Abstract
A control technique is proposed in this paper for control of modular multilevel converters (MMC) in highvoltage direct current (HVDC) transmission systems. Six independent dynamical state variables are considered in the proposed control technique, including two ac currents, three circulating currents, and the dc-link voltage, for effectively attaining the switching state functions of MMCs, as well as for an accurate control of the circulating currents. Several analytical expressions are derived based on the reference values of the state variables for obtaining the MMC switching functions under steady state operating conditions. In addition, dynamic parts of the switching functions are accomplished by the direct Lyapunov method to guarantee stable operation of the proposed technique for control of MMCs in HVDC systems. Moreover, the capability curve of MMC is developed to validate maximum power injection from MMCs into the power grid and/ or loads. The impacts of the variations of MMC output and dc-link currents on the stability of dc-link voltage are also evaluated in detail by small-signal analysis.

Abstract

Abstract
Modernization of electricity networks is currently being carried out using the concept of the smart grid; hence, the active participation of end-user consumers and distributed generators will be allowed in order to increase system efficiency and renewable power accommodation. In this context, this paper proposes a comprehensive methodology to optimally control lead-acid batteries operating under dynamic pricing schemes in both independent and aggregated ways, taking into account the effects of the charge controller operation, the variable efficiency of the power converter, and the maximum capacity of the electricity network. A genetic algorithm is used to solve the optimization problem in which the daily net cost is minimized. The effectiveness and computational efficiency of the proposed methodology is illustrated using real data from the Spanish electricity market during 2014 and 2015 in order to evaluate the effects of forecasting error of energy prices, observing an important reduction in the estimated benefit as a result of both factors: 1) forecasting error and 2) power system limitations.

Abstract
Prior statistical knowledge of atmospheric turbulence is essential for designing, optimizing and evaluating tomographic adaptive optics systems. We present the statistics of the vertical profiles of CN2 and the outer scale at Maunakea estimated using a SLOpe Detection And Ranging (SLODAR) method from on-sky telemetry taken by a multi-object adaptive optics (MOAO) demonstrator, called RAVEN, on the Subaru telescope. In our SLODAR method, the profiles are estimated by fitting the theoretical autocorrelations and cross-correlations of measurements from multiple Shack-Haltmann wavefront sensors to the observed correlations via the non-linear Levenberg-Marquardt Algorithm (LMA). The analytical derivatives of the spatial phase structure function with respect to its parameters for the LMA are also developed. From a total of 12 nights in the summer season, a large ground CN2 fraction of 54.3 per cent is found, with median estimated seeing of 0.460 arcsec. This median seeing value is below the results for Maunakea from the literature (0.6-0.7 arcsec). The average CN2 profile is in good agreement with results from the literature, except for the ground layer. The median value of the outer scale is 25.5 m and the outer scale is larger at higher altitudes; these trends of the outer scale are consistent with findings in the literature.

Abstract
We demonstrate in this research that surface-enhanced resonance Raman scattering combined with Raman imaging can be effectively used for analysis of distinct forms of organic dyes in antimicrobial Ag-loaded textile fibers. The potential of this approach, as a non-destructive characterization method of fabrics, was evaluated with Raman studies performed on the molecular forms of methylene blue (MB), used here as the organic dye model. On the basis of the surface-enhanced Raman scattering spectra of MB monomers and dimers, the Raman imaging of Ag-loaded linen fibers previously treated with MB solution was performed and then used for identification of the adsorbate species in distinct regions of the substrates. A semi-quantitative analysis is then performed by considering the area of the Raman bands ascribed to the MB molecular forms and image analysis applied to Raman images. Copyright (c) 2017 John Wiley & Sons, Ltd.

Abstract
This work describes an experimental setup that was developed in order to automate the One-dimensional consolidation properties of soil test. This experimental setup assures repeatability in the data acquisition test, avoiding human errors. The described setup is based on LabVIEW, LVDT sensors, a 16 Bit Data Acquisition Board, a Load device and a Consolidometer. The experimental setup was developed according to the standard ASTM D2435 / D2435M - 11.