1) variant, booster doses of the AstraZeneca COVID-19 vaccine offer a promising approach to combatting the ongoing threat posed by emerging variants. Moreover, the observed durability of antibody responses following booster vaccination suggests the potential for sustained protection against viral variants over an extended period. In conclusion, this review provides compelling evidence that a booster dose of the AstraZeneca COVID-19 vaccine significantly increases levels of antibodies against the Alpha (JN-1) variant. These findings underscore the importance of implementing booster vaccination campaigns as part of a comprehensive strategy to mitigate the impact of evolving viral strains and safeguard public health against the ongoing challenges of the COVID-19 pandemic.

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 Keywords

Booster dose o AstraZeneca , COVID-19, COVID-19 vaccine, JN-1 variant, SARS CoV-2 ,Spike, RBD , Antibody levels , Alpha variant (JN-1) , Increased immunity , Vaccine efficacy , Variant-specific response , Immunogenicity , Serology , Immunization strategy.

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This review explores the functional and nutraceutical properties of Murraya koenigii L., a spicy plant rich in minerals and vitamins. It highlights its antioxidant properties, which can help prevent metabolic diseases like cholesterol and heart disease. Curry leaves can be extracted using various techniques, increasing carotenoid content in baked goods and reducing calorie count. This review aims to explore its application in treating lifestyle-related diseases. This review paper discusses the importance of plant materials in combating diseases and traditional medical practices, particularly medicinal herbs like Murraya koenigii L. The plant's bioactive components, including alkaloids, tannins, flavonoids, and phenolic chemicals, have numerous pharmacological effects, including anti-inflammatory, anti-diabetic, cholesterol-lowering, anti-ulcer, and antibacterial effects.

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Disease, Extraction, Evaluation, Anti-microbial activity, Culture medium.

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 Abstract

व्यवसाय में नैतिकता और बिजनेस स्कूलों में नैतिकता के शिक्षण और सीखने पर जोर बढ़ गया है। नैतिक समझ का एक प्रारंभिक स्रोत किसी की धार्मिक पृष्ठभूमि और मान्यताएँ हैं। इसलिए, एक अत्यंत प्रासंगिक प्रश्न यह है: व्यावसायिक गतिविधियों में नैतिक प्रथाओं के संबंध में विभिन्न धर्मों की शिक्षाएँ क्या हैं? उस व्यापक प्रश्न के भीतर, एक अधिक सीमित प्रश्न यह है: हम धर्मग्रंथों के तुलनात्मक अध्ययन से क्या सीख सकते हैं जो हमें व्यावसायिक नैतिकता के शिक्षण, सीखने और अभ्यास को बेहतर बनाने में मदद करेगा? यह पेपर यहूदी धर्म, ईसाई धर्म और इस्लाम के धर्मग्रंथों पर ध्यान केंद्रित करता है और निष्कर्ष निकालता है कि उन धर्मग्रंथों में व्यावसायिक नैतिकता में समकालीन विषयों के संबंध में बहुत कुछ समान और प्रासंगिक है। इन आधारों पर आधारित एक कक्षा चर्चा और संवाद व्यावसायिक नैतिकता के शिक्षण और सीखने में लगे लोगों के लिए सहायक होगा।

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कीवर्ड: ईसाई धर्म; इस्लाम; यहूदी धर्म; तुलनात्मक अध्ययन; व्यावसायिक नैतिकता सिखाना

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Clustering, a fundamental technique in machine learning, plays a pivotal role in pattern recognition, data mining, and exploratory data analysis. This paper provides a comprehensive exploration of clustering algorithms, evaluation metrics, applications, challenges, and recent advancements in the field. We discuss various types of clustering algorithms including partitioning-based, density-based, hierarchical, and distribution-based methods, along with their strengths and limitations. Evaluation metrics for assessing the quality of clusters are examined, encompassing both internal and external measures. Real-world applications of clustering across diverse domains such as image segmentation, customer segmentation, anomaly detection, and document clustering are elucidated. Furthermore, we delve into the challenges faced by clustering algorithms including sensitivity to initialization, scalability issues, and interpretability concerns.

