Blind Sparse Deconvolution of Regularly Spaced Ultrasonic Echoes for Thickness Measurement

We present a method for estimating the thickness of thin materials from ultrasonic data, in the context of coating measurement or thickness estimation of tubes and pipes. When sending an ultrasonic pulse in normal incidence in a homogeneous material, a set of regularly spaced echoes is received. Thickness is then obtained from the estimation of the time delay between echoes. If thin structures are inspected (or if a low frequency transducer is used), then echoes may overlap. Then, visual interpretation is made difficult and standard automatic methods may fail. We propose a blind sparse deconvolution approach to this problem, where data are modeled as the convolution of a spike train with an unknown impulse response that corresponds to the shape of the echoes. The specific structure of the spike train (regularly spaced spikes with geometrically decreasing amplitudes) is taken into account and the echoes are modeled with a frequency modulated Gaussian signal. Joint estimation of all parameters is performed by non-linear least-squares minimization, with specific constraints, initialization and optimization procedure that aim to avoid local minima. Results are presented on simulated data and in application to thickness estimation of aluminum plates with 2mm and 1mm thickness

Blind Sparse Deconvolution of Regularly Spaced Ultrasonic Echoes for Thickness Measurement

We present a method for estimating the thickness of thin materials from ultrasonic data, in the context of coating measurement or thickness estimation of tubes and pipes. When sending an ultrasonic pulse in normal incidence in a homogeneous material, a set of regularly spaced echoes is received. Thickness is then obtained from the estimation of the time delay between echoes. If thin structures are inspected (or if a low frequency transducer is used), then echoes may overlap. Then, visual interpretation is made difficult and standard automatic methods may fail. We propose a blind sparse deconvolution approach to this problem, where data are modeled as the convolution of a spike train with an unknown impulse response that corresponds to the shape of the echoes. The specific structure of the spike train (regularly spaced spikes with geometrically decreasing amplitudes) is taken into account and the echoes are modeled with a frequency modulated Gaussian signal. Joint estimation of all parameters is performed by non-linear least-squares minimization, with specific constraints, initialization and optimization procedure that aim to avoid local minima. Results are presented on simulated data and in application to thickness estimation of aluminum plates with 2mm and 1mm thickness.</p

OsBSK3 Positively Regulates Grain Length and Weight by Inhibiting the Phosphatase Activity of OsPPKL1

Brassinosteroids (BRs) are a crucial class of plant hormones that regulate many important agronomic traits in rice (Oryza sativa L.); thus, the BR signaling pathway is a very important tool for breeders to improve the grain yield and quantity of rice. Contrary to the well-established BR signaling pathway in Arabidopsis, there are significant gaps in the rice BR signaling pathway, especially the regulation mechanism from OsBSK3 to OsPPKLs and OsGSKs. In this study, we report how OsBSK3 knockout mutants confer shorter and lighter grains and exhibit a typical BR-insensitive phenotype, suggesting OsBSK3 plays a positive role in BR signaling without genetic redundancy with homologs. Furthermore, OsBSK3 could physically interact with OsPPKL1 and OsGSK3, the downstream components in BR signaling, as a scaffold protein, and inhibit the phosphatase activity of OsPPKL1 on the dephosphorylation of OsGSK3. In addition, the genetic evidence showed OsBSK3 acts upstream of OsPPKL1 in regulating grain length and weight. Our results clarify the role of OsBSK3 and provide new insights into BR-signaling mechanisms, leading to potential new targets for the genetic improvement of rice

Piezoelectric Effect of Antibacterial Biomimetic Hydrogel Promotes Osteochondral Defect Repair

The lack of vascular tissue and the low metabolism and biological activity of mature chondrocytes lead to the low regeneration ability of articular cartilage. People try to solve this problem through various methods, but the effect is not very ideal. Inspired by the piezoelectric effect of collagen in cartilage tissue, this work focused on the design of a biomimetic hydrogel by introducing piezoelectric materials and silver nanowires into hydrogel to endow them with piezoelectric and antibacterial properties to promote tissue regeneration. Additionally, the mechanical and swelling properties of the material were adjusted to match natural articular cartilage. Based on bionic principles, a double-layer piezoelectric hydrogel was prepared and applied for the repair of osteochondral defects. An enhanced repair effect of osteochondral defects has been seen, which has demonstrated potential values for future application in bionics principle- and piezoelectric effect-based osteochondral tissue engineering. Furthermore, piezoelectric effect-induced degradation was observed. These results fully indicated the positive effect of the piezoelectric effect on promoting the regeneration of osteochondral tissue and in vivo degradation of materials