Abstract
The growth of renewable energy sources usage at the local level contributes to decentralizing the power and energy systems. Nowadays, there is an increment of residential consumers becoming prosumers able to consume their generation or sell it to the public grid to reduce the electricity bill. This great penetration of electricity compromises the proper functioning of the system. Local electricity markets (LEM) are market platforms aimed at electricity end-users to be able to negotiate and transact it between them, thus becoming active players in the system, being a possible solution to balance local systems. Different approaches for LEM design and implementation are proposed in the literature, usually based on community markets and peer-to-peer. Despite their value, these solutions' scalability is compromised as these are centralized solutions, and processing can become very heavy. In this sense, this work proposes a blockchain-based distributed and decentralized optimal solution for implementing LEM. © 2022 IEEE.

Abstract
The integration of distributed energy resources contributes to accomplishing a balance between the supply and demand inside a local market. The operation of these markets is based on the peer-to-peer negotiations between users, whose cooperation leads to an increase in the social welfare of the community, thus creating a more user-centric market. This work fits in the context of the energy community, where members of a community can exchange energy in peer-to-peer transactions and use the public electricity grid as a backup. The market aims at maximizing the social welfare of the community considering the operational costs of all community members. A particle swarm optimization algorithm implemented in Python is used to solve the problem. © 2022 IEEE.

Abstract
Recent commitments and consequent advances towards an effective energy transition are resulting in promising solutions but also bringing out significant new challenges. Models for energy management at the building and microgrid level are benefiting from new findings in distinct areas such as the internet of things or machine learning. However, the interaction and complementarity between such physical and virtual environments need to be validated and enhanced through dedicated platforms. This chapter presents the Multi-Agent based Real-Time Infrastructure for Energy (MARTINE), which provides a platform that enables a combined assessment of multiple components, including physical components of buildings and microgrids, emulation capabilities, multi-agent and real-time simulation, and intelligent decision support models and services based on machine learning approaches. Besides enabling the study and management of energy resources considering both the physical and virtual layers, MARTINE also provides the means for a continuous improvement of the synergies between the Internet of Things and machine learning solutions.

Abstract
Findings of Iron Age metallurgical activities related to tin metal and mining are very rare. In the present work, we present a detailed study of the Outeiro de Baltar hillfort, dated to the Late Iron Age/Early Roman period, located in a place where 20th century tin mining work took place. Elemental and microstructural analysis by portable, micro and wavelength dispersive X-ray fluorescence spectrometry (pXRF, micro-XRF and WDXRF) and scanning electron microscopy with energy dispersion spectrometer (SEM-EDS) showed that metallurgical debris found at the archaeological site is related to tin smelting and binary and ternary bronze productions. Analysis of the artefacts of diverse typologies found at the site showed that a variety of metals and alloys were in circulation and use. Samples of tin ores (cassiterite) from the region were analyzed for comparison with an archaeological tin slag from the site. The analytical results point to the production of tin metal using local cassiterite and the production of bronze by directly adding cassiterite into a smelting process. Furthermore, data of remote sensing (airborne Light Detection and Ranging (LiDAR) and historical aerial imagery) and Geographical Information System (GIS) mapping were combined with archival mining documentation and maps to retrieve a landscape context for the site. The study showed that the place of the Outeiro de Baltar hillfort (NW Iberia) was mined periodically over time.

Abstract
The ELASTIC European project addresses the emergence of extreme-scale analytics, providing a software architecture with a new elasticity concept, intended to support smart cyber-physical systems with performance requirements from extreme-scale analytics workloads. One of the main challenges being tackled by ELASTIC is the necessity to simultaneously fulfil the non-functional properties inherited from smart systems, such as real-time, energy efficiency, communication quality or security. This paper presents how the ELASTIC architecture monitors and manages such non-functional requirements, working in close collaboration with the component responsible for the orchestration of elasticity. © 2022, Ada-Europe. All rights reserved.

Abstract