Abstract
There are many man-made structures near the ocean, in the so called splash zone. These structures are submitted to corrosion and need to be inspected periodically, which is difficult to be performed by humans. Therefore, automated solutions should be devised, able to withstand the conditions found there. Given that some animals live in this environment, the authors propose the development of a biological inspired robot for achieving such inspection tasks. With this purpose, a biomechanical study of the spider crab was developed, focusing on the anatomy and locomotion of this animal, using the Matlab/Simulink SimMechanics toolbox. © 2018 by World Scientific Publishing Co. Pte. Ltd.

Abstract
Microgrid (MG) is a relatively new concept for the integration of distributed generation (DG) along with the loads in a distribution system. Islanded microgrid can be considered as a weak grid that has less inertia compared with the conventional power system. This reality makes the microgrid vulnerable to contingencies. Towards a flexible, safe and secure operation of an islanded MG, researchers have introduced a hierarchical control structure comprising tertiary, secondary and primary control. The primary control plays an important role in maintaining the voltage and frequency stability by sharing the loads among the DGs. This paper reviews and categorizes various primary control methods that have been introduced to control the voltage and frequency of inverter-based microgrids. Moreover, the reviewed methods in terms of their potential advantages and disadvantages are compared. Finally, the future trends are presented.

Abstract
In wireless networking R&D we typically depend on experimentation to further evaluate a solution, as simulation is inherently a simplification of the real-world. However, experimentation is limited in aspects where simulation excels, such as repeatability and reproducibility. Real wireless experiments are hardly repeatable. Given the same input they can produce very different output results, since wireless communications are influenced by external random phenomena such as noise, interference, and multipath. Real experiments are also difficult to reproduce due to testbed operational constraints and availability. We have previously proposed the Trace-based Simulation (TS) approach, which uses the TraceBasedPropagationLossModel to successfully reproduce past experiments. Yet, in its current version, the TraceBasedPropagationLossModel only supports point-to-point scenarios. In this paper, we introduce a new version of the model that supports Multiple Access wireless scenarios. To validate the new version of the model, the network throughput was measured in a laboratory testbed. The experimental results were then compared to the network throughput achieved using the ns-3 trace-based simulation and a pure ns-3 simulation, confirming the TS approach is valid for multiple access scenarios too.

Abstract
Software developers are more and more eager to understand their code's energy performance. However, even with such knowledge it is difficult to know how to improve the code. Indeed, little tool support exists to understand the energy consumption profile of a software system and to eventually (automatically) improve its code. In this paper we present a tool termed jStanley which automatically finds collections in Java programs that can be replaced by others with a positive impact on the energy consumption as well as on the execution time. In seconds, developers obtain information about energy-eager collection usage. jStanley will further suggest alternative collections to improve the code, making it use less time, energy, or a combination of both. The preliminary evaluation we ran using jStanley shows energy gains between 2% and 17%, and a reduction in execution time between 2% and 13%. A video can be seen at https://greensoftwarelab.github.io/jStanley.

Abstract
Over the last few years, electrical storage and especially battery systems have seen a strong rise in interest. In several countries, as for instance in Germany, lithium-ion batteries are now commonly deployed in end-consumer installations to shift local generation from photovoltaic systems in time. A further application for storage is price arbitrage, which corresponds to an operation strategy benefitting from price differentials. In this work, we describe a Mixed Integer Problem to optimize the storage dispatch considering both the 15- and the 60-min auctions in use in Germany. Furthermore, in addition to the calendric lifetime, the limitation to a certain number of cycles is considered in the evaluation. Last, it was conducted a sensitivity analysis to identify the price volatility level that is required to generate a profit from arbitrage operations. Therefore, a market price process with adjustable parameters has been implemented.

Abstract
The highly elliptical, 16-year-period orbit of the star S2 around the massive black hole candidate Sgr A* is a sensitive probe of the gravitational field in the Galactic centre. Near pericentre at 120 AU approximate to 1400 Schwarzschild radii, the star has an orbital speed of approximate to 7650 km s(-1), such that the first-order effects of Special and General Relativity have now become detectable with current capabilities. Over the past 26 years, we have monitored the radial velocity and motion on the sky of S2, mainly with the SINFONI and NACO adaptive optics instruments on the ESO Very Large Telescope, and since 2016 and leading up to the pericentre approach in May 2018, with the four-telescope interferometric beam-combiner instrument GRAVITY. From data up to and including pericentre, we robustly detect the combined gravitational redshift and relativistic transverse Doppler effect for S2 of z = Delta lambda/lambda approximate to 200 km s(-1)/c with different statistical analysis methods. When parameterising the post-Newtonian contribution from these effects by a factor f, with f = 0 and f = 1 corresponding to the Newtonian and general relativistic limits, respectively, we find from posterior fitting with different weighting schemes f = 0.90 +/- 0.09 vertical bar(stat) +/- 0.151 vertical bar(sys). The S2 data are inconsistent with pure Newtonian dynamics.