Abstract
Land cover maps obtained at high spatial and temporal resolutions are necessary to support monitoring and management applications in areas with many smallholder and low-input agricultural systems, as those characteristic in Mozambique. Various regional and global land cover products based on Earth Observation data have been developed and made publicly available but their application in regions characterized by a large variety of agro-systems with a dynamic nature is limited by several constraints. Challenges in the classification of spatially heterogeneous landscapes, as in Mozambique, include the definition of the adequate spatial resolution and data input combinations for accurately mapping land cover. Therefore, several combinations of variables were tested for their suitability as input for random forest ensemble classifier aimed at mapping the spatial dynamics of smallholder agricultural landscape in Vilankulo district in Mozambique. The variables comprised spectral bands from Landsat 7 ETM+ and Landsat 8 OLI/TIRS, vegetation indices and textural features and the classification was performed within the Google Earth Engine cloud computing for the years 2012, 2015, and 2018. The study of three different years aimed at evaluating the temporal dynamics of the landscape, typically characterized by high shifting nature. For the three years, the best performing variables included three selected spectral bands and textural features extracted using a window size of 25. The classification overall accuracy was 0.94 for the year 2012, 0.98 for 2015, and 0.89 for 2018, suggesting that the produced maps are reliable. In addition, the areal statistics of the class classified as agriculture were very similar to the ground truth data as reported by the Servicos Distritais de Actividades Economicas (SDAE), with an average percentage deviation below 10%. When comparing the three years studied, the natural vegetation classes are the predominant covers while the agriculture is the most important cause of land cover changes.

Abstract
The impact of climate on wine production (WP) temporal cycles in Douro (DR) and Vinhos Verdes (VVR) wine regions for a period of about 80 years, characterized by strong technological trend and climate variability, was modelled. The cyclical properties of WP, and which cycles are determined by spring temperature (ST) and soil water during summer (SW), were identified. It was achieved by applying a time-frequency approach, which is based on Kalman filter in the time domain. The time-varying autoregressive model can explain more than 67% (DR) and 95% (VVR) of the WP' variability and the integration of the ST and mainly SW increase the models' reliability. The results were then transferred into the frequency domain, and can show that WP in both regions is characterized by two cycles close to 5-6 and 2.5 years around the long run trend. The ST and SW showed great capacity to explain the cyclicality of WP in the studied regions being the coherence temporarily much more stable in VVR than in the DR, where a shift of the relative importance away from ST to SW can be recognized. This could be an indicator of lower impact of the foreseen hot and dry climate scenarios on WP in the regions with a maritime climate, such as the VVR, compared with hot and dry wine regions. Despite the marked differences in the two studied regions on ecological, viticulture practices and technological trend, the modelling approach based on time-frequency proved to be an efficient tool to infer the impact of climate on the dynamics of cyclical properties of regional WP, foreseeing its generalized use in other regions. This modelling approach can be an important tool for planning in the wine industry as well as for mitigation strategies facing the scenarios that combine technological progress and climate change.

Abstract
Europe's 2020 strategy considers sustainable management as an increasingly important criterion for the several normative and incentives recently legislated. It is expectable that in short-term, political decision-makers and farmers will need to evaluate the type and degree of their activities' impact on the environment, economy and society. For this reason, tools are required to ease and translate these evaluations, capable of defining the main imbalance factors that need action. Despite a wide range of sustainability assessment tools available in the literature, the underlying methodologies are very similar and resort to indicators aggregated in hierarchical evaluation models that should be representative and adaptive for putative transferability. This paper provides an overview of the most relevant computational sustainability evaluation tools and their scope of application, in a benchmarking analysis. To ease the comprehension of these tools, a literature review was performed to analyse their structural elements and based on methodologies. Copyright © 2020 Inderscience Enterprises Ltd.

Abstract
In recent years, mobile robots have become increasingly frequent in daily life applications, such as cleaning, surveillance, support for the elderly and people with disabilities, as well as hazardous activities. However, a big challenge arises when the robotic system must perform a fully autonomous mission. The main problems of autonomous missions include path planning, localisation, and mapping. Thus, this research proposes a hybrid methodology for mobile robots on an autonomous mission involving an offline approach that uses the Direct-DRRT* algorithm and the artificial potential fields algorithm as the online planner. The experimental design covers three scenarios with an increasing degree of accuracy in respect of the real world. Additionally, an extensive evaluation of the proposed methodology is reported.

Abstract
A robótica assistiva está presente em diversas áreas de pesquisa do mundo atual. Trabalhos voltados para o aumento da produtividade e para o auxílio de pessoas com deficiência física são alguns exemplos de como a robótica pode facilitar e melhorar a qualidade de vida do ser humano. Com o desenvolvimento de aplicações remotas é possível controlar diferentes dispositivos sem a necessidade de estar presente no local de atuação. Este artigo tem como objetivo controlar um robô humanoide remotamente através do reconhecimento de sinais de eletromiografia, bem como localizá-lo em seu ambiente.

Abstract
One of the teacher's first goals should be to motivate students to learn. Involving students in the learning process using project-based learning could be a useful and powerful tool to prepare the students for them professional future. As part of a degree course in Biomedical Engineering, from a Portuguese University, students were asked to look at society and identify a possible failure related to the biomedical field. From the identification of this fault, the project consisted in the planning and its possible resolution. In this article we present the case study of a student's team, whose project was candidate and winner for a national prize in the field of health innovation. Despite the particularization of this case study, the students considered the experience innovative and simultaneously motivating. They also highlighted the added value of a project going beyond the classroom. Therefore, in addition to allowing them to obtain classification to the curricular unit, this type of teaching and learning could have a special impact on civil society.