Double-Layer Compressive Sensing Based Efficient DOA Estimation in WSAN with Block Data Loss.

Accurate information acquisition is of vital importance for wireless sensor array network (WSAN) direction of arrival (DOA) estimation. However, due to the lossy nature of low-power wireless links, data loss, especially block data loss induced by adopting a large packet size, has a catastrophic effect on DOA estimation performance in WSAN. In this paper, we propose a double-layer compressive sensing (CS) framework to eliminate the hazards of block data loss, to achieve high accuracy and efficient DOA estimation.

Efficient Sparse Signal Transmission over a Lossy Link Using Compressive Sensing.

Reliable data transmission over lossy communication link is expensive due to overheads for error protection. For signals that have inherent sparse structures, compressive sensing (CS) is applied to facilitate efficient sparse signal transmissions over lossy communication links without data compression or error protection. The natural packet loss in the lossy link is modeled as a random sampling process of the transmitted data, and the original signal will be reconstructed from the lossy transmission results using the CS-based reconstruction method at the receiving end.

[Association of MMP14 gene polymorphisms and osteoporosis in Zhuang men from Baise region of Guangxi].

Objective: To assess the association between membrane type 1 matrix metalloproteinase gene (MT1-MMP, MMP14) polymorphisms and osteoporosis in Zhuang men from Baise region of Guangxi.

Methods: Genotypes of 5 loci (rs1003349, rs3751488, rs2269213, rs2236303 and rs743257) of MMP14 gene in 301 Zhuang men were determined with single base extension methods, and bone mineral density (BMD) at left calcaneus was evaluated with quantitative ultrasound with measured values of broadband ultrasonic attenuation (BUA). The subjects were divided according to BMD into osteoporosis group, osteopenia group and normal bone density group.