Volume 11 | Issue 5 |

 Abstract

Background - Sudarshan Kriya Yoga (SKY) is a unique rhythmic breathing process advocated by Art of Living, Bangalore, India SKY is not practiced as a single technique but is integrated with asanas, pranayamas , meditations and attitude training. It has four distinct components. 1)Ujjayi" or "Victorious Breath" 2) Bhastrika or "Bellows Breath" 3) Om chanting 4) Sudarshan Kriya (Soham kriya) According to recent study done in 2021, prevalence of stress in undergraduate physiotherapy students is 94.4% Stress is associated with SNS (Sympathetic Nervous System)overactivity and PNS(Parasympathetic Nervous System) underactivity. Objective - Aims to find the effectiveness of Sudarshan Kriya Yoga(SKY) on stress in undergraduate physiotherapy students using Perceived Stress Scale (PSS10) after 4 weeks. Method - : Study begun with the presentation of synopsis to the ethical committee in PES MCOP. An approval was granted from the ethical committee .73 subjects were selected on the basis of inclusion and exclusion criteria. Pre PSS10 scores were taken .SKY technique was performed for 4 weeks .Post PSS10 scores were taken. Data entered and analysed. Results - There was significant effect of SKY technique on stress in undergraduate students (p<0.0001) Conclusion - This study concluded that there was significant effect of SKY technique on stress in undergraduate physiotherapy students after 4 weeks.

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stress, SKY technique, PSS10 score, undergraduate physiotherapy students

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The development of high-speed tableting equipment and the usage of direct compression techniques for tableting have increased the demands placed on excipients functionally day by day. a stable excipient with multifunctional activity can be developed with the help of co-processing. To create new, stable co-processed excipients, the combinations of one or two synthetic or natural polymers have been thoroughly investigated. Co-processing of plant-based components has benefited numerous pharmaceutical industries worldwide in recent years. The broad overview of co-processing, the methods used, and the benefits of utilising natural components in co-processing are highlighted in the current review paper. Additionally, current advancements in excipient technology are briefly highlighted, with a focus on natural combinations that could be employed as co-processed excipients.

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Co-processing, Spray drying, Macroporous, hygroscopicity, compressibility.

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A chatbot is a piece of intelligent software that can interact with users in a way that is similar to how a human might. Chatbots are utilised for client communication, social media marketing, and instant messaging.According to HubSpot research, 71% of people prefer using messaging applications for customer assistance. Because it is a rapid solution to their issue, chatbots have a promising future in business. We'll put in place a chatbot that can comprehend what the user is saying and respond appropriately. Algorithms like Natural Language Processing are used by chatbots.

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Chatbot, Deep learning techniques, HubSpot, Natural Language Processing

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Due to globalization, we have seen a worldwide trend towards frequent migration of people. In 21st century the desire to uproot and find a new place to live is both forced and choice. In other words, people may cross borders for political, economic, or even a combination of the two reasons. The advantages of emigrating to another country economically are amplified by unfavourable political situations. Challenges of acculturation and acclimatization connect with the search of better opportunities. M.G. Vassanji's, an eminent diasporic Canadian writer in his novel. No New Land discusses the struggle of Indian immigrants who left their country twice to fit in host nations like Africa and Canada.

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Migration, Cultural conflict, Immigrants, Multiculturalism

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ABSTRACT: Background: Acute ischemic stroke describes a Stroke is often referred to as a brain attack or "cerebrovascular Accident (CVA). A clot blocks a blood vessel that delivers oxygen and nutrients to the brain or bursts (or ruptures), resulting in a stroke. When this happens, brain cells in that location cannot get the blood (or oxygen) they need and perish. Alteplase and Tenecteplase are thrombolytic drugs used for ischemic stroke. Alteplase converts fibrinogen to the proteolytic enzyme plasmin, which lysis fibrin as well as fibrinogen Tenecteplase converts plasminogen to plasmin is increased relative to its conversion in the absence of fibrin. Methods: The study was carried out on 20 patients with AIS. The study was conducted by categorizing them into two groups, 10 patients were treated with Alteplase, and 10 patients were treated with Tenecteplase. The efficacy of Alteplase and Tenecteplase is assessed by using NIHSS and MRS. Health-related QOL of Alteplase and Tenecteplase was assessed using an SS-QOL questionnaire in patients with AIS. Anxiety and depression are assessed by HADS. The cost of both drugs is compared. Result: By using NIHSS and MRS it is assessed that Tenecteplase is more effective than Alteplase. The QOL in Tenecteplase patient show significant change as compared to Alteplase.

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Acute ischemic stroke, Tenecteplase, Alteplase, NIHSS, MRS, SS-QOL, HADS.

