Iterative Semantic Transformer by Greedy Distillation for Community Question Answering

The semantic matching problem consists of recognizing if the candidate text is relevant to a particular input text. Semantic similarities can be determined from human-curated knowledge, but such knowledge may not be available in every language. Instead, statistical learning techniques have been applied, but these techniques circumvent the need for manual feature engineering by using large datasets to train models to perform semantic similarity scoring between portions of text or words. The pre-trained transformer provides a further mechanism to consolidate the information throughout a sentence into single sentence-level representations, but these representations may not be optimal for the matching task. As an alternative, we propose an interactive semantic transformer based on a greedy layer-wise framework to learn a distributed similarity representation for sentence pairs. The novelty of the architecture lies in an abstract representation of the semantic similarities created by three-stage learning strategies. Model training is accomplished through a greedy layer-wise training scheme, that incorporates both supervised and unsupervised learning. The proposed model is experimentally compared to state-of-the-art approaches on three different dataset types: the library TREC, the Yahoo!, and Stack Exchange community question datasets, and results show the proposed model outperforming other approaches

Study on Radiated Noise of a Panel under Fluctuating Surface Pressure Due to an Idealized Side Mirror

As traditional automobiles develop towards new energy vehicles, the noise, vibration and harshness (NVH) performance of automobiles is facing new challenges. Without the cover of the traditional engine noise and inlet and exhaust noise, the high-speed wind noise becomes more prominent. Thus, research on the calculation method of vehicle interior noise in high-speed driving condition is needed. However, vehicle body structure is complex, and the external excitation components are complicated. In order to analyze the method of predicting the vehicle interior noise at high speed, an idealized side mirror model is taken as the research object in this paper and the radiated noise of a panel under the fluctuating surface pressure (FSP) due to the idealized side mirror is studied. The FSP of the panel is first studied by the numerical simulations of incompressible and compressible flow field. For the incompressible flow field, the Corcos turbulent boundary layer (TBL) model is established to simulate the convective component and the boundary element method (BEM) is used to extract the acoustic component. Subsequently, the Corcos model coupling BEM method, the random modal force coupling BEM method and the deterministic modal force coupling BEM method are used separately to calculate the noise of the panel under the FSP. For the compressible flow field, the convective and acoustic component in the fluctuating pressure are separated by the wavenumber-frequency spectrum (WFS) method. The radiated noise of the panel under the FSP is calculated again by using the WFS, the method of random modal force and the method of deterministic modal force, respectively. Then, the computational time of the six methods of incompressible and compressible calculation is compared. Finally, a fast and accurate method of calculating the panel radiated noise under FSP is obtained by comparing the computational accuracy with the experimental results and combining the computational time: the method of incompressible random modal force. This method can be used to quickly and accurately analyze the vehicle interior noise at high speed, and to optimize the exterior protrusions and the vehicle sound package for improving the vehicle NVH performance at high speed

Foreleg Transcriptomic Analysis of the Chemosensory Gene Families in Plagiodera versicolora (Coleoptera: Chrysomelidae)

Plagiodera versicolora (Coleoptera: Chrysomelidae) is a worldwide leaf-eating forest pest in salicaceous trees. The forelegs play important roles in the chemoreception of insects. In this study, we conducted a transcriptome analysis of adult forelegs in P. versicolora and identified a total of 53 candidate chemosensory genes encoding 4 chemosensory proteins (CSPs), 19 odorant binding proteins (OBPs), 10 odorant receptors (ORs), 10 gustatory receptors (GRs), 6 ionotropic receptors (IRs), and 4 sensory neuron membrane proteins (SNMPs). Compared with the previous antennae transcriptome data, 1 CSP, 4 OBPs, 1 OR, 3 IRs, and 4 GRs were newly identified in the forelegs. Subsequently, the tissue expression profiles of 10 P. versicolora chemosensory genes were performed by real-time quantitative PCR. The results showed that PverOBP25, PverOBP27, and PverCSP6 were highly expressed in the antennae of both sexes. PverCSP11 and PverIR9 are predominately expressed in the forelegs than in the antennae. In addition, the expression levels of PverGR15 in female antennae and forelegs were significantly higher than those in the male antennae, implying that it may be involved in some female-specific behaviors such as oviposition site seeking. This work would greatly further the understanding of the chemoreception mechanism in P. versicolora

