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Biological conversion of sulfide, acetate, and nitrate to, respectively, elemental sulfur (S(0)), carbon dioxide, and nitrogen-containing gas (such as N2) at NaCl concentration of 35-70 g/L was achieved in an expanded granular sludge bed (EGSB) reactor. A C/N ratio of 1:1 was noted to achieve high sulfide removal and S(0) conversion rate at high salinity. The extracellular polymeric substance (EPS) quantities were increased with NaCl concentration, being 11.4-mg/g volatile-suspended solids at 70 mg/L NaCl. The denitrifying sulfide removal (DSR) consortium incorporated Thauera sp. and Halomonas sp. as the heterotrophs and Azoarcus sp. being the autotrophs at high salinity condition. Halomonas sp. correlates with the enhanced DSR performance at high salinity.

State-of-the-art synthesis methods for microwave passive components suffer from the following drawbacks. They either have good efficiency but highly depend on the accuracy of the equivalent circuit models, which may fail the synthesis when the frequency is high, or they fully depend on electromagnetic (EM) simulations, with a high solution quality but are too time consuming. To address the problem of combining high solution quality and good efficiency, a new method, called memetic machine learning-based differential evolution (MMLDE), is presented. The key idea of MMLDE is the proposed online surrogate modelbased memetic evolutionary optimization mechanism, whose training data are generated adaptively in the optimization process. In particular, by using the differential evolution algorithm as the optimization kernel and EM simulation as the performance evaluation method, high-quality solutions can be obtained. By using Gaussian process and artificial neural network in the proposed search mechanism, surrogate models are constructed online to predict the performances, saving a lot of expensive EM simulations. Compared with available methods with the best solution quality, MMLDE can obtain comparable results, and has approximately a tenfold improvement in computational efficiency, which makes the computational time for optimized component synthesis acceptable. Moreover, unlike many available methods, MMLDE does not need any equivalent circuit models or any coarse-mesh EM models. Experiments of 60 GHz syntheses and comparisons with the state-of-art methods provide evidence of the important advantages of MMLDE.

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Many-core chip design has become a popular means to sustain the exponential growth of chip-level computing performance. The main advantage lies in the exploitation of parallelism, distributively and massively. Consequently, the on-chip communication fabric becomes the performance determinant. In the meantime, the introduction of Ultra-Wideband (UWB) interconnect brings in the new opportunity for giga-bps communication bandwidth, milliwatts communication power, and low cost implementation for millimeter range on-chip communication for future chip generations. In this paper, we study multi-channel wireless Network-on-Chip (McWiNoC) with ultra-short RF/wireless links for multi-hop communication. We first present the benefit of high bandwidth, low latency and flexible topology configurations provided by this new on-chip interconnection network. We then propose a distributed and deadlockfree location based routing scheme. We further design an efficient channel arbitration scheme to grant multi-channel access. With a few representative synthetic traffic patterns and SPLASH-II benchmarks, we demonstrate that McWiNoC can achieve 23.3% average performance improvement and 65.3% average end-to-end latency reduction over a baseline NoC of 8 × 8 metal wired mesh.

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