Abstract
This paper deals with an optimal operation of a microgrid in the electricity market and presents the communication between the distribution market operator and microgrid operator. The distribution market operator controls and manages the electricity market established in the distribution level, determining the amount of both electricity price and power exchange between market participants. The microgrid operator is able to purchase active and reactive power from the local distribution market. An effective short-term scheduling of the microgrid is implemented to ensure optimal operation. A risk based stochastic model is used to model the prevailing uncertainties such as loads, wind generation, and main-grid availability in a market-based operation framework. Moreover, in this model, a linearized AC power flow is added to the mathematical formulations to offer a comprehensive solution to the security-constraint operation of the microgrid. The stochastic operation strategy is formulated as a mixed integer linear programming problem. Regarding the uncertainty modeling, the substation equipment failure is modeled with Monte-Carlo algorithm. The effectiveness of the risk-based stochastic method is demonstrated using a microgrid test bed in the presence of demand response resources, dispatchable and wind generation units as well as energy storage system. The results demonstrate demand response program can significantly reduce the operation cost in worst scenarios. Also, it is indicated that the risk averse decisions reduce the risk of experiencing costly scenario. The proposed framework incorporating the distribution market constraints reduces the uncertainty in real-time operation as it can specified the required energy before running the problem. The deviations from assigned energy to the microgrid are penalized through the distribution market operator.

Abstract
Engineering aims to improve the quality of daily life on a planet with limited resources. This chapter describes how the European Project Semester offered by the School of Engineering of the Porto Polytechnic contributes to make engineering undergraduates conscious of their environmental and societal impact. The program is a project-based active learning framework where problem-solving is supported by intercultural communication and creativity, ethical and sustainable reasoning, and global contextual analysis. This analysis shows that it fosters scientific, technical, and interpersonal competencies, emphasizing ethical and sustainable design as recommended by several reference institutions through the testimonials left on the project reports and the evolution perceived by the participants during the semester. These findings are supported by a sample of 45 projects conducted by 228 students from 23 countries and 65 degrees. All projects aimed to have a lasting impact on the future engineering practice of participants and, somehow, transform the world positively.

Abstract
The Portuguese General Directorate for Book, Archives and Libraries (DGLAB) has selected CIDOC CRM as the basis for its next-generation digital archive management software. Given the ontological foundations of the Conceptual Reference Model (CRM), a graph database or a triplestore was seen as the best candidate to represent a CRM-based data model for the new software. We thus decided to compare several of these databases, based on their maturity, features, performance in standard tasks and, most importantly, the Object-Graph Mappers (OGM) available to interact with each database in an object-oriented way. Our conclusions are drawn not only from a systematic review of related works but from an experimental scenario. For our experiment, we designed a simple CRM-compliant graph designed to test the ability of each OGM/database combination to tackle the so-called diamond-problem in Object-Oriented Programming (OOP) to ensure that property instances follow domain and range constraints. Our results show that (1) ontological consistency enforcement in graph databases and triplestores is much harder to achieve than in a relational database, making them more suited to an analytical rather than a transactional role; (2) OGMs are still rather immature solutions; and (3) neomodel, an OGM for the Neo4j graph database, is the most mature solution in the study as it satisfies all requirements, although it is also the least performing.

Abstract
The widespread use of Internet-of-Things (IoT) across different application domains leads to an increased concern regarding their dependability, especially as the number of potentially mission-critical systems becomes considerable. Fault-tolerance has been used to reduce the impact of faults in systems, and their adoption in IoT is becoming a necessity. This work focuses on how to exercise fault-tolerance mechanisms by deliberately provoking its malfunction. We start by describing a proof-of-concept fault-injection add-on to a commonly used publish/subscribe broker. We then present several experiments mimicking real-world IoT scenarios, focusing on injecting faults in systems with (and without) active self-healing mechanisms and comparing their behavior to the baseline without faults. We observe evidence that fault-injection can be used to (a) exercise in-place fault-tolerance apparatus, and (b) detect when these mechanisms are not performing nominally, providing insights into enhancing in-place fault-tolerance techniques.

Abstract
Nowadays, decentralized microgrids (DC-MGs) have become a popular topic due to the effectiveness and the less complexity. In fact, DC-MGs resist to share their internal information with the distribution system operator (DSO) to protect their privacy and compete in the electricity market. Further, lack of information sharing among MGs in normal operation conditions leads to form a competitive market. However, in emergency operation conditions, it results numerous challenges in managing network outages. Therefore, this paper presents a hierarchical model consisting of three stages to enhance the resilience of DC-MGs. In all stages, the network outage management is performed considering the reported data of MGs. In the first stage, proactive actions are performed with the aim of increasing the network readiness against the upcoming windstorm. In the second stage, generation scheduling, allocation of mobile units and distribution feeder reconfiguration (DFR) are operated by DSO to minimize operating costs. In the final stage, the repair crew is allocated to minimize the energy not served (ENS). Un-certainties of load demand, wind speed and solar radiation are considered, and the effectiveness of the proposed model is investigated by integrating to the 118-bus distribution network. Finally, the results of the simulation indicate that DFR and proactive actions decrease the ENS by 19,124 kWh and 4101 kWh, respectively. Further, the sharing of information among MGs leads to a 48.16% growth in the supply service level to critical loads, and consequently a 3.47% increase in the resilience index.

Abstract
The sedimentary processes play a major role in every aquatic ecosystem, however, there are few automated options for in-situ monitoring of sediment displacement in the streambed of waterways. We present an automated optical instrument for in-situ continuous monitoring of sediment deposition and erosion of the streambed that requires no calibration. With a production cost of 32euro, power consumption of 300 mu A in sleep mode, and capacity to monitor the bedform of a waterway, the sensor was developed to evaluate the sediment dynamics of coastal areas with a wide spatial and temporal resolution. The novel device is intended to be buried in the sand and uses 32 infrared channels to monitor the streambed sediment height. For testing purposes, a maximum measuring length of 160 mm and 5 mm resolution was chosen, but these values are scalable. Sensors can be built with different ranges and precision according to the needs of the fieldwork. A laboratory experiment was conducted to demonstrate the working principle of the instrument and its behaviour regarding the turbidity originated by suspended sediment and the settling and deposition of the suspended particles. The device was deployed for 119 days in an estuarine area and was able to detect patterns in the sediment deposition and resuspension during the tidal cycles. Also, abnormal events occurred during the experiment as floods and algae blooms. During these events, the sensor was able to record exceptional erosion and sediment deposition rates. The reported automated instrument can be broadly used in sedimentary studies or management and planning of fluvial and maritime infrastructures to provide real-time information about the changes in the bedform of the watersheds.