Abstract
We describe a case study application for untethered video dissemination using a hybrid edge-cloud architecture featuring Android devices, possibly organised in WiFi-Direct groups, and Raspberry Pi-based cloudlets, structured in a mesh and also working as access points. The application was tested in the real-world scenario of a Portuguese volleyball league game. During the game, users of the application recorded videos and injected them in the edge-cloud. The cloudlet servers continuously synchronised their cached video contents over the mesh network, allowing users on different locations to share their videos, without resorting to any other network infrastructure. An analysis of the logs gathered during the experiment shows that such portable setups can easily disseminate videos to tens of users through the edge-cloud with low latencies. We observe that the edge-cloud may be naturally resilient to faulty cloudlets or devices, taking advantage of video caching within devices and WiFi-Direct groups, and of device churn to opportunistically disseminate videos.

Abstract
The continued development of mobile robots (MR) must be accompanied by an increase in robotics' safety measures. Not only must MR be capable of detecting and diagnosing faults, they should also be capable of understanding when the dangers of a mission, to themselves and the surrounding environment, warrant the abandonment of their endeavors. Analysis of fault detection and diagnosis techniques helps shed light on the challenges of the robotic field, while also showing a lack of research in autonomous decision-making tools. This paper proposes a new skill-based architecture for mobile robots, together with a novel risk assessment and decision-making model to overcome the difficulties currently felt in autonomous robot design.

Abstract
We present an integrated research data management (RDM) workflow that captures data from the moment of creation until its deposit. We integrated LabTablet, our electronic laboratory notebook, Dendro, our data organisation and description platform aimed at collaborative management of research data, and EUDAT's B2DROP and B2SHARE platforms. This approach combines the portability and automated metadata production abilities of LabTablet, Dendro as a collaborative RDM tool for dataset preparation, with the scalable storage of B2DROP and the long-term deposit of datasets in B2SHARE. The resulting workflow can be put to work in research groups where laboratorial or field work is central.

Abstract
Growing number of inverter-based distributed energy resources (DERs) and sensitive loads increase the need for coordinated power management activities in islanded operation of microgrids. Especially low voltage networks have low inertia and high RA ratio, causing instability due to fluctuations in distributed generation (DG) and local voltage problems in islanded operation. This study investigates management of DERs that operate in current mode for providing voltage regulation support to master unit(s) in islanded operation of microgrids. A special focus was set on local voltage issues in low voltage (LV) network feeders. Field experiments in a large test facility highlighted management accuracy and corrective impact potential of DERs connected to different parts of a feeder.

Abstract
The proliferation of Information and Communication Technologies allowed the development of new solutions to be applied at the shop-floor and all the tools which helps the manufacturers. Hence, new solutions such as cyber-physical production systems, data analytics and knowledge management were developed and proposed to solve the wellknown issues, such as quality control in multistage manufacturing systems. However, those solutions can only have a small contribution in solving that issues compared to an optimized and fully integrated approach. To allow the development of a fully integrated environment, it is necessary to deliver a standard way to communicate and interact with the different functionalities. The proposed research aims to provide an integration layer, capable of translating the rules defined at the knowledge management level, structured as Decision Model and Notation rules, into an AutomationML based language. This allows the cyber-physical production system the ability to apply these rules near the shop-floor. This article presents the template defined to represent the rules in AutomationML as well as the infrastructure developed to receive the rules from the knowledge management, translate them and deliver to the cyber-physical production system. At the end of the article is presented a test bed where the solution is instantiated with rules focused on quality control.

Abstract
The decarbonisation of the power sector is key to achieving the Paris Agreement goal of limiting global mean surface temperature rise to well below 2 °C. This will require rapid, national level transitions to low carbon electricity generation, such as variable renewables (VRE), nuclear and fossil fuels with carbon capture and storage, across the world. At the same time it is essential that future power systems are sustainable in the wider sense and thus respect social, environmental and technical limitations. Here we develop an energy-land-water nexus modelling framework and use it to perform a scenario analysis with the aim of understanding the planning and operational implications of these constraints on Great Britain's (GB) power system in 2050. We consider plausible scenarios for limits on installed nuclear capacity, siting restrictions that shape VRE deployment and water use for thermal power station cooling. We find that these factors combined can lead to up to a 25% increase in the system's levelised cost of electricity (LCOE). VRE siting restrictions can result in an up to 13% increase in system LCOE as the deployment of onshore wind is limited while nuclear capacity restrictions can drive an up to 17% greater LCOE. We also show that such real-world limitations can cause substantial changes in system design both in terms of the spatial pattern of where generators are located and the capacity mix of the system. Thus we demonstrate the large impact simultaneously considering a set of nexus factors can have on future GB power systems. Finally, given our plausible assumptions about key energy-land-water restrictions and emission limits effecting the GB power system in 2050, the cost optimal penetration of VREs is found to be at least 50%.