Preparation of biaxially textured Ce1-x(Y0.2Zr0.8)xOδ buffer layers on RABiTS NiW tapes by chemical solution deposition

Highly (100)-oriented Ce_1-x(Y_0.2Zr_0.8)_xO_δ (CYZO) films were prepared on biaxially textured NiW substrates by a chemical solution deposition approach using metal inorganic salts as starting materials. It has been found that both the preferential orientation and surface roughness of CYZO films decrease gradually with increasing of the doping percentage of Y³⁺ and Zr⁴⁺ ions. The epitaxial growth relationship of (220)_CYZO//(200)_NiW and [00?l]_CYZO//[001]_NiW was demonstrated by XRD texture measurement as well as atomic resolution STEM observation. XRD, Raman and XPS spectra results indicate that Y³⁺ and Zr⁴⁺ ions were indeed introduced into CeO₂ lattice to substitute Ce⁴⁺ ions and form cubic fluorite CYZO solid solution. Moreover, CeO₂ buffer layer can be endowed a strong enough capability to prevent element diffusion through co-doping of yttrium and zirconium, provided that an optimal doping ratio of them is adopted. This will provide a new approach to fabricating strong-barrier single buffer layer for coated conductor.     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Mechanophysical Cues in Extracellular Matrix Regulation of Cell Behavior

The extracellular matrix (ECM) is a macromolecular network that can provide biochemical and structural support for cell adhesion and formation. It regulates cell behavior by influencing biochemical and physical cues. It is a dynamic structure whose components are modified, degraded, or deposited during connective tissue development, giving tissues strength and structural integrity. The physical properties of the natural ECM environment control the design of naturally or synthetically derived biomaterials to guide cell function in tissue engineering. Tissue engineering is an important field that explores physical cues of the ECM to produce new viable tissue for medical applications, such as in organ transplant and organ recovery. Understanding how the ECM exerts physical effects on cell behavior, when cells are seeded in synthetic ECM scaffolds, is of utmost importance. Herein we review recent findings in this area that report on cell behaviors in a variety of ECMs with different physical properties, i.e., topology, geometry, dimensionality, stiffness, and tension.     

A Novel Beam Search to Improve Neural Machine Translation for English-Chinese

Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, overcoming the weaknesses of conventional phrase-based translation systems. Although NMT based systems have gained their popularity in commercial translation applications, there is still plenty of room for improvement. Being the most popular search algorithm in NMT, beam search is vital to the translation result. However, traditional beam search can produce duplicate or missing translation due to its target sequence selection strategy. Aiming to alleviate this problem, this paper proposed neural machine translation improvements based on a novel beam search evaluation function. And we use reinforcement learning to train a translation evaluation system to select better candidate words for generating translations. In the experiments, we conducted extensive experiments to evaluate our methods. CASIA corpus and the 1,000,000 pairs of bilingual corpora of NiuTrans are used in our experiments. The experiment results prove that the proposed methods can effectively improve the English to Chinese translation quality.     

Properties of recombinant 4-α-glucanotransferase from Bifidobacterium longum subsp. longum JCM 1217 and its application

Food Science and Biotechnology - To determine the physiochemical properties of the 4-α-glucanotransferase from Bifidobacterium sp., the bllj_0114 gene encoding 4-α-glucanotransferase was...