A combinatorial criterion for k-separability of multipartite Dicke states

We derive a combinatorial criterion for detecting k-separability of N-partite Dicke states. The criterion is efficiently computable and implementable without full state tomography. We give examples in which the criterion succeeds, where known criteria fail

Color Filtering Localization for Three-Dimensional Underwater Acoustic Sensor Networks

Accurate localization for mobile nodes has been an important and fundamental problem in underwater acoustic sensor networks (UASNs). The detection information returned from a mobile node is meaningful only if its location is known. In this paper, we propose two localization algorithms based on color filtering technology called PCFL and ACFL. PCFL and ACFL aim at collaboratively accomplishing accurate localization of underwater mobile nodes with minimum energy expenditure. They both adopt the overlapping signal region of task anchors which can communicate with the mobile node directly as the current sampling area. PCFL employs the projected distances between each of the task projections and the mobile node, while ACFL adopts the direct distance between each of the task anchors and the mobile node. Also the proportion factor of distance is proposed to weight the RGB values. By comparing the nearness degrees of the RGB sequences between the samples and the mobile node, samples can be filtered out. And the normalized nearness degrees are considered as the weighted standards to calculate coordinates of the mobile nodes. The simulation results show that the proposed methods have excellent localization performance and can timely localize the mobile node. The average localization error of PCFL can decline by about 30.4% than the AFLA method.Comment: 18 pages, 11 figures, 2 table

A Novel Combined Modelling and Optimization Technique for Microwave Components

This paper presents a novel combined parametric modelling and design optimization technique for microwave components utilizing the neural networks. The proposed technique provides an iterative mechanism between ANN model training and design optimization update. This iterative mechanism is fully automated and requires no manual intervention. Furthermore, the proposed technique overcomes the limitations of the common ANN optimization strategy where the fixed training region of the ANN model limits the freedom of design optimization. The proposed technique automatically enlarges the ANN training region until an optimization solution satisfying the user’s design specification is met. Once the whole iterative process is finished, an accurate parametric model and an optimal solution satisfying the design specification are simultaneously generated. A parametric modelling and design optimization example of a wideband QuasiElliptic filter design is presented to demonstrate the validity of this technique

DREAMSeq: An Improved Method for Analyzing Differentially Expressed Genes in RNA-seq Data

RNA sequencing (RNA-seq) has become a widely used technology for analyzing global gene-expression changes during certain biological processes. It is generally acknowledged that RNA-seq data displays equidispersion and overdispersion characteristics; therefore, most RNA-seq analysis methods were developed based on a negative binomial model capable of capturing both equidispersed and overdispersed data. In this study, we reported that in addition to equidispersion and overdispersion, RNA-seq data also displays underdispersion characteristics that cannot be adequately captured by general RNA-seq analysis methods. Based on a double Poisson model capable of capturing all data characteristics, we developed a new RNA-seq analysis method (DREAMSeq). Comparison of DREAMSeq with five other frequently used RNA-seq analysis methods using simulated datasets showed that its performance was comparable to or exceeded that of other methods in terms of type I error rate, statistical power, receiver operating characteristics (ROC) curve, area under the ROC curve, precision-recall curve, and the ability to detect the number of differentially expressed genes, especially in situations involving underdispersion. These results were validated by quantitative real-time polymerase chain reaction using a real Foxtail dataset. Our findings demonstrated DREAMSeq as a reliable, robust, and powerful new method for RNA-seq data mining. The DREAMSeq R package is available at http://tanglab.hebtu.edu.cn/tanglab/Home/DREAMSeq

A 0.1–5.0 GHz flexible SDR receiver with digitally assisted calibration in 65 nm CMOS

© 2017 Elsevier Ltd. All rights reserved.A 0.1–5.0 GHz flexible software-defined radio (SDR) receiver with digitally assisted calibration is presented, employing a zero-IF/low-IF reconfigurable architecture for both wideband and narrowband applications. The receiver composes of a main-path based on a current-mode mixer for low noise, a high linearity sub-path based on a voltage-mode passive mixer for out-of-band rejection, and a harmonic rejection (HR) path with vector gain calibration. A dual feedback LNA with “8” shape nested inductor structure, a cascode inverter-based TCA with miller feedback compensation, and a class-AB full differential Op-Amp with Miller feed-forward compensation and QFG technique are proposed. Digitally assisted calibration methods for HR, IIP2 and image rejection (IR) are presented to maintain high performance over PVT variations. The presented receiver is implemented in 65 nm CMOS with 5.4 mm2 core area, consuming 9.6–47.4 mA current under 1.2 V supply. The receiver main path is measured with +5 dB m/+5dBm IB-IIP3/OB-IIP3 and +61dBm IIP2. The sub-path achieves +10 dB m/+18dBm IB-IIP3/OB-IIP3 and +62dBm IIP2, as well as 10 dB RF filtering rejection at 10 MHz offset. The HR-path reaches +13 dB m/+14dBm IB-IIP3/OB-IIP3 and 62/66 dB 3rd/5th-order harmonic rejection with 30–40 dB improvement by the calibration. The measured sensitivity satisfies the requirements of DVB-H, LTE, 802.11 g, and ZigBee.Peer reviewedFinal Accepted Versio

Adaptive and degenerative evolution of the S-Phase Kinase-Associated Protein 1-Like family in Arabidopsis thaliana

Genome sequencing has uncovered tremendous sequence variation within and between species. In plants, in addition to large variations in genome size, a great deal of sequence polymorphism is also evident in several large multi-gene families, including those involved in the ubiquitin-26S proteasome protein degradation system. However, the biological function of this sequence variation is yet not clear. In this work, we explicitly demonstrated a single origin of retroposed Arabidopsis Skp1-Like (ASK) genes using an improved phylogenetic analysis. Taking advantage of the 1,001 genomes project, we here provide several lines of polymorphism evidence showing both adaptive and degenerative evolutionary processes in ASK genes. Yeast two-hybrid quantitative interaction assays further suggested that recent neutral changes in the ASK2 coding sequence weakened its interactions with some F-box proteins. The trend that highly polymorphic upstream regions of ASK1 yield high levels of expression implied negative expression regulation of ASK1 by an as-yet-unknown transcriptional suppression mechanism, which may contribute to the polymorphic roles of Skp1-CUL1-F-box complexes. Taken together, this study provides new evolutionary evidence to guide future functional genomic studies of SCF-mediated protein ubiquitylation