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.     

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.     

Superamphiphobic,light-trapping FeSe2 particles with a micro-nano hierarchical structure obtained by an improved solvothermal methodSuperamphiphobic,light-trapping FeSe2 particles with a micro-nano hierarchical structure obtained by an improved solvothermal methodSuperamphiphobic,light-trapping FeSe2 particles with a micro-nano hierarchical structure obtained by an improved solvothermal method

Wettability and the light-trapping effect of FeSe2 particles with a micro-nano hierarchical structure have been inves- tigated. Particles are synthesized by an improved solvothermal method, wherein hexadecyl trimetbyl ammonium bromide （CTAB） is employed as a surfactant. After modifying the particles with heptadecafluorodecyltrimethoxy-silane （HTMS）, we find that the water contact angle （WCA） of the FeSe2 particles increases by 6.1~ and the water sliding angle （WSA） decreases by 2.5~ respectively, and the diffuse reflectivity decreases 29.4% compared with similar FeSe2 particles synthe- sized by the conventional method. The growth process of the particles is analyzed and a growth scenario is given. Upon altering the PH values of the water, we observe that the superhydrophobic property is maintained quite consistently across a wide PH range of 1-14. Moreover, the modified particles were also found to be superoleophobic. To the best of our knowledge, there is no systematic research on the wettability of FeSe2 particles, so our research provides a reference for other researchers.     

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.     

转变高中物理学习方式的实践与思考

介绍了研读式、研究式、研讨式、研习式四种学习方式实施的依据、条件、步骤及应该注意的问题和应达到的教学目标以及在教学过程中确保能够具体实施的做法及思考．     

光学透明频率选择表面的设计研究

以氟化镁为基底材料, 采用基底、金属网栅与频率选择表面一体化设计方法设计了一种雷达波与光学波段双带通的结构. 利用模式匹配法对设计结构的传输特性进行了仿真研究, 并将设计结果与制备样件的测试结果进行了对比分析. 结果发现: 采用一体化设计的方法设计光学透明频率选择表面, 不仅能够快速得到电场基函数而且还能够准确预估其谐振尺寸, 从而在提高计算效率的同时避免了模式互作用零点的出现. 采用一体化设计方法获得了具有稳定滤波特性的光学透明频率选择表面, 为雷达/红外双模制导头罩的电磁屏蔽技术和隐身技术提供了一种有效技术方案. 关键词： 复合制导 频率选择表面 金属网栅 一体化设计     

Gray photorefractive polymeric optical spatial solitons

We show that gray spatial optical solitons are possible in biased photorefractive polymers under steady-state conditions. We find that for a given material parameter the absolute value of a gray photorefractive polymeric soliton's phase decreases with an increase in the beam's grayness, whereas it increases with the material parameter for a given beam's grayness and that the full width half maximum (FWHM) of the gray soliton beam's intensity increases with the beam's grayness when the normalized background intensity and the material parameter are fixed and decreases with an increase in the normalized background intensity when the material parameter is fixed. On the other hand, we also show that N coupled beam evolution equations in biased photorefractive polymers can exhibit multicomponent gray solitons. These multicomponent gray solitons can be obtained provided that the N coupled beams share the same polarization, wavelength, and are incoherent with one another. The characteristics and stability properties of these multicomponent gray solitons are also discussed in detail.