Abstract

Abstract
Como saber quais foram os principais problemas encontrados; quais as estratégias desenvolvidas em diferentes países, municípios, estados; e como se mobilizaram em tempos de pandemia da COVID-19? Como os estudantes, pais, professores, gestores e pesquisadores compreenderam esse movimento? Que aprendizagens e desafios a pandemia trouxeram à pesquisa em Educação? A partir dessas problematizações emerge a Rede Internacional de Educação OnLIFE (RIEOnLIFE), em parceria com a UAb Portugal. Este artigo objetiva apresentar o conceito de Educação OnLIFE, a RIEOnLIFE e seus movimentos, bem como discutir o primeiro movimento da rede, o Movimento EscutAÇÕES. De natureza qualitativa, a pesquisa busca inspiração no conceito de Living Labs, articulado ao método cartográfico de pesquisa- intervenção, originando três movimentos como território da pesquisa: as escutAÇÕES, as COnversAÇÕES e as COMpartilhAÇÕES. Os resultados evidenciam potência para: conectar instituições e sujeitos; compreender os problemas, estratégias e movimentos; conhecer desafios e aprendizagens; constituir um espaço comum de legitimação e construção da RIEOnLIFE enquanto rede ou plataforma de Educação OnLIFE.

Abstract
The distribution networks can convincingly break down into small-scale self-controllable areas, namely microgrids (mu G), to substitute mu Gs arrangements for effectively coping with perturbations. This flexible structure not only could potentially possess the strength to recover quickly, but also ensures the supply of vital loads and preserves functionalities under any contingency. To achieve these targets, this article examines a novel spatiotemporal algorithm to split the existing network into a set of self-healing mu Gs. In this endeavor, after designing the mu Gs by determining a mix of heterogeneous generation resources and allocating remotely controlled switches, the mu Gs operational scheduling is decomposed into interconnected and islanded modes. The main intention in the grid-tied state is to maximize the mu Gs profit while equilibrating load and generation at the islanded state by sectionalizing on-fault area, executing resources rescheduling, network reconfiguration and load shedding when the main grid is interrupted. The proposed problem is formulated as an exact computationally efficient mixed integer linear programming problem relying on the column & constraint generation framework and an adjustable interval optimization is envisaged to make the mu Gs less susceptible against renewables variability. Finally, the effectiveness of the proposed model is adequately assured by performing a realistic case study.

Abstract
Virtual reality has shown to have great potential as an educational tool when it comes to new learning methods. With the growth and dissemination of this technology, there is a massive opportunity for teachers to add this technology to their methods of teaching a second/foreign language, since students keep showing a growing interest in new technologies. This systematic review of empirical research aims at understanding whether the use of gaming strategies in virtual reality is beneficial for the learning of a second/foreign language or not. Results show that more than half of the articles proved that virtual reality technologies with gaming strategies can be used to learn a foreign language. It was also found that "learning" was the most evaluated dependent variable among the chosen records, augmented reality was the leading technology used, primary education and lower secondary was the most researched school stages, and the most used language to evaluate the use of gamified technology was by far the English language. Given the lack of directed investigation, it is recommended to use these technologies to support second language learning and not entirely replace traditional approaches. A research agenda is also proposed by the authors.

Abstract
There is an increasing interest to study the interactions between atmospheric electrical parameters and living organisms at multiple scales. So far, relatively few studies have been published that focus on possible biological effects of atmospheric electric and magnetic fields. To foster future work in this area of multidisciplinary research, here we present a glossary of relevant terms. Its main purpose is to facilitate the process of learning and communication among the different scientific disciplines working on this topic. While some definitions come from existing sources, other concepts have been re-defined to better reflect the existing and emerging scientific needs of this multidisciplinary and transdisciplinary area of research.

Abstract
Wine is the most important product from the Douro Region, in Portugal. Ampelographs are disappearing, and farmers need new solutions to identify grapevine varieties to ensure high-quality standards. The development of methodology capable of automatically identify grapevine are in need. In the scenario, deep learning based methods are emerging as the state-of-art in grapevines classification tasks. In previous work, we verify the deep learning models would benefit from focus classification patches in leaves images areas. Deep learning segmentation methods can be used to find grapevine leaves areas. This paper presents a methodology to segment grapevines images automatically based on the U-net model. A private dataset was used, composed of 733 grapevines images frames extracted from 236 videos collected in a natural environment. The trained model obtained a Dice of 95.6% and an Intersection over Union of 91.6%, results that fully satisfy the need of localise grapevine leaves.