The Metaverse is an emerging virtual universe that combines technologies such as VR, AR, AI, and IoT, to captivate the user in an artificial universe that blends reality and technology seamlessly. The metaverse provides a plethora of opportunities to vastly expand and realize the capabilities of our imagination as technology materializes ideas into intractable objects for an enhanced experience. The metaverse can also impact the education sector offering a unique opportunity to revolutionize education by providing immersive and interactive learning experiences through 3D avatars. In traditional libraries, students read books to learn about a vast array of topics and can visualize those topics through 2D images provided in the books, but such images might not always be the best stimulus to enhance the reader’s imagination. The introduction and integration of “Digital Libraries” through the Metaverse enable school students to explore various subjects in 3D environments, providing a practical approach to knowledge and improving comprehension, resulting in enjoyable and effective learning experiences. Metaverse enables seamless embodied user communication in real-time and dynamic interactions with digital antiquities. Besides, a digital library is defined as an online database of digital collections. It contains a lot of papers and resources which are arranged digitally. Its benefits include effectiveness, accuracy, authenticity assurance, simpler plagiarism management, easy accessibility, and high convenience. However, it has its drawbacks too such as copyright issues, distractions due to notifications, and various health hazards. In response to those drawbacks, how a digital library may use the Metaverse to add visual and auditory effects to enrich information provided in books has been illustrated, and how digital libraries in the Metaverse have the potential to revolutionize education while also addressing and potentially solving the problems that afflict traditional libraries has been highlighted by suggesting a prototype of the digital library in the Metaverse.

Now a days heart failure is one of the most common chronic diseases that cause death. As it possesses high risk of death, it is important to predict patient’s survival and optimize treatment strategies. Machine learning techniques have come to light as useful tools for evaluating enormous quantities of patient data and deriving important patterns and insights in recent years. The purpose of the study is to investigate the feasibility of using the machine learning methods for predicting heart failure patient’s chances of survival. We have worked on a dataset with 2029 heart failure patients and the dataset comprises 13 features. To conduct this research, we suggested a model (Stacked machine learning model using scikit-learn using Decision Tree, Naive Bias, Random Forest, Linear Regression, SVM, XGBoost, ANN) using which we got better results than previously existed researches. We believe the suggested model will help advance our understanding of heart attack prediction.