Abstract
Fake news spreads rapidly, creating issues and making detection harder. The purpose of this study is to determine if fake news contains sentiment polarity (positive or negative), identify the polarity of sentiment present in their textual content and determine whether sentiment polarity is a reliable indication of fake news. For this, we use a deep learning model called BERT (Bidirectional Encoder Representations from Transformers), trained on a sentiment polarity dataset to classify the polarity of sentiments from a dataset of true and fake news. The findings show that sentiment polarity is not a reliable single feature for recognizing false news correctly and must be combined with other parameters to improve classification accuracy. © 2024 The Author(s). Published by Elsevier B.V.

Abstract
This study was initiated at a time of unprecedented uncertainty, as lecturers and educational institutions across the world tried to manage the move to online education as a result of the global COVID-19 pandemic. It started with lecturers' perspectives of their performance during that time to identify innovative teaching strategies beyond the priority of emergency teaching. The main goal was to identify the occurrence of more permanent changes in Higher Education after the pandemic. The research was based on a qualitative approach where faculty members were interviewed about their activities before, during and after lockdown periods. Data collected was analysed with the help of an algorithm based on Artificial Intelligence. Ultimately, it was possible to gather and evaluate practical solutions related to hybrid learning in Europe, Australia, and New Zealand, leading to recommendations for stakeholders in Higher Education.

Abstract
Educational chatbots are digital tools designed to assist learners in various educational settings. These chatbots use natural language processing (NLP) and machine learning algorithms to simulate human conversation and respond to user queries in a way that facilitates learning. They can be integrated into various educational platforms such as learning management systems, educational apps, and websites to provide learners with a personalized and interactive learning experience. Our paper discusses different scenarios for educational purposes and suggests in total four scenarios for educational needs.

Abstract
Application execution requests in cloud architecture and fog paradigm are generally heterogeneous in terms of contexts at the device and application level. The scheduling of requests in these architectures is an optimization problem with multiple constraints. Despite numerous efforts, task scheduling in these architectures and paradigms still presents some enticing challenges that make us question how tasks are routed between different physical devices, fog, and cloud nodes. The fog is defined as an extension of the cloud, which provides processing, storage, and network services near the edge network, and due to the density and heterogeneity of devices, the scheduling is very complex, and, in the literature, we still find few studies. Trying to bring innovative contributions in these areas, in this paper, we propose a solution to the context-aware task-scheduling problem for fog paradigm. In our proposal, different context parameters are normalized through Min-Max normalization, requisition priorities are defined through the application of the Multiple Linear Regression (MLR) technique and scheduling is performed using Multi-Objective Non-Linear Programming Optimization (MONLIP) technique. The results obtained from simulations in the iFogSim toolkit, show that our proposal performs better compared to the non-context-aware proposals.

Abstract
In recent years there have been several commercial products designated as "augmented books". These use gamification and augmented reality technologies to provide the reader with more layers of information, thereby fostering the use of the book in new ways. So, in this article we describe part of the research and outcomes of the Portuguese project CHIC – C3, aimed at designing and developing a platform for managing the production of digital content connected with printed books. Furthermore, we developed a model for the gamification of digital content based on the printed book, mainly aimed at educational purposes. A proof of concept for the model was built in the form of a companion platform, supported by the Moodle LMS, fully integrated with the main CHIC website. Readers were able to access the platform, engage in several content related games, and interact with other readers.