Abstract
This paper summarises the joint efforts of a multinational group of six undergraduate students cooperating within the European Project Semester (EPS) conducted at the Instituto Superior de Engenharia do Porto (ISEP). The EPS@ISEP initiative, made available as a part of the Erasmus+ international students exchange programme, employs the principles of problem-based learning, facing students with—albeit downscaled—real-life scenarios and tasks they may encounter in their future professional practice. Participation in the project initiative outclasses most of the traditional courses through a wide spawn of its learning outcomes. Participants acquire not only hard skills necessary for an appropriate execution of the project, but also broaden their understanding of the approached problem through detailed scientific, management, marketing, sustainability, and ethics analysis—all in the atmosphere of multicultural and interdisciplinary collaboration. The team under consideration, based on personal preferences and predispositions, chose the topic of vertical farming and, in particular, to design a domestic indoor gardening solution, appropriate for space efficient incubation of plants. The paper portrays the process, from research, analysis, formulation of the idea to the design, development and testing of a minimum viable proof of concept prototype of the “Vereatable” solution. © 2019, Springer Nature Switzerland AG.

Abstract
Transmission Expansion Planning (TEP) is traditionally carried out based on long-term forecasts for the peak load, which is viewed as the worst-case scenario. However, with the increasing renewable penetration, the peak load may not be longer the only worst-case to quantify new investment requirements. In fact, high off-peak load scenarios combined with low renewable generation can originate unforeseen bottlenecks. Besides, as TEP is a time-consuming problem, relaxed decision-making processes are often proposed in the literature to address the problem, however there is no guarantee that optimal planning has been achieved when some costs in the decision-making process are neglected. In this sense, this paper proposes a novel methodological framework to ensure that the system is sufficiently robust to overcome conditions with high electricity demand and low renewable energy, furthermore, this paper also presents a broad comparison between the common decision making processes adopted in the TEP literature aiming at providing a more insightful understanding of its impact on the total system cost. The optimization model, which is based on a multi-stage planning strategy, considers an AC-OPF model to enforce operational constrains, including the N-1 contingency criterion. The proposed model is tested through an evolutionary algorithm on a large test system with 118 bus. The uncertainties inherent to wind-solar-hydrothermal systems, demand and the life cycle of generation and transmission equipment are duly considered in the simulations. The results demonstrate the effectiveness of the proposed methodology in providing solution plans able to meet the demand even in scenarios with high off-peak load and low renewable generation, unlike the planning carried out considering only the peak load. Besides, the results also demonstrate that relaxed decision-making models may generate insufficient expansion plans.

Abstract
With the profusion of web content, researchers have avidly studied and proposed new approaches to enable the anticipation of its impact on social media, presenting many distinct approaches throughout the last decade. Diverse approaches have been presented to tackle the problem of web content popularity prediction, including standard classification and regression approaches. Furthermore, these approaches have also taken into consideration distinct scenarios of data availability, where one may target the prediction of popularity before or after the publication of the items, which is highly interesting for different objectives from a user standpoint. This work aims at reviewing previous work and discussing open issues and challenges that could foster impactful research on this topic. Five areas are identified that require further research, covering the full spectrum of the problem: social media data, the learning task, recommendation and evaluation. © 2019 Elsevier B.V.

Abstract
In this paper the proposal of a low cost high performance educational mobile robot is described. The robot is based on an Arduino, applied in the low level control, while the high level control loop is carried out by an RPI running an object pascal application. The described robot was prototyped in order to have a competitive participation in the Robotic Day Line Follower 2017 competition, taking advantage of the RPI capabilities. The RPI allows the use of higher performance sensors, when compared with the most common standard approaches based on a single 8 bit RISC micro-controller, having as disadvantage the inevitable robot size increase, which compromises in certain situations the robot maneuverability and increases the power consumption. The robot is equipped with DC Motors, the chosen line follower sensor is the picamera and for the obstacle detection sonar sensors are used. © CLAWAR Association.

Abstract
Searching for health information is the third most popular activity on the Internet. There is evidence that query suggestions in lay and medico-scientific terminology improve health information retrieval by who is not a health professional. Developing systems that suggest queries in these terminologies requires knowing if concepts are lay or medico-scientific. In this paper, we propose and compare approaches to compute the degree of association of a concept to lay and medico-scientific terminology. We use different thesauri for this purpose and use the cosine similarity to measure the closeness of concepts with subsets of those thesauri. The evaluation of our approaches uses an existing glossary containing concepts in both terminologies in English and Portuguese and a and a set of queries submitted by users and classified by health professionals as lay or medical-scientific. We concluded that the best method to classify a concept uses the CHV vocabulary as a subset.

Abstract
Since the emergence of the Global Village, the information flow changed drastically. Digital Technologies changed how people communicate, how they access information and how they share it. It gave people an unlimited exposure to information and knowledge. However, it also seemed to limit it. Recommendation algorithms are used in order to provide a customized experience that captivates users. Although they play an important role in selecting information that is considered relevant to the user, significant information/content may be omitted. Consequently, users end up closed in a bubble of limited information, which affects critical thinking skills and appears to influence and guide personal opinions. Little attention has been given to the negative effects of information bias on people’s critical thinking. Thus, it is hoped that this study will at the same time educate and bring awareness to this issue. In a survey we performed (with 117 answers) the majority of the survey sample (approximately 54,7%) revealed discomfort regarding the storage and filtering of data. Interestingly, 29,9% of the participants were found to be indifferent regarding this issue. From these results, the authors can conclude that, although most of the participants feel uncomfortable, they prefer to be passive about this, which reinforces the idea of conformity and the false sense of organization mentioned herein. An interview with an expert in the area drew attention to the fact that social pressure most often leads users to comply and rely on the group’s beliefs and attitudes, which facilitates social relationships and avoids confrontation. © Springer Nature Switzerland AG 2019.