Robust signal recovery algorithm for structured perturbation compressive sensing

It is understood that the sparse signal recovery with a standard compressive sensing（CS） strategy requires the measurement matrix known as a priori. The measurement matrix is, however, often perturbed in a practical application.In order to handle such a case, an optimization problem by exploiting the sparsity characteristics of both the perturbations and signals is formulated. An algorithm named as the sparse perturbation signal recovery algorithm（SPSRA） is then proposed to solve the formulated optimization problem. The analytical results show that our SPSRA can simultaneously recover the signal and perturbation vectors by an alternative iteration way, while the convergence of the SPSRA is also analytically given and guaranteed. Moreover, the support patterns of the sparse signal and structured perturbation shown are the same and can be exploited to improve the estimation accuracy and reduce the computation complexity of the algorithm. The numerical simulation results verify the effectiveness of analytical ones.

Effects of C_6-HSL on Potato Growth and Capacity against Soft Rot Disease

[Objective]The aim of this study was to investigate whether communication signal C6-HSL among individual bacteria can influence plant growth and disease resistance ability. [Method]With potato virus-free plantlets as the test materials and C6-HSL as the inducer,the potato＇s growth and the ability of resistance against Erwinia carotovora subp carotovora were tested after being treated by C6-HSL with different concentrations. The effects of C6-HSL on plant landmark defense enzyme activities and H2O2 content in potato leaves were measured especially. [Result]C6-HSL with different concentrations could obviously inhibit the growth rate of root and the number of roots,but had no effect on plant height,number of nodes and leaf size. POD or SOD activity and H2O2 content in plant landmark defense enzymes significantly increased after induction of C6-HSL,but PAL and PPO activity had no obvious change. In the resistant test,potato plants induced by C6-HSL could inhibit the infection of Erwinia carotovora subp carotovora effectively,and its incidence was significantly lower than the control group. [Conclusion]Bacteria AHL can be possibly used as a new kind of plant disease-resistant activator.

Flexible bioelectronics for physiological signals sensing and disease treatment

Flexible bioelectronics,including wearable and implantable electronics,have revolutionized the way of human-machine interaction due to the fact that they can provide natural and seamless interactions with humans and keep stable and durable at strained states.As sensor elements or biomimetic actuators,flexible bioelectronics can dynamically sense and monitor physiological signals,reveal real-time physical health information and provide timely precise stimulations or treatments.Thus,the flexible bioelectronics are playing increasingly important roles in human-health monitoring and disease treatment,which will significantly change the future of healthcare as well as our relationships with electronics.This review summarizes recent major progress in the development of flexible substrates or encapsulation materials,sensors,circuits and energy-autonomous powers toward digital healthcare monitoring,emphasizing its role in biomedical applications in vivo and problems in practical applications.A future perspective into the challenges and opportunities in emerging flexible bioelectronics designs for the next-generation healthcare monitoring systems is also presented.

Human Respiration Rate Estimation Using Ultra-wideband Distributed Cognitive Radar System

It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present a multi-ray propagation model for UWB signal,which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces,A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment.This model enables replication of time-varying multipath profiles due to the displacement of a human chest.Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate.The analytical framework can serve as a basis in the planning and evaluation of future rheasurement programs.We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture.

Plant mineral nutrient sensing and signaling

As terrestrial plants are sessile organisms and therefore must directly deal with an often complex and changing environment, they have had to develop complex and elegant strategies to survive and thrive in the face of environmental stress. This is particularly true for plant adaptation to the soil environment, where essential mineral nutrients often are found at sub- optimal levels and their concentrations can vary significantly, both spatially and temporally. Furthermore, plants also at times have to respond to excessively high and potentially toxic levels of essential nutrients, as well as toxic levels of non- essential metals and metalloids in the soil. Although plant mineral nutrition as a bona ~ide research discipline has a history of over 15o years, beginning with the pioneering work of Justus Von Liebieg and others in the mid-1800＇s, it is only very recently that researchers have begun to truly appreciate how sophisticated plants are with regards to the sensing of their mineral status and the maintaining of mineral homeostasis in the plant.

Coherence-based performance analysis of the generalized orthogonal matching pursuit algorithm

The performance guarantees of generalized orthogonal matching pursuit（ gOMP） are considered in the framework of mutual coherence. The gOMP algorithmis an extension of the well-known OMP greed algorithmfor compressed sensing. It identifies multiple N indices per iteration to reconstruct sparse signals.The gOMP with N≥2 can perfectly reconstruct any K-sparse signals frommeasurement y = Φx if K 〈1/N（1/μ-1） ＋1,where μ is coherence parameter of measurement matrix Φ. Furthermore,the performance of the gOMP in the case of y = Φx ＋ e with bounded noise ‖e‖2≤ε is analyzed and the sufficient condition ensuring identification of correct indices of sparse signals via the gOMP is derived,i. e.,K 〈1/N（1/μ-1）＋1-（2ε/Nμxmin） ,where x min denotes the minimummagnitude of the nonzero elements of x. Similarly,the sufficient condition in the case of G aussian noise is also given.

