Investigation of Range Profiles from a Simplified Ship on Rough Sea Surface and Its Multipath Imaging Mechanisms

The range profiles of a two-dimension (2 D) perfect electric conductor (PEC) ship on a wind-driven rough sea surface are derived by performing an inverse discrete Fourier transform (IDFT) on the wide band backscattered field. The rough sea surface is assuming to be a PEC surface. The back scattered field is computed based on EM numerical simulation when the frequencies are sampled between 100 MHz and 700 MHz. Considering the strong coupling interactions between the ship and sea, the complicated multipath effect to the range profile characteristics is fully analyzed based on the multipath imaging mechanisms. The coupling mechanisms could be explained by means of ray theory prediction and numerical extraction of the coupling currents. The comparison of the range profile locations between ray theory prediction and surface current simulation is implemented and analyzed in this paper. Finally, the influence of different sea states on the radar target signatures has been examined and discussed

Analysis between ABO blood group and clinical outcomes in COVID-19 patients and the potential mediating role of ACE2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become the most common coronavirus that causes large-scale infections worldwide. Currently, several studies have shown that the ABO blood group is associated with coronavirus disease 2019 (COVID-19) infection and some studies have also suggested that the infection of COVID-19 may be closely related to the interaction between angiotensin-converting enzyme 2 (ACE2) and blood group antigens. However, the relationship between blood type to clinical outcome in critically ill patients and the mechanism of action is still unclear. The current study aimed to examine the correlation between blood type distribution and SARS-CoV-2 infection, progression, and prognosis in patients with COVID-19 and the potential mediating role of ACE2. With 234 patients from 5 medical centers and two established cohorts, 137 for the mild cohort and 97 for the critically ill cohort, we found that the blood type A population was more sensitive to SARS-CoV-2, while the blood type distribution was not relevant to acute respiratory distress syndrome (ARDS), acute kidney injury (AKI), and mortality in COVID-19 patients. Further study showed that the serum ACE2 protein level of healthy people with type A was significantly higher than that of other blood groups, and type O was the lowest. The experimental results of spike protein binding to red blood cells also showed that the binding rate of people with type A was the highest, and that of people with type O was the lowest. Our finding indicated that blood type A may be the biological marker for susceptibility to SARS-CoV-2 infection and may be associated with potential mediating of ACE2, but irrelevant to the clinical outcomes including ARDS, AKI, and death. These findings can provide new ideas for clinical diagnosis, treatment, and prevention of COVID-19

Plant immunity suppression by an exo-β-1,3-glucanase and an elongation factor 1α of the rice blast fungus

Fungal cell walls undergo continual remodeling that generates β-1,3-glucan fragments as products of endo-glycosyl hydrolases (GHs), which can be recognized as pathogen-associated molecular patterns (PAMPs) and trigger plant immune responses. How fungal pathogens suppress those responses is often poorly understood. Here, we study mechanisms underlying the suppression of β-1,3-glucan-triggered plant immunity by the blast fungus Magnaporthe oryzae. We show that an exo-β-1,3-glucanase of the GH17 family, named Ebg1, is important for fungal cell wall integrity and virulence of M. oryzae. Ebg1 can hydrolyze β-1,3-glucan and laminarin into glucose, thus suppressing β-1,3-glucan-triggered plant immunity. However, in addition, Ebg1 seems to act as a PAMP, independent of its hydrolase activity. This Ebg1-induced immunity appears to be dampened by the secretion of an elongation factor 1 alpha protein (EF1α), which interacts and co-localizes with Ebg1 in the apoplast. Future work is needed to understand the mechanisms behind Ebg1-induced immunity and its suppression by EF1α

Obtaining Sequential Efficiency for Concurrent Object-Oriented Languages

Concurrent object-oriented programming (COOP) languages focus the abstraction and encapsulation power of abstract data types on the problem of concurrency control. In particular, pure fine-grained concurrent object-oriented languages (as opposed to hybrid or data parallel) provides the programmer with a simple, uniform, and flexible model while exposing maximum concurrency. While such languages promise to greatly reduce the complexity of large-scale concurrent programming, the popularity of these languages has been hampered by efficiency which is often many orders of magnitude less than that of comparable sequential code. We present a sufficient set of techniques which enables the efficiency of fine-grained concurrent object-oriented languages to equal that of traditional sequential languages (like C) when the required data is available. These techniques are empirically validated by the application to a COOP implementation of the Livermore Loops. 1 Introduction The increasing use of ..

