Abstract
Standalone rural microgrid (MG) systems are considered as a sustainable and economical solutions towards rural area electrifications. Specific control schemes are necessary to adopt for reliable and economic performance of these rural MGs. This study focuses on the optimal utilization of biomass potential considering specific applications of bio generator (BG) with BG-PV-WT-BSS and BG-PV-SMES based standalone rural MG systems. In the first case of the BG-PV-WT-BSS, the optimal sizing/selection of DGs of a rural MG has been proposed using the improved-MILP (I-MILP) approach. The objectives of this study were to minimize total net present cost (TNPC), the levelized cost of energy (LCOE) and GHG emissions. In the second case of BG-PV-SMES, the simulation model of the rural microgrid consisting of a variable speed bio generator (VSBG) and photovoltaic (PV) has been developed. Afterwards, a simplified EMS has been designed for the coordinated operation control of the distributed energy resources (DERs) in the rural MGs using MATLAB/Simulink®^R environment. For the DGs connected via power converter, FOSMC and FCS-MPC based coordinated control has been proposed in the simplified EMS. The purpose of the FOSMC and FCS-MPC based power converter is the improvement of the system performance (for instance power quality, regulated voltage and THD) under external disturbances. Simulation analysis shows the better operation of FOSMC and FCS-MPC under less THD and improved power quality.

Abstract
CoronaSurveys is an ongoing interdisciplinary project developing a system to infer the incidence of COVID-19 around the world using anonymous open surveys. The surveys have been translated into 60 languages and are continuously collecting participant responses from any country in the world. The responses collected are pre-processed, organized, and stored in a version-controlled repository, which is publicly available to the scientific community. In addition, the CoronaSurveys team has devised several estimates computed on the basis of survey responses and other data, and makes them available on the project's website in the form of tables, as well as interactive plots and maps. In this paper, we describe the computational system developed for the CoronaSurveys project. The system includes multiple components and processes, including the web survey, the mobile apps, the cleaning and aggregation process of the survey responses, the process of storage and publication of the data, the processing of the data and the computation of estimates, and the visualization of the results. In this paper we describe the system architecture and the major challenges we faced in designing and deploying it.

Abstract
The potential of end-users to modify their consumption pattern makes them an interesting resource for providing energy flexibility in energy communities. Thus, active end-users require sufficient incentives and automated trading and management schemes. In order to enable increased small-scale end-users participation for flexibility service provision, a new design for flexibility trading is required to model the behavior of different agents and their interactions in energy communities. The novelty of our work lies in proposing an iterative game-based approach in which all agents - consisting of the distribution system operator (DSO), aggregators, and customers- can determine their decision variables to optimize their own objective functions and interact with others to modify their decisions according to others' decisions. In addition, three scenarios are considered to study the effects of agents' freedom while setting their decision variables (by removing one of their constraints in their corresponding decision-making problem). Moreover, the impact of the presence of interruptible loads in comparison with shiftable loads is investigated in this paper. According to the simulation results, it is found that in the scenario where end-users have fewer constraints, in presence of interruptible loads, end-users gain greater income compared to the absence of interruptible loads.

Abstract
Two distinct optical fibers for endoscope-based configurations are demonstrated and studied in this work. The fibers used for the experiment consist of: a conventional singlemode fiber (SMF 28e) and a hollow core photonic crystal fiber (HC-PCF) based on silica. Two studies that allowed the characterization of these fibers, according to their optical output power and when subjected to curvature, were carried out. The intensity power profile was also analysed in relation to the propagation distance, transversal displacement and incidence angle. After this study it can be concluded that the most suitable solution for the endoscope is the HC-PCF fiber working as a transmission probe. For the proof of concept of the fiber-based endoscope, a cleaved multimode fiber (MMF) tip was used as a reception probe and its reflection efficiency was also analysed.

Abstract
There is a growing trend to split problems into separate subproblems and develop separate models for each (e.g., different churn models for separate customer segments; different failure prediction models for separate university courses, etc.). While it may lead to better predictive models, the use of multiple models makes interpretability more challenging. In this paper, we address the problem of synthesizing the knowledge contained in a set of models without a significant loss of prediction performance. We focus on decision tree models because their interpretability makes them suitable for problems involving knowledge extraction. We detail the process, identifying alternative methods to address the different phases involved. An extensive set of experiments is carried out on the problem of predicting the failure of students in courses at the University of Porto. We assess the effect of using different methods for the operations of the methodology, both in terms of the knowledge extracted as well as the accuracy of the combined models.

Abstract