The current high energy consumption is a constant global risk due to the impact that this causes on the planet, multiple solutions from the technical, social and economic points of view have sought to mitigate these problems. One of these solutions is known as microgrid, which integrates renewable energy sources through power interfaces in order to provide quality electric power service. The use of DC / AC converters in microgrids is fundamental and therefore has been investigated from the topologies, modulation and control schemes. One of these techniques is known as Virtual Synchronous Generators or Synchronverter, where the inverter is searched for as a synchronous generator. Therefore, in the following article the Synchronverter technique and proportional resonant control is developed to operate inverters in parallel with in an electrical microgrid.

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Given a graph, like a social/computer network or the blogosphere, in which an infection (or meme or virus) has been spreading for some time, how to select the k best nodes for immunization/quarantining immediately? Most previous works for controlling propagation (say via immunization) have concentrated on developing strategies for vaccination pre-emptively before the start of the epidemic. While very useful to provide insights in to which baseline policies can best control an infection, they may not be ideal to make real-time decisions as the infection is progressing.In this paper, we study how to immunize healthy nodes, in presence of already infected nodes. Efficient algorithms for such a problem can help public-health experts make more informed choices. First we formulate the Data-Aware Vaccination problem, and prove it is NP-hard and also that it is hard to approximate. Secondly, we propose two effective polynomial-time heuristics DAVA and DAVA-fast. Finally, we also demonstrate the scalability and effectiveness of our algorithms through extensive experiments on multiple real networks including epidemiology datasets, which show substantial gains of up to 10 times more healthy nodes at the end.

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Here, we show that NH2-MIL-88B(Fe) can be used as a peroxidase-like catalyst for Fenton-like degradation of methylene blue (MB) in water. The iron-based NH2-MIL-88B(Fe) metal organic framework (MOF) was synthesized by a facile and rapid microwave heating method. It was characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, powder X-ray diffraction, and the Brunauer–Emmett–Teller method. The NH2-MIL-88B(Fe) MOF possesses intrinsic oxidase-like and peroxidase-like activities. The reaction parameters that affect MB degradation were investigated, including the solution pH, NH2-MIL-88B(Fe) MOF and H2O2 concentrations, and temperature. The results show that the NH2-MIL-88B(Fe) MOF exhibits a wide working pH range (pH 3.0–11.0), temperature tolerance, and good recyclability for MB removal. Under the optimal conditions, complete removal of MB was achieved within 45 min. In addition, removal of MB was above 80% after five cycles, showing the good recyclability of NH2-MIL-88B(Fe). The NH2-MIL-88B(Fe) MOF has the features of easy preparation, high efficiency, and good recyclability for MB removal in a wide pH range. Electron spin resonance and fluorescence probe results suggest the involvement of hydroxyl radicals in MB degradation. These findings provide new insight into the application of high-efficient MOF-based Fenton-like catalysts for water purification.

Conspectus The past few years have witnessed an exciting revival of the research interest in two-dimensional (2D) lead halide perovskites. The renaissance is strongly motivated by the great success of their three-dimensional (3D) counterparts in optoelectronic applications. Different from 3D lead halide perovskites where free carriers are generated upon photoexcitation, 2D lead halide perovskites experience weaker dielectric screening and stronger quantum confinement effects. Therefore, strongly bound excitons with binding energy of up to a few hundreds of meV are considered to be the main excited-state species responsible for optoelectronic processes in 2D perovskites. In addition to strong excitonic effects, polaronic effects are also inherent in the soft and anharmonic lattice of lead halide perovskites, and polaronic structural relaxation is found to strongly renormalize carrier excited-state behaviors. For example, ferroelectric large polaron formation and liquid-like solvation of band edge carriers are proposed to account for the exceptional properties of 3D lead halide perovskites. As for 2D lead halide perovskites, polaronic characteristics have also been observed in exciton spectral characters, but how the interplay between excitonic effect and polaronic effect redefines the nature of exciton polarons and their excited-state behaviors still remains largely unexplored. In this Account, we discuss our recent experimental findings about the excited-state properties of exciton polarons in 2D lead halide perovskites. We begin our discussion by introducing a conventional view of strongly bound excitons in 2D lead halide perovskites with large exciton binding energy, which is typically estimated from steady-state absorption spectra. However, owing to the soft and anharmonic lattice, excitons in 2D lead halide perovskites exhibit significant polaronic characters and exist as exciton polarons. It is still unclear how polaronic effects would affect the exciton properties in 2D lead halide perovskites, especially in their excited-state dynamics. By probing exchange interaction, we found that both intra- and inter-exciton Coulomb interaction strengths are substantially weakened by the polaronic screening effect, which is manifested as (1) a counter­intuitively longer exciton spin lifetime by almost an order of magnitude or a smaller intraexcitonic interaction strength with temperature increasing from 80 to 340 K and (2) an order of magnitude smaller interexcitonic interaction strength compared to another prototypical 2D semiconductor named transition-metal dichalcogenides (TMDCs) with a comparable steady-state exciton binding energy. We further discuss the interplay between the long- and short-range exciton–phonon interaction and conclude that the exciton–phonon interaction strength is in an intermediate regime and the exciton polaron is momentarily trapped in 2D perovskites, that is, a dynamic exciton polaron. Finally, we highlight prospective opportunities with ligand and cation engineering to regulate the excito...

Time-series Vegetation Indices (VIs) are usually used for estimating grain yield. However, multi-temporal VIs may be affected by different background, illumination, and atmospheric conditions, so the absolute differences among time-series VIs may include the effects induced from external conditions in addition to vegetation changes, which will pose a negative effect on the accuracy of crop yield estimation. Therefore, in this study, the parcel-based relative vegetation index ( ΔVI ) and the parcel-based relative yield are proposed and further used to estimate rice yield. Hyperspectral images at key growth stages, including tillering stage, jointing stage, booting stage, heading stage, filling stage, and ripening stage, as well as rice yield, were obtained with Rikola hyperspectral imager mounted on Unmanned Aerial Vehicle (UAV) in 2017 growing season. Three types of parcel-level relative vegetation indices, including Relative Normalized Difference Vegetation Index (RNDVI), Relative Ratio Vegetation Index (RRVI), and Relative Difference Vegetation Index (RDVI) are created by using all possible two-band combinations of discrete channels from 500 to 900 nm. The optimal VI type and its band combinations at different growth stages are identified for rice yield estimation. Furthermore, the optimal combinations of different growth stages for yield estimation are determined by F -test and validated using leave-one-out cross validation (LOOCV) method. The comparison results show that, for the single-growth-stage model, RNDVI [880,712] at booting stage has the best correlation with rice yield with a R 2 -value of 0.75. For the multiple-growth-stage model, RNDVI [808,744] at jointing stage, RNDVI [880,712] at booting stage and RNDVI [808,744] at filling stage gain a higher R 2 -value of 0.83 with the mean absolute percentage error of estimated rice yield of 3%. The study demonstrates that the proposed method with parcel-level relative vegetation indices and relative yield can achieve higher yield estimation accuracy because it can make full use of the advantage that remote sensing can monitor relative changes accurately. The new method will further enrich the technology system for crop yield estimation based on remotely sensed data.