Abstract
This study aims to explore the role of social networks in the internationalisation of startups. For this purpose, the social network LinkedIn is used, and two case studies of Portuguese technological startups are employed. The findings indicate that social networks can contribute to the acceleration of the internationalisation process and decrease their costs. Their relevance is greater in the initial phase of the internationalisation process. However, its relevance is limited in more advanced phases of this process. LinkedIn can be used by startups to obtain several benefits such as brand awareness, identification of new opportunities, customer feedback, among others. The results of this study are essentially useful in a practical dimension for companies that plan to start or improve their internationalisation process sustained on social networks.

Abstract

Abstract
This paper presents an adaptable dictionary-based feature extraction approach for spike sorting offering high accuracy and low computational complexity for implantable applications. It extracts and learns identifiable features from evolving subspaces through matched unsupervised subspace filtering. To provide compatibility with the strict constraints in implantable devices such as the chip area and power budget, the dictionary contains arrays of {-1, 0 and 1} and the algorithm need only process addition and subtraction operations. Three types of such dictionary were considered. To quantify and compare the performance of the resulting three feature extractors with existing systems, a neural signal simulator based on several different libraries was developed. For noise levels sigma(N) between 0.05 and 0.3 and groups of 3 to 6 clusters, all three feature extractors provide robust high performance with average classification errors of less than 8% over five iterations, each consisting of 100 generated data segments. To our knowledge, the proposed adaptive feature extractors are the first able to classify reliably 6 clusters for implantable applications. An ASIC implementation of the best performing dictionary-based feature extractor was synthesized in a 65-nm CMOS process. It occupies an area of 0.09 mm(2) and dissipates up to about 10.48 mu W from a 1 V supply voltage, when operating with 8-bit resolution at 30 kHz operating frequency.

Abstract
Tourism crowdsourcing platforms accumulate and use large volumes of feedback data on tourism-related services to provide personalized recommendations with high impact on future tourist behavior. Typically, these recommendation engines build individual tourist profiles and suggest hotels, restaurants, attractions or routes based on the shared ratings, reviews, photos, videos or likes. Due to the dynamic nature of this scenario, where the crowd produces a continuous stream of events, we have been exploring stream-based recommendation methods, using stochastic gradient descent (SGD), to incrementally update the prediction models and post-filters to reduce the search space and improve the recommendation accuracy. In this context, we offer an update and comment on our previous article (Veloso et al., 2019a) by providing a recent literature review and identifying the challenges laying ahead concerning the online recommendation of tourism resources supported by crowdsourced data.

Abstract
Evermore end-to-end digital services depend on the proper interoperation of multiple products, forming a distributed system, often subject to timing requirements. To ensure interoperability and the timely behavior of such systems, it is important to conduct integration tests that verify the interactions with the environment and between the system components in key scenarios. The automation of such integration tests requires that test components are also distributed, with local testers deployed close to the system components, coordinated by a central tester. Test coordination in such a test architecture is a big challenge. To address it, in this article we propose an approach based on the pre-processing of the test scenarios. We first analyze the test scenarios in order to check if conformance errors can be detected locally (local observability) and test inputs can be decided locally (local controllability) by the local testers for the test scenario under consideration, without the need for exchanging coordination messages between the test components during test execution. If such properties do not hold, we next try to determine a minimum set of coordination messages or time constraints to be attached to the given test scenario to enforce those properties and effectively solve the test coordination problem with minimal overhead. The analysis and enforcement procedures were implemented in the DCO Analyzer tool for test scenarios described by means of UML sequence diagrams. Since many local observability and controllability problems may be caused by design flaws or incomplete specifications, and multiple ways may exist to enforce local observability and controllability, the tool was designed as a static analysis assistant to be used before test execution. DCO Analyzer was able to correctly identify local observability and controllability problems in real-world scenarios and help the users fix the detected problems.

Abstract
In recent years, the large deployment of distributed energy resources (DERs) in low voltage networks is changing the traditional approach to power systems. This massive change is pushing towards new solutions to improve energy trading in low voltage networks. Consumer-centric options, such as full peer-to-peer (P2P) and energy community markets (CM) are seen as viable options to increase the active participation of end-users in the electricity markets. This work studies the full P2P and CM market approaches applied to the actual regulatory framework in Brazil, evaluating and comparing both approaches to be potentially applied in Brazil. A case study based on a typical Brazilian neighborhood is designed, allowing to assess the behavior of consumers and prosumers in both markets. The results show the economic viability of both models, considering the social welfare and the penetration of distributed generation in the system. An important conclusion under the current regulatory framework is that the full P2P can have greater benefits over the CM, as long as the distributed generation is enough to confer near self-sufficiency to the peer's demand.