Sodium ions storage performance of PSS-rGO composites

The functionalized graphene, with prominent capability over expansion of interlayer spacing and enhancement of sodium ion diffusivity, has gained paramount interests in fabricating anode of sodium ion batteries(SIBs). Here, a poly(sodium 4-vinylbenzenesulfonate)graphene composite(PSS-rGO) was synthesized via an in situ insertion process. The insertion structure is based on the π-π interaction between the electron of graphene and the electron of PSS, which expands the interlayer spacing of rGO and, more importantly, stabilizes the structure of the composites, restrains the stack of graphene. Beyond that, the introduced sodium sulfonate groups are capable of increasing the diffusion rate of sodium ions for fast sodium ion adsorption, ensuring superior cycling performance. The performances of the simples were characterized by scanning electron microscopy(SEM), transmission electron microscopy(TEM), X-ray diffraction(XRD), Raman spectrometer(Raman), X-ray photoelectron spectrometer(XPS), electrochemical workstation and battery detection system. The results show the PSS-rGO remains a reversible capacity of 256 mAh·g-1 at 5 A·g-1 after 6000 cycles, with an ultralow decay rate of 0.003%. This work provides a feasible avenue for exploring advanced organic-inorganic hybrid materials with high capacity, fast sodium storage and ultralong lifespan for SIBs

Fast-Charging Sodium-Ion Batteries Enabled by Molecular-Level Designed Nitrogen and Phosphorus Codoped Mesoporous Soft Carbon

Soft carbons have attracted extensive interests as competitive anodes for fast-charging sodium-ion batteries (SIBs); however, the high-rate performance is still restricted by their large ion migration barriers and sluggish reaction kinetics. Herein, we show a molecular design approach toward the fabrication of nitrogen and phosphorus codoped mesoporous soft carbon (NPSC). The key to this strategy lies in the chemical cross-linking reaction between polyphosphoric acid and p-phenylenediamine, associated with pyrolysis induced in-situ self-activation that creates mesoporous structures and rich heteroatoms within the carbon matrix. Thanks to the enlarged interlayer spacing, reduced ion diffusion length, and plentiful active sites, the obtained NPSC delivers a superb rate capacity of 215 mAh g−1 at 10 A g−1 and an ultralong cycle life of 4,700 cycles at 5 A g−1. Remarkably, the full cell shows 99% capacity retention during 100 continuous cycles, and maximum energy and power densities of 191 Wh kg−1 and 9.2 kW kg−1, respectively. We believe that such a synthetic protocol could pave a novel venue to develop soft carbons with unique properties for advanced SIBs

The C-3 Functionalization of 1<i>H</i>-Indazole through Suzuki–Miyaura Cross-Coupling Catalyzed by a Ferrocene-Based Divalent Palladium Complex Immobilized over Ionic Liquid, as Well as Theoretical Insights into the Reaction Mechanism

The C-3 functionalization of 1H-indazole could produce a lot of highly valuable pharmaceutical precursors, which could be used for the treatment of cancer and many other inflammatory diseases. This work was focused on the C-3 functionalization of 1H-indazole through Suzuki–Miyaura cross-coupling of 3-iodo-1H-indazole with organoboronic acids, catalyzed by various palladium catalysts immobilized over imidazolium ionic liquids, as well as catalyst recycling. A series of reaction parameters, including the substrate, catalyst, and ionic liquid, were fully investigated. It is significant to note that the yields of the present Suzuki–Miyaura cross-coupling were mainly determined by the catalyst and the solvent used, more than the chemical structure of the substrate. Furthermore, ferrocene-based divalent palladium complexes showed better catalytic outputs compared to simple palladium salts. Moreover, using two imidazolium ionic liquids, BMImX (BMIm+ = 1-n-butyl-3-methylimidazolium, X− = BF4−, PF6−) not only improved the yields of cross-coupled products, but also avoided the formation of Pd(0) black, as compared to the non-ionic liquid facilitated reactions, and simultaneously making catalyst recycling more effective. On average, BMImBF4 performed better than BMImPF6. Additionally, scientific calculations revealed that 1,1′-bis(diphenylphosphino)ferrocene-palladium(II)dichloride dichloromethane complex (PdCl2(dppf)) showed a lower energy barrier in the formation of intermediates than [1,1′-bis(di-tert-butylphosphino)ferrocene]dichloropalladium(II) (PdCl2(dtbpf)), leading to higher catalytic outputs. This work may contribute to the development of 1H-indazole-derived new pharmaceuticals