A Reducing Iteration Orthogonal Matching Pursuit Algorithm for Compressive Sensing

In recent years, Compressed Sensing（CS） has been a hot research topic. It has a wide range of applications, such as image processing and speech signal processing owing to its characteristic of removing redundant information by reducing the sampling rate. The disadvantage of CS is that the number of iterations in a greedy algorithm such as Orthogonal Matching Pursuit（OMP） is fixed, thus limiting reconstruction precision.Therefore, in this study, we present a novel Reducing Iteration Orthogonal Matching Pursuit（RIOMP） algorithm that calculates the correlation of the residual value and measurement matrix to reduce the number of iterations.The conditions for successful signal reconstruction are derived on the basis of detailed mathematical analyses.When compared with the OMP algorithm, the RIOMP algorithm has a smaller reconstruction error. Moreover, the proposed algorithm can accurately reconstruct signals in a shorter running time.

Construction of compressed sensing matrixes based on the singular pseudo-symplectic space over finite fields

Compressed sensing（CS） provides a new approach to acquire data as a sampling technique and makes it sure that a sparse signal can be reconstructed from few measurements. The construction of compressed matrixes is a central problem in compressed sensing. This paper provides a construction of deterministic CS matrixes, which are also disjunct and inclusive matrixes, from singular pseudo-symplectic space over finite fields of characteristic 2. Our construction is superior to De Vore＇s construction under some conditions and can be used to reconstruct sparse signals through an efficient algorithm.

Characteristic difference analysis and transfer parameter determination for different satellites to detect NDVI values

Here we propose a new method of NDVI difference analysis and NDVI difference correction for multi-sensors to detect NDVI.This method integrate PROSPECT model,SAIL model and MODTRAN atmospheric radioactive transfer model to simulate the remote sensing signals of different satellites for both NDVI difference analysis and correction without using real satellite images.The effects of both the sensors' spectral responses and atmospheric condition are simulated,and the differences among NDVI values derived from thirty different satellites are analyzed quantitatively.Focusing on the conversions of NDVI values among different satellites,through linear regression analysis,we estimate the transfer parameters between any two different satellite NDVI values,and present the lookup tables of transfer parameters under the atmospheric conditions of three surface visibility range values (10,23 and 50 km).The proposed method is useful for NDVI applications and analyses for multi-sensors.

General principles of developing novel radioprotective agents for nuclear emergency

With the rapid application of nuclear energy and radiological technology in national economy and military field,the risk of nuclear accidents increases as well.Exposure to irradiation causes severe damages to the human body,and radioprotective agents are required for medical protection.To find the safe and effective radioprotective agents is the key for nuclear emergency.Recently,Toll like receptors(TLRs)and PHD-HIF oxygen sensing signal pathway have been extensively studied for radioprotection.Great progress has been made in this field and a number of radioprotective agents have been found.In this review,we have summarized recent findings of radioprotective roles of TLRs signaling pathway and PHD-HIF signaling pathway and discussed the general principles of developing novel radioprotective agents.These findings will provide opportunities for developing new strategies to prevent IR-induced injuries in public health events.

Transcriptional Regulation of the Ambient Temperature Response by H2A.Z Nucleosomes and HSF1 Transcription Factors in Arabidopsis

Temperature influences the distribution, range, and phenology of plants. The key transcriptional activators of heat shock response in eukaryotes, the heat shock factors （HSFs）, have undergone large-scale gene amplification in plants. While HSFs are central in heat stress responses, their role in the response to ambient temperature changes is less well understood. We show here that the warm ambient temperature transcriptome is dependent upon the HSFA1 clade ofArabidopsis HSFs, which cause a rapid and dynamic eviction of H2A.Z nucleosomes at target genes. A transcriptional cascade results in the activation of multiple downstream stress-responsive transcription factors, triggering large-scale changes to the transcriptome in response to elevated temperature. H2A.Z nucleosomes are enriched at temperature-responsive genes at non-inducible temperature, and thus likely confer inducibility of gene expression and higher responsive dynamics. We propose that the antagonistic effects of H2A.Z and HSF1 provide a mechanism to activate gene expression rapidly and precisely in response to temperature, while preventing leaky transcription in the absence of an activation signal.