Abstract
Este estudo desenvolveu-se numa Unidade Curricular da Licenciatura em Engenharia Informática, no contexto de ensino superior português a distância, com alunos maiores de 23 anos, na qual se adotou a abordagem pedagógica e-SimProgramming. Esta abordagem situada em ambiente empresarial simulado recorre a narrativas imersivas desenvolvidas através da técnica OC2-RD2, contemplando o argumento, as personagens e os espaços. Os nomes das personagens têm significados que remetem para arquétipos. Para operacionalizar esta técnica adaptaram-se os nomes dados às personagens ao contexto cultural de Portugal, origem da maioria dos alunos, já que os originais tinham sido concebidos para o contexto cultural do Brasil. Adotou-se uma metodologia de investigação quantitativa e qualitativa, numa perspetiva de estudo de tendência, baseada na análise de respostas a um questionário online. O objetivo visa compreender as perceções dos estudantes sobre os nomes das personagens, em relação à sua adequabilidade na abordagem aos arquétipos da técnica OC2-RD2 no ambiente de simulação. O questionário é composto por questões relativas à perceção dos estudantes quanto ao nome de cada personagem, e caso considerassem o nome desadequado poderiam sugerir alternativas. Realizou-se a análise de dados quantitativa e qualitativa, sendo que em 99 alunos inscritos, 40 responderam ao questionário (40%). Os resultados demonstram que os nomes selecionados para as personagens foram aceites pela maioria dos estudantes (valores iguais ou superiores a 70%). Quanto às sugestões de nomes alternativos, surgiram três grupos distintos: 1- personalidades da área do desenvolvimento de software (e.g. Lovelace, remetendo para Ada Lovelace) e referências técnicas (e.g. Python, uma linguagem de programação); 2- nomes próprios portugueses (e.g. Manuel, Íris); 3- expressões figurativas (e.g. Quasenada, MaisouMenos). Conclui-se que a adaptação dos nomes originais das personagens para o contexto cultural de Portugal foi considerada adequada pelos estudantes, podendo contribuir para a aprendizagem situada com imersão em simulação de ambiente empresarial. Em trabalhos futuros recomenda-se a análise da interpretação dos nomes sugeridos pelos alunos às personagens, para aferir se correspondem aos arquétipos originais ou se induziram alguma alteração, para melhor compreensão da perceção das narrativas face ao contexto cultural e às várias áreas de conhecimentos.;This study was developed in a course of the undergraduate program in Informatics Engineering, in the context of online higher education in Portugal, with students over 23 years of age, in which the eSimProgramming pedagogical approach was adopted. This approach employs situated learning with immersive narratives to simulate a business environment. The narratives were developed through the OC2-RD2 technique, contemplating the script, the characters, and the spaces. The names of the characters have meanings that refer to archetypes. To deploy this technique, the names given to the characters were adapted to the cultural context of Portugal, the origin of most students, since the original names had been designed for the cultural context of Brazil. A quantitative and qualitative research methodology was adopted, in a trend study perspective, based on the analysis of answers from an online questionnaire. The objective is to understand perceptions of character names in relation to their suitability in addressing the archetypes of the OC2-RD2 technique in the simulation environment. The questionnaire is composed of questions regarding the perception of the name of each character, and if they considered the name inappropriate, they could suggest alternatives. Quantitative and qualitative data analysis was performed, and out of 99 students enrolled, 40 answered the questionnaire (40%). The results show that the names selected for the characters were accepted by most students (values equal to or greater than 70%). As for suggestions for alternative names, three distinct groups emerged: 1- personalities from the area of software development (e.g. Lovelace, referring to Ada Lovelace) and technical references (e.g. Python, a programming language); 2- Portuguese given names (e.g. Manuel, Íris); 3- figurative expressions (e.g. Quasenada, MaisouMenos meaning , We conclude that the adaptation of the original names of the characters to the Portuguese cultural context was considered adequate by the students, potentially contributing to the immersion in the simulation of the business environment. In future work we recommend the analysis of the interpretation of the names suggested by the students to the characters, to check if they match the original archetypes or if they induced some change, for a better understanding of the perception of the narratives vis-à-vis the cultural context and the various areas of knowledge.

Abstract
In this paper it is presented an educational experiment, that consists of a mechatronic system applied to demonstrate concepts such as prototyping and control. The described mechatronic system is based on a conveyor belt, that was integrated with a manipulator, being physical devices commonly used in the industry. The conveyor Belt was prototyped from scratch, using 3d print technology. Its movement is based on the closed loop control of a DC Motor, based on a PID. The Conveyor Belt was integrated with a Braccio Manipulator from Arduino, using the ZMQ communication library, which is a high-performance asynchronous messaging library. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Abstract
Industry 4.0 confronts companies, in particular SMEs, with various technological, organizational and cultural challenges with great impact on traditional business models. This paradigmatic socio-technical shift, implies the redefinition of the role of people in the organisation, the integration of all organisational decision layers (from the factory floor to the decision support structures) and the digital connection of the entire value chain, including processes, people and machines. However, the lack of qualified resources and the lack of an holistic understanding of industry 4.0 derail SMES’ digital transformation journey. This research work discusses the need for industry 4.0 re-conceptualisation, tailored to SMES’ needs. A lightweight ontology is presented and discussed how it contributes to the organisation and structuring a Community Of Practice, to share knowledge in the context of SMES’ industry 4.0 initiatives. Despite of the discussed use case, the developed artefact might be used to assess SME’s digital readiness. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Computing subgraph frequencies is a fundamental task that lies at the core of several network analysis methodologies, such as network motifs and graphlet-based metrics, which have been widely used to categorize and compare networks from multiple domains. Counting subgraphs is, however, computationally very expensive, and there has been a large body of work on efficient algorithms and strategies to make subgraph counting feasible for larger subgraphs and networks. This survey aims precisely to provide a comprehensive overview of the existing methods for subgraph counting. Our main contribution is a general and structured review of existing algorithms, classifying them on a set of key characteristics, highlighting their main similarities and differences. We identify and describe the main conceptual approaches, giving insight on their advantages and limitations, and we provide pointers to existing implementations. We initially focus on exact sequential algorithms, but we also do a thorough survey on approximate methodologies (with a trade-off between accuracy and execution time) and parallel strategies (that need to deal with an unbalanced search space).

Abstract

Abstract
The negative impact of false information on social networks is rapidly growing. Current research on the topic focused on the detection of fake news in a particular context or event (such as elections) or using data from a short period of time. Therefore, an evaluation of the current proposals in a long-term scenario where the topics discussed may change is lacking. In this work, we deviate from current approaches to the problem and instead focus on a longitudinal evaluation using social network publications spanning an 18-month period. We evaluate different combinations of features and supervised models in a long-term scenario where the training and testing data are ordered chronologically, and thus the robustness and stability of the models can be evaluated through time. We experimented with 3 different scenarios where the models are trained with 15-, 30-, and 60-day data periods. The results show that detection models trained with word-embedding features are the ones that perform better and are less likely to be affected by the change of topics (for example, the rise of COVID-19 conspiracy theories). Furthermore, the additional days of training data also increase the performance of the best feature/model combinations, although not very significantly (around 2%). The results presented in this paper build the foundations towards a more pragmatic approach to the evaluation of fake news detection models in social networks.