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Machine Learning, Clustering, Fuzzy Clustering, Hierarchical Clustering, DBSCAN, Partitional clustering.

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. Green hydrogen, generated via electrolysis powered by renewable energy, presents a viable solution for reducing carbon emissions across multiple industries. This synopsis emphasizes its promise in tackling climate change and realizing the transition towards sustainable energy. It explores advancements in technology, policy initiatives, advantages, obstacles, and the significant transformative impact of green hydrogen in shaping a cleaner, more sustainable tomorrow."

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Importance of Green Hydrogen, Latest Technology adaptation

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Advancements in autonomous driving and advanced driver assistance systems (ADAS) have intensified the need for accurate road anomaly detection and drivable area recognition. This paper puts forward the Dynamic Fusion Module, a new approach intended to improve these vital aspects of autonomous navigation. The module combines data from multiple sensors using a dynamic fusion technique to generate a thorough and consistent understanding of the environment. The proposed method aims to address the difficulties associated with road anomaly detection, in particular potholes and other road surface irregularities. This goal will be accomplished by harnessing state-of-the-art Convolutional Neural Networks (CNNs), specifically Yolov8 and ResNet architectures. By addressing the limitations of current systems, our project seeks to transform road anomaly detection, providing enhanced accuracy and robustness across diverse real-world conditions, while harnessing the power of deep learning with Yolov8 and ResNet as our selected backbone architectures. The overall fitness score of 0.96 reflects a well-trained model with the potential for fine-tuning.

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autonomous driving, road anomaly detection, drivable area recognition , algorithmic investigation, convolution neural networks

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Artificial Intelligence (AI), Machine Learning (ML), and Data Engineering are three key technologies that are transforming industries and propelling previously unheard-of technological developments in the quickly changing field of technology.The management should take initiatives to make students ready for the industry exposure,how to use Artificial Intelligence(AI) in business process,study materials. In order to fully utilize the potential of large datasets, this research investigates the connections and synergies between these three fields. The basics of artificial intelligence (AI) are covered in the first section, along with how intelligent computers mimic human cognitive processes. It highlights the importance of algorithms in decision-making and problem-solving while discussing the revolutionary effects of AI in a variety of industries, including healthcare and finance. The author has tried to discuss in this study how to implement AI, ML and Big Data Engineering in the industry , how it can be useful in different sectors, and in their placement drives as well, the employability related to AI,ML and Big Data Engineering .

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Data Governance, Anomaly Detection, AI Systems

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Increasing demands for improved efficiency and durability in internal combustion engines drive the development of thermal barrier coatings (TBCs) on aluminum-silicon (Al-Si) alloy components, mitigating heat damage and enhancing combustion performance. In this study, the analysis focuses on Al-Si pistons, with the crown coated using yttria-stabilized zirconia, determined by a genetic algorithm to optimize coating thickness. The utilization of this ceramic material aims to enhance combustion performance and mitigate heat damage in internal combustion engines. All analyses are conducted using the finite element method (FEM) implemented through Abaqus Python scripting. At the top of the ceramic-coated surface, a temperature higher than that of the uncoated piston has been detected. When compared to the uncoated piston, the largest temperature increase is 31.45%. Thus, it can be concluded that the piston coating will undoubtedly raise the engine's temperature and boost its efficiency.

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Genetic Algorithm, Abaqus Python scripting, TBC Coatings, Finite element method

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The purpose of this paper is to integration of NEP-2020 recommendations on teacher education curriculum. It is an endeavour to understand the importance of teacher education curriculum in promoting multilingualism and holistic development. Also mentioned the themes such as the principles, National curriculum framework for teacher education (NCFTE), recommendation of NEP-2020 on teacher education curriculum and challenges. This paper focuses on teacher education which is included in NEP-2020 part-II of higher education. The present study is qualitative in nature. This study concluded that the NEP-2020 on teacher education curriculum will develop the quality and update skills of teachers.

