Abstract
Weather conditions have a major impact on citizens’ daily mobility. Depending on weather conditions trips may be delayed, demand may be changed as well as the modal shift. These variations have a major impact on the use and operation of public transport, particularly in transport systems that operate close to capacity. However, the influence of weather conditions on transport demand is difficult to predict and quantify. For this purpose, an artificial neural network model – the Multilayer Perceptron – is used as a regression model to estimate the demand of urban public transport buses based on weather conditions. Transit bus ridership and weather conditions were collected along a year from a medium-size European metropolitan area (Oporto, Portugal) and linked under the assumption that individuals choose the travel mode based on the weather conditions that are observed during the departure hour, the hour before and two hours before. The transit ridership data were also labelled according to the hour, day of the week, month, and whether there was a strike and/or holiday or not. The results demonstrate that it is possible to predict the demand of public transport buses using the weather conditions observed two hours before with low error for the entire network (MAE = 143 and RMSE = 322). The use of weather conditions allow to decreases the error of the prediction by ~8% for the entire network. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Public opinion is nowadays a valuable data source for many sectors. In this study, we analysed the transportation sector using messages extracted from Twitter. Contrasting with the traditional surveying methods that are high-cost and inefficient used in transportation sector, social media are popular sources of crowdsensing. This work used BERT embeddings, an unsupervised pre-trained model released in 2018, to classify travel-related terms using tweets collected from three distinct cities: New York, London, and Melbourne. In order to understand if a simple model can have a good performance, we used unigrams. A list of 24 travel-related words was used to classify the messages. Popular words are train, walk, car, station, street, and avenue. Between 3% to 5% of all messages are classified as traffic-related, while along the typical working hours of the day the values is around 5-6%. A high model performance was obtained, with precision and accuracy higher than 0.80 and 0.90, respectively. The results are consistent for all the three cities assessed. © 2021 IEEE.

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Video games provide a means to improve a human's cognitive skills. There are several genres of games that affect different cognitive subcategory. The purpose of this paper is to determine whether video games could really improve cognitive skills and decision-making; and which video games genre affect which cognitive skills. The authors assess previous experiments related to video games and cognitive skills. The paper reviewed 27 experimental and literature review studies. The results of the review proved that video games do improve cognitive skills and decision-making. Cognitive skills such as perception, attentional control, and decision-making improves when subjects were trained with video games. In relation to video games genre, Real-time strategy (RTS) players outperforms First-person shooter (FPS) players on cognitive flexibility while FPS players tend to have lower switching cost in work. People with profession such as nurses and doctors showed improved decision-making and risk assessment when trained with serious simulation games. High school and undergraduate students who played video games exhibit better result when given tasks related to cognitive abilities compared to students who do not played video games. We encourage further studies to conduct a much bigger experiment to correlate with our findings. (C) 2021 The Authors. Published by Elsevier B.V.

Abstract
Sustainability in project management is an emerging and evolving field of study, in the 2030 Agenda for Sustainable Development. Sustainability in project management is immersed in many goals and targets, and is also echoed in many other goals and targets. In this sense, the goal of this research was to analyse how to incorporate sustainability issues and Sustainable Development Goals - SDGs as critical success factors for project management and propose a sustainable project management model. The developed conceptual model contains the variables related to the identified barriers and motivation factors for the integration of sustainability with project management. It presents seven hypotheses and five constructs: Sustainable Development Goals; Interested Parties; Sustainable Companies; Sustainable Project Management Methodology and Sustainable Project. The proposed model and its constructs' relationships were validated using a structural equation model, across more than 400 valid questionnaires, completed by project management professionals from all around the world. The main result of the study indicates that for sustainability to become an integer part of project management, the dissemination and use of a sustainable project management methodology that considers the SDGs - Sustainable Development Goals by companies and professional associations, encouraging professionals to be trained and certified in these sustainable methodologies, is necessary.