Expression analysis of four flower-specific promoters of Brassica spp. in the heterogeneous host tobacco

The 5’-flanking region of ca. 1200 bp upstream of the translation start site (TSS) of a putative cell wall protein gene was cloned from Brassica campestris, B. chinensis, B. napus and B. oleracea, and transferred to tobacco via Agrobacterium-mediation after fused to promoter-less beta-glucuronidase(GUS) reporter gene. Histochemical GUS staining and fluorometric quantification of the transgenic tobacco showed that all four promoters conferred GUS expression in petal, anther, pollen and stigma ofthe flower, not in any vegetative organs or tissues of the plants. A series of 5’-end deletion of the promoter from B. napus disclosed that the region -104 to -17 relative to TSS was sufficient to confer flower-specific expression, and the region -181 to -161 played a key role in maintaining strong drivingpower of the promoter. Besides, several enhancer and suppressor regions were also identified in the promoter

General approach for the determination of the magneto-angular dependence of the critical current of YBCO coated conductors

The physical understanding and numerical modelling of superconducting devices which exploit the high performance of second generation high temperature superconducting tapes (2G-HTS), is commonly hindered by the lack of accurate functions which allow the consideration of the in-field dependence of the critical current. This is true regardless of the manufacturer of the superconducting tape. In this paper, we present a general approach for determining a unified function I $_{c}$(B, θ), ultimately capable of describing the magneto-angular dependence of the in-field critical current of commercial 2G-HTS tapes in the Lorentz configuration. Five widely different superconducting tapes, provided by three different manufacturers, have been tested in a liquid nitrogen bath and external magnetic fields of up to 400 mT. The critical current was recorded at 90 different orientations of the magnetic field ranging from θ = 0°, i.e., with B aligned with the crystallographic ab-planes of the YBCO layer, towards ±90°, i.e., with B perpendicular to the wider surfaces of the 2G-HTS tape. The whole set of experimental data has been analysed using a novel multi-objective model capable of predicting a sole function I $_{c}$(B, θ). This allows an accurate validation of the experimental data regardless of the fabrication differences and widths of the superconducting tapes. It is shown that, in spite of the wide set of differences between the fabrication and composition of the considered tapes, at liquid nitrogen temperature the magneto-angular dependence of the in-field critical current of YBCO-based 2G-HTS tapes, can be described by a universal function I $_{c}$($\textit{f}$(B), θ), with a power law field dependence dominated by the Kim's factor B/B $_{0}$, and an angular dependence moderated by the electron mass anisotropy ratio of the YBCO layer.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) project NMZF/064. X Zhang acknowledges a grant from the China Scholarship Council (No. 201408060080)

Finite dimensional integrable Hamiltonian systems associated with DSI equation by Bargmann constraints

The Davey-Stewartson I equation is a typical integrable equation in 2+1 dimensions. Its Lax system being essentially in 1+1 dimensional form has been found through nonlinearization from 2+1 dimensions to 1+1 dimensions. In the present paper, this essentially 1+1 dimensional Lax system is further nonlinearized into 1+0 dimensional Hamiltonian systems by taking the Bargmann constraints. It is shown that the resulting 1+0 dimensional Hamiltonian systems are completely integrable in Liouville sense by finding a full set of integrals of motion and proving their functional independence.Comment: 10 pages, in LaTeX, to be published in J. Phys. Soc. Jpn. 70 (2001

Automatic Stack Velocity Picking Using an Unsupervised Ensemble Learning Method

Seismic velocity picking algorithms that are both accurate and efficient can greatly speed up seismic data processing, with the primary approach being the use of velocity spectra. Despite the development of some supervised deep learning-based approaches to automatically pick the velocity, they often come with costly manual labeling expenses or lack interpretability. In comparison, using physical knowledge to drive unsupervised learning techniques has the potential to solve this problem in an efficient manner. We suggest an Unsupervised Ensemble Learning (UEL) approach to achieving a balance between reliance on labeled data and picking accuracy, with the aim of determining the stack velocity. UEL makes use of the data from nearby velocity spectra and other known sources to help pick efficient and reasonable velocity points, which are acquired through a clustering technique. Testing on both the synthetic and field data sets shows that UEL is more reliable and precise in auto-picking than traditional clustering-based techniques and the widely used Convolutional Neural Network (CNN) method

A New Method for Riccati Differential Equations Based on Reproducing Kernel and Quasilinearization Methods

We introduce a new method for solving Riccati differential equations, which is based on reproducing kernel method and quasilinearization technique. The quasilinearization technique is used to reduce the Riccati differential equation to a sequence of linear problems. The resulting sets of differential equations are treated by using reproducing kernel method. The solutions of Riccati differential equations obtained using many existing methods give good approximations only in the neighborhood of the initial position. However, the solutions obtained using the present method give good approximations in a larger interval, rather than a local vicinity of the initial position. Numerical results compared with other methods show that the method is simple and effective