Abstract
As supply chains become more digital to reach new levels of global competitiveness, caveats from this decision arise. Cyber-risks are one of these potential setbacks, affecting supply chains directly and indirectly, and propagating via supply chain flows and stocks information, material, and financial. This study applied a systematic literature review to determine how the supply chain's flows and stocks serve as points of entry to cyber-risks. Cyber-risks arise from different sources (i.e., direct attacks, built-in problems, low-quality issues), impacting supply chains' flows and stocks (material and information). There is a relation between the type of supply chain and which flow, or stock facilitates access to the supply chain. Finally, we provide a distinction between two concepts related to Supply Chain Risk Management and cyber-risks. This research is useful to 1) enterprise decision-makers, as the description of potential cyber-risks' points of entry delivers hints on where to focus managerial efforts; 2) developers of Supply Chain Management (SCM) Information and Communication Technology (ICT) systems, since discussing potential points of entry build awareness about probable exploitation points, thus improving ICT systems' resiliency, and 3) scholars, as the depiction of the state-of-the-art may serve as a common departing point for future research. (C) 2021 The Authors. Published by Elsevier B.V.

Abstract
Over the past few years, the amount of information generated, consumed and stored on the Web has grown exponentially, making it impossible for users to keep up to date. Temporal data representation can help in this process by giving documents a sense of organization. Timelines are a natural way to showcase this data, giving users the chance to get familiar with a topic in a shorter amount of time. Despite their importance, little is known about their use in the context of single documents. In this paper, we present Time-Matters, a novel system to automatically explore arbitrary texts through temporal narratives in an interactive fashion that allows users to get insights into the relevant temporal happenings of a story through multiple components, including temporal annotation, storylines or temporal clustering. In contrast to classical timeline multi-document summarization tasks, we focus on performing text summaries of single documents with a temporal lens. This approach may be of interest to a number of providers such as media outlets, for which automatically building a condensed overview of a text is an important issue.

Abstract
In this paper it is presented an educational experiment, that consists of a mechatronic system applied to demonstrate concepts such as prototyping, control, haptic feedback and the use of different sensors and actuators. The described mechatronic system is based on the use of two identical manipulators, being physical devices commonly used in the industry. The physical components of the manipulators were 3D printed, being the original model of each manipulator the EEZYBotArm MK2. This, already existent prototype was modified, with the necessary changes, to fulfill the requisites of the proposed system, being included load cells to provide measurement of the applied forces, and the robot gripper was also modified, being applied an electromagnetic actuator.

Abstract
The main aim of this article is to explore the relationship between tourism experience and international retirement migration. Despite the current trends in international tourism and the marketing efforts of some destinations to attract retired foreigners, contributions in the literature about prospective migrants' decision process are still rare, particularly regarding long-term migration and beyond the traditional north-south flows from the wealthy countries to warmer and more affordable destinations. Building on migration theories and models, including the recently proposed push-pull plus model, this article includes a qualitative study with 12 Brazilian citizens with varying degrees of intention to migrate to Europe after retirement. Results show that tourism acts as an important facilitator of prospective migrants' decision process, functioning as a mediating driver of future migration, by enabling to gather information and to experience the living conditions in the destination. Overall, this article demonstrates that the push-pull plus model is particularly interesting to capture prospective migrants' dynamic decision process. Implications for managers and future research suggestions are also provided.

Abstract
The increasing penetration of renewable energy sources and the need to adjust to the future demand requires adopting measures to improve energy resources management, especially in buildings. In this context, PV generation forecast has an essential role in the energy management entities by preventing problems related to intermittent weather conditions and allowing participation in incentive programs to reduce energy consumption. This paper proposes an automatic model for the day-ahead PV generation forecast, combining several forecasting algorithms with the expected weather conditions. To this end, this model communicates with a SCADA system, which is responsible for the cyberphysical energy management of an actual building.

Abstract
The rise of social media and the explosion of digital news in the web sphere have created new challenges to extract knowledge and make sense of published information. Automated timeline generation appears in this context as a promising answer to help users dealing with this information overload problem. Formally, Timeline Summarization (TLS) can be defined as a subtask of Multi-Document Summarization (MDS) conceived to highlight the most important information during the development of a story over time by summarizing long-lasting events in a timely ordered fashion. As opposed to traditional MDS, TLS has a limited number of publicly available datasets. In this paper, we propose TLS-Covid19 dataset, a novel corpus for the Portuguese and English languages. Our aim is to provide a new, larger and multi-lingual TLS annotated dataset that could foster timeline summarization evaluation research and, at the same time, enable the study of news coverage about the COVID-19 pandemic. TLS-Covid19 consists of 178 curated topics related to the COVID-19 outbreak, with associated news articles covering almost the entire year of 2020 and their respective reference timelines as gold-standard. As a final outcome, we conduct an experimental study on the proposed dataset over two extreme baseline methods. All the resources are publicly available at https://github.com/LIAAD/tls-covid19.