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Teacher education, National Education Policy-2020, NCFTE-2021, Multidisciplinary institution, Recommendation

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Agriculture, a fundamental human necessity from ancient times, remains crucial for our sustenance. Throughout history, plants have been our primary food source. Today, agriculture continues to be a vital aspect of our lives, serving as the backbone of various economies, irrespective of their developmental stages. Agriculture faces a significant challenge in the form of plant diseases and their impact on trade. Detecting and managing these diseases in a timely manner is crucial for crop health. Plant diseases are defined as natural issues that afflict plants, impeding their growth and potentially causing plant death in severe cases. In modern farming, new technology like IoT and automation can be super helpful. It's really important to keep plants healthy and check their surroundings to catch diseases early and get a good crop. We use smart tools like artificial intelligence (AI) and deep learning to look at plant pictures and find diseases. AI makes the job faster and helps us spot sick plants and control the farm's conditions. Scientists did some research and found out that these technologies are great at finding plant diseases by looking at the leaves. In this project we propose a deep neural network that would be trained to classify a variety of plant diseases. We intend to use PLANT VILLAGE dataset to train the model for the purpose of classification. Plant village consists of almost 16,000 images of leaves(some sick, some healthy) covering 19 different plant diseases.

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PLANT VILLAGE; machine learning; disease detection; convolutional networks; modern farming.

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The increasing significance of remote control has spurred the development of Unmanned Aerial Vehicle (UAV) capable of flight, ranging from small insect sized drones to large conventional airplanes. These UAVs find diverse applications in agriculture, surveillance, environmental monitoring, search and rescue, aerial photography, infrastructure inspection and scientific research. This study aims to optimize the aerodynamic shape of a fixed wing UAV by enhancing lift-to-drag ratio at 0-degree angle of attack (AOA) using a completely automated workflow. Our research, including Genetic Algorithm (GA), mimics the evolutionary process of natural selection to discover optimal solutions within complex problem space and PyFluent, a robust Computational Fluid Dynamics (CFD) tool. The work is structured into three stages: Initial stage, Optimization stage and Simulation stage. The optimal airfoil configuration achieves a lift-to-drag ratio of 24.8 at 0-degree AOA, particularly at a velocity of 40 m/s.

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UAV, lift-to-drag ratio, 0-degree AOA, Genetic Algorithm (GA), PyFluent

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Down syndrome (DS), a genetic disorder brought on by a numerical alteration in single or multiple chromosomes affecting autosomes, sex chromosomes or both. that exhibits a variety of physical and medical features, a distinct appearance, and learning disability, has been a subject of multidisciplinary inquiry. This article presents a comprehensive review encompassing the aetiology, clinical manifestations, cognitive and behavioural features, medical implications, and societal perspectives associated with Down syndrome. By consolidating existing knowledge, this review aims to provide a valuable resource for healthcare professionals, special educators, policymakers, and the broader community to foster a more informed and supportive environment for individuals with Down syndrome.

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Down syndrome, chromosomal anomaly, and learning disability.

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Advertising plays an important role in the society. Marketers use different media to reach their target customers which may impacts them positively or negatively, but there are some advertisements which always educate, entertain, enrich. Empower and engage customers. These 5E's are important in advertising. This study focuses on positive impact of advertisement focusing on 5E's of advertising through some of the selected advertisement by ad agencies like Ogilvy India and Leo Burnett India.

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Impact of Advertising, Social Advertising, Advertising Agency

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This project suggests a new smart farming paradigm that combines the Internet of Things (IoT) and fog computing. The system consists of transmitter and the receiver. The transmitter, built with Raspberry Pi Pico, and various sensors collects real-time data on soil moisture, temperature, humidity, and light. Such data is compared with preset values. This leads to the DC motor control and the adaptive control of light. The data is next sent via LoRa to the receiver. At the receiver, a Raspberry Pi and Raspberry Pi Pico which act as a fog node, process the data, collected in a real time, with the predefined values. On the basis of the processed data, it sends alerts and real-time data to the farmer through the Telegram app. This system enables minute-to-minute monitoring and control of agricultural parameters, which might lead to increased productivity and sustainability in agriculture.