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Sapota (Manilkara zapota) is a tropical fruit tree that is native to Mexico, Central America, and parts of South America. This belongs to the family sapotaceace. The sapota fruit is a brownish, round or oval-shaped berry, about the size of a small apple, with a thin, rough, and grainy skin. The flesh is soft, creamy, and has a pleasant, musky flavor. The fruit contains many small, black, shiny seeds that are not usually eaten. It has the medicinal benefits like anti-inflammatory, helps in digestion, energy provider, source of antioxidants, it is good for bones, controls blood pressure. Sapota fruit is a good source of dietary fiber, vitamins A, C, and E, and minerals such as potassium, magnesium, and iron. This fruit is good for pregnant women The sapota tree is an evergreen tree that can grow up to 15-20 meters tall and has a dense, spreading crown of leaves.

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sapota, dietary fiber, phosporous

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Training and placement (TNP) are critical components of every educational establishment, where most of the work is done manually. Paper-based methods, databases, spreadsheets, and e-mail exchanges help to handle TNP activities. With paper and spreadsheet-based methods, it is difficult to manage the data and applications of all the students for every company in placement activity. In the traditional approach, the placement coordinators create forms and need to circulate them among the students to get applications. The application process for a company involves filling out student details forms which are repetitive as most details are static. The students face difficulty while tracking and managing all the applications they have made to various companies with a traditional spreadsheet-based approach. With the traditional approach, it is difficult for students to prepare for placement drives with vast content. The goal of the proposed work is to automate TNP activity. The main benefit of this proposed work is that it only requires a single registration. The proposed work will help the students in managing the applications. The chatbot is one of this system's essential components. This AI-assisted chatbot can help students with placement-related questions. In order to respond to and process the questions, this chatbot employs NLP and different ML models. The proposed work will provide a job posting facility that is much easier to work with. Filtering of students as per the company's eligibility criteria would also be achieved. Recommendations are made using the proposed work for the preparation of placement drives. Also, all the placed students can be tracked in a single place and statistics can be derived from the data of placed students.

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Automation, Artificial Intelligence, Chatbot, Machine Learning, NLP.

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The proposed work explores the potential of holographic projection technology and artificial intelligence (AI) to create a 3D holographic assistant that can be interacted with through speech-based input. The proposed system will assist users with a variety of tasks, such as communication, internet searches, video playback, weather updates, news, games, and reminders. Holographic projection technology, which allows for graphical interaction, is increasingly being used by multinational companies due to its complexity and versatility in various fields such as medicine, virtual reality, digital art, and security. The developed technique seeks to enhance the user experience by giving AI more control over the hardware, thereby making the virtual assistant more comfortable to talk to. The system uses a speaker, microphone, personal computer, extended display, and holographic projection setup to produce high-quality holograms and effectively transmit and receive video streams.

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Holograms, Holographic Artificial Intelligent Assistant, 3D Display, Interactive Display, Voice Assistant, pyttsx, Google API, Google Search.

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The integration of artificial intelligence in energy management has garnered significant attention due to its potential to revolutionize the way we consume, produce, and distribute energy. This paper presents a study on the impact of artificial intelligence on energy management, highlighting a revolutionary shift in the power industry. This study aims to shed light on the impact of artificial intelligence on energy management and pave the way for a more sustainable future. However, the objective of this study is to assess the potential of artificial intelligence and machine learning in transforming the energy industry. By leveraging artificial intelligence, energy management systems can optimize energy consumption, reduce waste, and enhance efficiency. The research delves into the ways in which AI is transforming the energy sector and the implications of this transformation for businesses and consumers alike. Through a comprehensive analysis of the latest trends and developments in AI-powered energy management, this study sheds light on the opportunities and challenges that lie ahead. By exploring the potential benefits of AI in optimizing energy consumption, reducing costs, and improving sustainability, this paper provides valuable insights for industry professionals and policymakers seeking to stay ahead of the curve.

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Artificial Intelligence, Energy Management, Power Sector, Smart Grid, Optimization

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This paper presents a flight delay prediction model using K-Nearest Neighbors (KNN) and Decision Tree algorithms. The model utilizes historical flight data to predict the likelihood of a flight being delayed. The KNN algorithm is used to identify similar flights in the past, while the Decision Tree algorithm is used to classify the flight based on its attributes. The model is trained and tested on a dataset containing flight information from a major airport over a period of several years. Results show that the KNN and Decision Tree algorithms are effective in predicting flight delays, with the Decision Tree algorithm outperforming the KNN algorithm in terms of accuracy. The proposed model has potential applications in the aviation industry, allowing airlines and airports to better anticipate and manage flight delays. This paper presents a flight delay prediction model using K-Nearest Neighbor (KNN) and Decision Tree algorithms. The model utilizes historical flight data, weather data, and airport information to predict the likelihood of a flight being delayed. The KNN algorithm is used to identify similar flights based on their characteristics, such as the airline, departure time, and destination, and predict the delay status based on the delays of the similar flights. The Decision Tree algorithm is used to create a rule-based model that predicts the delay status based on the most important factors contributing to delays. The model is evaluated using a dataset of flight information and weather data from a major airport, and achieves an accuracy of over 80% in predicting flight delays. The proposed model can assist airlines, airports, and passengers in making informed decisions and reducing the impact of flight delay.

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 Keywords

Python, Machine Learning, KNN Algorithm, Decision tree algorithm, Flight Delay Prediction.

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