Abstract
The resilient smart distribution system is intended to cope with low probability, high-risk extreme events, including extreme natural disasters. In this regard, the flexible partitioning distribution system into supply-sufficient microgrids can be considered an interesting subject. This paper introduces a novel technique for partitioning a smart distribution system into supply-sufficient microgrids. In the presented model, the impact of demand response programs and energy storage has been considered in the proposed framework. Furthermore, besides the electricity aspects, the effects of gas network infrastructure on flexible portioning are also investigated to improve system resiliency facing natural disasters. The proposed model aims to maximize served load, which has been structured as a mixed integer linear programming (MILP) problem. The IEEE 34 bus standard test system is used to investigate the effectiveness of the proposed structure. The results of the study show that the proposed structure can increase the served load and the supply-sufficiently of the smart grid power system.

Abstract
The Real-Time Monitoring and Performance Management suite tool, known as UIL (User Interface Layer), was developed in the FASTEN project, a R&D initiative financed by the innovation and research program H2020 within a bilateral Europe-Brazil call. UIL was conceived and deployed in the IIoT architecture of the project. The goal was to provide a usercentered assistance to the human operator for both decision-responsibility and control loop, in a continuously updating information fashion, related to system's state. In order to have experimental results, a qualitative assessment was conducted in an industrial environment. The architecture proposed was based on the adoption of a Knowledge Engineering User Interface to support Operator 4.0. Our empirical experiments point out to a successful set of results. Copyright (C) 2021 The Authors.

Abstract
Unmanned Aerial Vehicles (UAVs) are a key ingredient in the industry and in warehouse logistics digital transformation process, providing the ability to perform automatic cyclic counting and real-time inventory, localize hard-to-find items and reach narrow storage areas. The use of UAVs poses new challenges, such as indoor autonomous localization and navigation, collision avoidance and automated UAV fleet management. This paper addresses the development of a vision-based Graph-SLAM approach for UAV indoor localization without predefined warehouse markers positions. A framework is proposed and developed to support different commercial UAV platforms, allowing the estimation in real-time of the UAV position and attitude. Indoor experimental tests were carried out in order to evaluate the performance of the developed method, comparing the results obtained with an approach based on the pre-mapped markers position indoor localization method.

Abstract
Researchers have to ensure that their projects comply with Research Data Management (RDM) requirements. Consequently, the main funding agencies require Data Management Plans (DMPs) for grant applications. So, institutions are investing in RDM tools and implementing RDM workflows in order to support their researchers. In this context, we propose a collaborative DMP-building method that involves researchers, data stewards and other parties if required. This method was applied as part of an RDM workflow in research groups across several scientific domains. We describe it as a systematic approach and illustrate it through a set of case studies. We also address the DMP monitoring process during the life cycle of projects. The feedback from the researchers highlighted the advantages of creating DMPs and their growing need. So, there is motivation to improve the DMP support process according to the machine-actionable DMPs concept and to the best practices in each scientific community.

Abstract
Significant developments on semiconductor technology have captured the electronic industry and paved the way for dominating household appliances market. Typical loads in this market generally have nonlinear voltage current characteristics. Therefore, highly-integrated power-electronic based electrical equipment in the demand side has caused harmonic pollution, which is one of the most important power quality problems in distribution system operation. To address this issue, there have been significantly great attempts to keep total harmonic distortion (THD) and total demand distortion (TDD) levels within International standard limits defined by IEEE 519 and IEC 61000. On the other hand, load shifting has recently drawn special attention of power grid planners to improve system performance substantially in the smart grid paradigm. In this study, the real harmonic measurements of residential appliances (both linear and nonlinear) are carried out in the Smart Home Laboratory in Yildiz Technical University, Istanbul, Turkey. Different load profiles are then created with a high accuracy based on the measured voltage and current, active, reactive and apparent power. Also, three case studies are considered to investigate the impacts of load shifting strategies on power quality requirements in terms of satisfying the relevant standards. As a result, it is shown that the TDD value decreases below nearly 8% limitation by mitigating the harmonic distortion and the TDD index, which indicates the harmonic distortion effect on the system regarding the desired standard limits of IEEE.

Abstract
As life expectancy grows and the population requirements for satisfactory health and wellness levels increases, there is a clear opportunity for the incorporation of alternative techniques and tools for promoting health and preventing disease. One of these tools, is the use of thermal water-based treatments, commonly known as thermalism, as tools to trigger patients’ overall wellness. Despite the collective assumption of the effects of thermalism, there is little to no scientific evidence of these treatments, thus impairing the potential of this activity to become more widespread in society. Thus, with this paper, we present a conceptual model for a non-invasive sensing system based on wearables that can monitor a set of patients’ biomarkers which will serve as the basis for the validation of the effects of thermalism. This system will also serve as a management and operation control tool for thermal SPA managers and technical directors.