Reproducibility is a cornerstone of science, as the replication of findings is the process through which they become knowledge. It is widely considered that many fields of science are undergoing a reproducibility crisis. This has led to the publications of various guidelines in order to improve research reproducibility. This didactic chapter intend...
Published in 3 Biotech
Tomato yellow leaf curl virus (TYLCV) causes tremendous losses of tomato worldwide. An elicitor Hrip1, which produced by Alternaria tenuissima, can serve as a pathogen-associated molecular patterns (PAMPs) to trigger the immune defense response in Nicotiana benthamiana. Here, we show that Hrip1 can be targeted to the extracellular space and signifi...
We derive an explicit (i.e., non-iterative) formula for the retrieval of the overlap function in an aerosol lidar with both elastic and Raman N2 and/or O2 channels used for independent measurements of aerosol backscatter and extinction coefficients. The formula requires only the measured, range-corrected elastic and the corresponding Raman signals,...
In seismic tomography, traveltime infor mation of seismic body phases is commonly used to invert the seismic velocities of the subsurface structure. At long periods or for later seismic phases, the arri v al time of seismic phases lack definiti ve onset and a direct picking of the absolute arri v al time has large uncertainty and reproducibility. A...
This correspondence investigates a reconfigurable intelligent surface (RIS)-assisted wireless communication system with security threats. The RIS is deployed to enhance the secrecy outage probability (SOP) of the data sent to a legitimate user. By deriving the distributions of the received signal-to-noise-ratios (SNRs) at the legitimate user and th...
Hyperspectral anomaly detection (AD) task is a typical binary classification problem, and utilizing background prior knowledge is a key technique to solving such problems. The two most commonly used priors for hyperspectral images are low-rank and local smooth properties. Most traditional matrixbased methods use two regularizations to model these t...
We address the problem of detecting a Gaussian rank-one signal using training samples to learn the covariance matrix of the noise present in the samples under test. Towards this end, we propose to use the latter after they have been whitened by the sample covariance matrix of the training samples. As an alternative to the generalized likelihood rat...
Early fault detection and estimation in nowadays’ complex systems are mandatory to ensure prognosis operations, good conditional maintenance, and safety. Kullback–Leibler Divergence (KLD) and Jensen–Shannon Divergence (JSD) are two measures characterized by high sensitivity for the evaluation of minor differences between probability distributions. ...
Change-points in time series data are usually defined as the time instants at which changes in their properties occur. Detecting change-points is critical in a number of applications as diverse as detecting credit card and insurance frauds, or intrusions into networks. Recently the authors introduced an online kernel-based change-point detection me...
International audience
