A Novel Method for Pattern Recognition of GIS Partial Discharge via Multi-Information Ensemble Learning

Partial discharge (PD) is the main feature that effectively reflects the internal insulation defects of gas-insulated switchgear (GIS). It is of great significance to diagnose the types of insulation faults by recognizing PD to ensure the normal operation of GIS. However, the traditional diagnosis method based on single feature information analysis has a low recognition accuracy of PD, and there are great differences in the diagnosis effect of various insulation defects. To make the most of the rich insulation state information contained in PD, we propose a novel multi-information ensemble learning for PD pattern recognition. First, the ultra-high frequency and ultrasonic data of PD under four typical defects of GIS are obtained through experiment. Then the deep residual convolution neural network is used to automatically extract discriminative features. Finally, multi-information ensemble learning is used to classify PD types at the decision level, which can complement the shortcomings of the independent recognition of the two types of feature information and has higher accuracy and reliability. Experiments show that the accuracy of the proposed method can reach 97.500%, which greatly improves the diagnosis accuracy of various insulation defects.     

Deep Multilabel Multilingual Document Learning for Cross-Lingual Document Retrieval

Cross-lingual document retrieval, which aims to take a query in one language to retrieve relevant documents in another, has attracted strong research interest in the last decades. Most studies on this task start with cross-lingual comparisons at the word level and then represent documents via word embeddings, which leads to insufficient structure information. In this work, the cross-lingual comparison at the document level is achieved through the cross-lingual semantic space. Our method, MDL (deep multilabel multilingual document learning), leverages a six-layer fully connected network to project cross-lingual documents into a shared semantic space. The semantic distances can be calculated when the cross-lingual documents are transformed into embeddings in semantic space. The supervision signals are automatically extracted from the data and then used to construct the semantic space via a linear classifier. The ambiguity of manual labels could be avoided and the multilabel supervision signals can be acquired instead of a single label. The representation of the semantic space is enriched by multilabel supervision signals, which improves the discriminative ability of the embeddings. The MDL is easy to extend to other fields since it does not depend on specific data. Furthermore, MDL is more efficient than the models training all languages jointly, since each language is trained individually. Experiments on Wikipedia data showed that the proposed method outperforms the state-of-the-art cross-lingual document retrieval methods.     

Genetically engineered materials: Proteins and beyond

Information-rich molecules provide opportunities for evolution. Genetically engineered materials are superior in that their properties are coded within genetic sequences and could be fine-tuned. In this review, we elaborate the concept of genetically engineered materials(GEMs) using examples ranging from engineered protein materials to engineered living materials. Proteinbased materials are the materials of choice by nature. Recent progress in protein engineering has led to opportunities to tune...     

HIGH-FREQUENCY VIBRATIONS OF CORRUGATED CYLINDRICAL PIEZOELECTRIC SHELLS

Coupled extensional and flexural cylindrical vibrations of a corrugated cylindrical piezoelectric shell consisting of multiple pieces of circular cylindrical surfaces smoothly connected along their generatrix are studied. To validate the results for the case of relatively thick shells or equivalently high-frequency modes with short wavelengths, existing analysis is extended by considering shear deformation and rotatory inertia. An analytical solution is obtained. Based on the solution, resonant frequencies and mode shapes are calculated.     

First Organic–Inorganic Hybrid Compounds Formed by Ge-V-O Clusters and Transition Metal Complexes of Aromatic Organic Ligands

Three compounds based on Ge-V-O clusters were hydrothermally synthesized and characterized by IR, UV-Vis, XRD, ESR, elemental analysis and X-ray crystal structural analysis. Both [Cd(phen)(en)]₂[Cd₂(phen)₂V₁₂O₄₀Ge₈(OH)₈(H₂O)]∙12.5H₂O (1) and [Cd(DETA)]₂[Cd(DETA)₂]_0.5[Cd₂(phen)₂V₁₂O₄₁Ge₈(OH)₇(0.5H₂O)]∙7.5H₂O (2) (1,10-phen = 1,10-phenanthroline, en = ethylenediamine, DETA = diethylenetriamine) are the first Ge-V-O cluster compounds containing aromatic organic ligands. Compound 1 is the first dimer of Ge-V-O clusters, which is linked by a double bridge of two [Cd(phen)(en)]²⁺. Compound 2 exhibits an unprecedented 1-D chain structure formed by Ge-V-O clusters and [Cd₂(DETA)₂]⁴⁺ transition metal complexes (TMCs). [Cd(en)₃]{[Cd(η₂-en)₂]₃[Cd(η₂-en)(η₂-μ₂-en)(η₂-en)Cd][Ge₆V₁₅O₄₈(H₂O)]}∙5.5H₂O (3) is a novel 3-D structure which is constructed from [Ge₆V₁₅O₄₈(H₂O)]¹²⁻ and four different types of TMCs. We also synthesized [Zn₂(enMe)₃][Zn(enMe)]₂[Zn(enMe)₂(H₂O)]₂[Ge₆V₁₅O₄₈(H₂O)]∙3H₂O (4) and [Cd(en)₂]₂{H₈[Cd(en)]₂Ge₈V₁₂O₄₈(H₂O)}∙6H₂O (5) (enMe = 1,2-propanediamine), which have been reported previously. In addition, the catalytic properties of these five compounds for styrene epoxidation have been assessed.     