Digital Surface Model Generation for High Resolution Satellite Stereo Image Based on Modified Semi-global Matching

A method is proposed for generating digital surface model (DSM) of high resolution satellite imagery (HRSI) based on modified semi-global matching (SGM) algorithm.Firstly,the system error of the rational function model is compensated by using the geometric constraint relation between the image connection points.Based on the compensation model,the image is divided into blocks.The projection trajectory method is used to obtain the image pairs of the images.In the dense matching stage,the disparity map is computed using semi-global matching by layer after building the pyramids images,and an expansion corrosion algorithm for disparity graphs,which takes into account the image texture information,is introduced to constrain the range of parallax search,increase the number of effective pixels at the edge of the parallax map and reduce the memory overhead and computation time required for the algorithm.In the post processing stage of disparity image,the edge information of disparity image is protected by weighted median filtering algorithm.Finally,the DSM is acquired based on the forward intersection.The stereo images of World View 3 and ZY-3 to experiment are selected.The experimental results show that the DSM accuracy obtained by this method is nearly 1.5 times higher than that of GSD in elevation direction,and the edge characteristics of the object are maintained well.The algorithm is computationally efficient and has relatively low memory overhead

Series Arc Fault Detection Algorithm Based on Autoregressive Bispectrum Analysis

Arc fault is one of the most critical reasons for electrical fires. Due to the diversity, randomness and concealment of arc faults in low-voltage circuits, it is difficult for general methods to protect all loads from series arc faults. From the analysis of many series arc faults, a large number of high frequency signals generated in circuits are found. These signals are easily affected by Gaussian noise which is difficult to be eliminated as a result of frequency aliasing. Thus, a novel detection algorithm is developed to accurately detect series arc faults in this paper. Initially, an autoregressive model of the mixed high frequency signals is modelled. Then, autoregressive bispectrum analysis is introduced to analyze common series arc fault features. The phase information of arc fault signal is preserved using this method. The influence of Gaussian noise is restrained effectively. Afterwards, several features including characteristic frequency, fluctuation of phase angles, diffused distribution and incremental numbers of bispectrum peaks are extracted for recognizing arc faults. Finally, least squares support vector machine is used to accurately identify series arc faults from the load states based on these frequency features of bispectrum. The validity of the algorithm is experimentally verified obtaining arc fault detection rate above 97%

A hybrid execution model for fine-grained languages on distributed memory multicomputers

While ne-grained concurrent languages can naturally capture concurrency in many irregular and dynamic problems, their exibility has generally resulted in poor execution e ciency. In such languages the computation consists of many small threads which are created dynamically and synchronized implicitly. In order to minimize the overhead of these operations, we propose ahybrid execution model which dynamically adapts to runtime data layout, providing both sequential e ciency and low overhead parallel execution. This model uses separately optimized sequential and parallel versions of code. Sequential e ciency is obtained by dynamically coalescing threads via stack-based execution and parallel e ciency through latency hiding and cheap synchronization using heap-allocated activation frames. Novel aspects of the stack mechanism include handling return values for futures and executing forwarded messages (the responsibility to reply is passed along, like call/cc in Scheme) on the stack. In addition, the hybrid execution model is expressed entirely in C, and therefore is easily portable to many systems. Experiments with function-call intensive programs show that this model achieves sequential e ciency comparable to C programs. Experiments with regular and irregular application kernels on the CM-