With the large-scale commercialization of 5G networks, the era of Internet of Things (IoT), which is oriented toward the Internet of Everything (IoE), is coming. Under the circumstance, reliable and secure communication are the great challenges for future wireless network because of the broadcasting characteristics of electromagnetic wave. Physical-layer security (PLS) is an effective way to ensure secure communication by exploiting random nature of fading channels. Motivated by this, we investigate PLS of the wireless-powered cooperative multirelaying for IoT networks in the presence of eavesdropper with the estimation errors of channel (EEC) and imbalance between in-phase and quadrature-phase (IIQ). Specifically, the relays can be charged by the source with the aid of energy harvesters, and a novel more secure modify-and-forward (MF) relay protocol is proposed. For further improving energy efficiency and reducing extra interference, the$K$th superior relay selection scheme is proposed since some best ones are not available due to some scheduling or failure. Based on the system under study, we derive the analytical expressions for the outage probability (OP), intercept probability (IP), and secrecy OP (SOP) to evaluate the reliable and secure performance of this consideration system. Particularly, we then analyze the asymptotic behaviors of the OP, IP, and SOP, respectively. Through computer simulation, we show that: 1) with EEC, the error floors of the OP and SOP are of presence; 2) multiple relays lead to better OP and SOP performance; and 3) IIQ improves the security and is detrimental to the system reliability.

This paper deals with the global exponential stability for delayed recurrent neural networks (DRNNs). By constructing an augmented Lyapunov-Krasovskii functional and adopting the reciprocally convex combination approach and Wirtinger-based integral inequality, delay-dependent global exponential stability criteria are derived in terms of linear matrix inequalities. Meanwhile, a general and effective method on global exponential stability analysis for DRNNs is given through a lemma, where the exponential convergence rate can be estimated. With this lemma, some global asymptotic stability criteria of DRNNs acquired in previous studies can be generalized to global exponential stability ones. Finally, a frequently utilized numerical example is carried out to illustrate the effectiveness and merits of the proposed theoretical results.

SUMMARY: Here we present Sequence Variant Analyzer (SVA), a software tool that assigns a predicted biological function to variants identified in next-generation sequencing studies and provides a browser to visualize the variants in their genomic contexts. SVA also provides for flexible interaction with software implementing variant association tests allowing users to consider both the bioinformatic annotation of identified variants and the strength of their associations with studied traits. We illustrate the annotation features of SVA using two simple examples of sequenced genomes that harbor Mendelian mutations. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://www.svaproject.org.