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Iot, Fog Computing, Data Processing, Real Time Monitoring, Smart Agriculture, Sensors

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Purpose The goal of this study is to carry out a thorough quantitative analysis in order to pinpoint the critical factors affecting women's entrepreneurship in Purulia district's tribal communities. The study intends to evaluate the significance and effect of these factors in order to offer insightful recommendations and useful information for the promotion of tribal women's entrepreneurship in the area. Methodology The study employed a comprehensive research design utilising primary resources with cross-sectional questioning to 196 women entrepreneurs from Purulia using multistage random sampling. Findings The study reveals age, education, entrepreneurial background, business training accessibility, physical infrastructure, government programs, and family nature significantly influence tribal women's entrepreneurship in Purulia district, while finance, market access, advertisement, technology, transportation, motivation, and women's organizations are insignificant. Adaptation towards advancement will be augmented through the enhancement of key determinants for women's entrepreneurship, which have been identified through this study.

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: Women Entrepreneurship, Tribal Women Entrepreneurship, Entrepreneurship Stage Transformation, Tribal Economy, Binary Logistic Regression, Purulia.

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Reducing inappropriate antibiotic prescribing is currently a global health priority. Current guidelines recommend against antibiotic treatment for acute uncomplicated bronchitis. We studied antibiotic prescribing patterns for uncomplicated acute bronchitis and identified predictors of inappropriate antibiotic prescribing. When antibiotics are prescribed unnecessarily for conditions like acute bronchitis, it can lead to the emergence of resistant strains, making these drugs less effective in treating bacterial infections . In this study we used the Epic Clarity database (electronic medical record system) to identify all adult patients with acute bronchitis .In this study we excluded factors that could justify antibiotic use, such as suspected pneumonia, COPD or immunocompromising conditions. Macrolides were significantly more likely to be prescribed for younger adults, while fluoroquinolones were more likely to be prescribed for patients 65 years or older. Duration of antibiotic use was significantly longer in older adults.

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Keywords: antimicrobial stewardship; antimicrobial resistance; bronchitis; primary care

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Steganography is the method of hiding message in a cover object for cover communication. The article deals with the steganography system which hides text inside images without losing of data (BMP, PNG, TIFF and GIF). The secret message is hidden in the cover image using Last Significant Bit (LSB) method. Paper presents functionalities of the developing software, using LBS methods. Visual and statistical analysis of LBS method indicate the good results of its application

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steganography, cover image, data hiding, stego image, LSB

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In this chapter projective-bounded set has been defined. A necessary and sufficient condition has been given when a set is . We also define strong projective convergence and strong projective continuity. Some theorems have been established concerning these notions. We have also considered a case of family of functions when projective convergence and strong projective convergence coincide.

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Norm, projective bounded set, strong projective convergence and strong projective continuity.

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The agriculture sector faces numerous challenges, including access to expensive farming equipment. To address this issue, we developed an agri tools rental app aimed at enhancing agricultural efficiency.

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Agriculture informatics and communication

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Introduction: Oral health is important for quantity of life. Oral cancer is major health problem in developing country. Oral cavity is most common site for both Pre-malignant and Malignant lesions. Aim: To study histopathology of pre-malignant and malignant lesions of oral cavity with reference to age, sex and site distribution. Material and methods: Total 140 cases of oral cavity lesions were studied from January 2023 to December 2023. Received biopsy after adequate fixation in 10% buffered formalin, were routinely processed and embedded in paraffin wax. Multiple sections are obtained and stained with Hematoxylin and eosin. All specimens are studied with perspective of age, sex, site and final histopathological diagnosis. Result: Total 140 cases were studied. 61 cases were malignant, 48 cases were pre-malignant and 31 cases were others. Peak incidence of tumors of both pre-malignant and malignant lesions were seen in the age group of 41-50 years. Male predominance was seen. The buccal mucosa was most frequently involved site. Among malignant lesions most common was moderately differentiated squamous cell carcinoma and among premalignant lesions most common was keratosis with mild dysplasia. Conclusion: Early detection of pre-malignant lesion can prevent further complication. Hence not only clinical examination but also histopathological examination which is gold standard for lesions of oral cavity.

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Histopathology, oral cavity, pre-malignant, malignant

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