Numerical Study on an RBF-FD Tangent Plane Based Method for Convection–Diffusion Equations on Anisotropic Evolving Surfaces

In this paper, we present a fully Lagrangian method based on the radial basis function (RBF) finite difference (FD) method for solving convection–diffusion partial differential equations (PDEs) on evolving surfaces. Surface differential operators are discretized by the tangent plane approach using Gaussian RBFs augmented with two-dimensional (2D) polynomials. The main advantage of our method is the simplicity of calculating differentiation weights. Additionally, we couple the method with anisotropic RBFs (ARBFs) to obtain more accurate numerical solutions for the anisotropic growth of surfaces. In the ARBF interpolation, the Euclidean distance is replaced with a suitable metric that matches the anisotropic surface geometry. Therefore, it will lead to a good result on the aspects of stability and accuracy of the RBF-FD method for this type of problem. The performance of this method is shown for various convection–diffusion equations on evolving surfaces, which include the anisotropic growth of surfaces and growth coupled with the solutions of PDEs.     

Palladium-catalyzed hydrosilylation of ynones to access silicon-stereogenic silylenones by stereospecific aromatic interaction-assisted Si–H activation

Hydrosilylation is one of the most important reactions in synthetic chemistry and ranks as a fundamental method to access organosilicon compounds in industrial and academic processes. However, the enantioselective construction of chiral-at-silicon compounds via catalytic asymmetric hydrosilylation remained limited and difficult. Here we report a highly enantioselective hydrosilylation of ynones, a type of carbonyl-activated alkynes, using a palladium catalyst with a chiral binaphthyl phosphoramidite ligand. The stereospecific hydrosilylation of ynones affords a series of silicon-stereogenic silylenones with up to 94% yield, 20:1 regioselectivity and 98:2 enantioselectivity. The density functional theory(DFT) calculations were conducted to elucidate the reaction mechanism and origin of high degree of stereoselectivity, in which the powerful potential of aromatic interaction in this reaction is highlighted by the multiple C–H-π interaction and aromatic cavity-oriented enantioselectivitydetermining step during desymmetric functionalization of Si–H bond.     

Analytical performance study of solar blind non-line-of-sight ultraviolet short-range communication links

Motivated by recent advances in solid-state incoherent ultraviolet sources and solar blind detectors, we study communication link performance over a range of less than 1 km with a bit error rate (BER) below 10(-3) in solar blind non-line-of-sight situation. The widely adopted yet complex single scattering channel model is significantly simplified by means of a closed-form expression for tractable analysis. Path loss is given as a function of transceiver geometry as well as atmospheric scattering and attenuation and is compared with experimental data for model validation. The BER performance of a shot-noise-limited receiver under this channel model is demonstrated.     

Investigation on the scattering effect of ceramic Nd:YAG

This paper investigates the scattering effect of domestic 0.5 at{\%} ceramic Nd:YAG. An effective method has been utilized to measure the scattering and absorption coefficients. An end-pumped continuous wave (CW) Nd:YAG ceramic laser was also demonstrated. A maximum output power of 6.7~W at 1064~nm was obtained at an 808-nm pump power of 32.9~W. Conversion efficiency and slope efficiency have been achieved. This indicates that scattering has an important effect on the optical performance of ceramic Nd:YAG.     

级联二阶非线性铌酸锂全光开关的研制

以基于准位相匹配和频与差频级联二阶非线性[X^(2)：X^(2)]基础上的全光开关的理论分析作指导,进行了周期极化铌酸锂晶体(PPLN)和退火质子交换光波导(APE)的实验制备,利用所研制的PPLN-APE器件,以自行研制的工作波长为1．54μm的被动调Q掺钴铝酸镁激光器作为控制光源,以工作波长为1．5μm的连续二极管激光器为信号光源进行了级联二阶非线性全光开关实验。当控制光峰值功率为3kw,信号光功率为1mW时,实现13％的开关效率,分析了进一步提高全光开关性能的途径。