Rethinking Graph Regularization for Graph Neural Networks

The graph Laplacian regularization term is usually used in semi-supervised representation learning to provide graph structure information for a model $f(X)$. However, with the recent popularity of graph neural networks (GNNs), directly encoding graph structure $A$ into a model, i.e., $f(A, X)$, has become the more common approach. While we show that graph Laplacian regularization brings little-to-no benefit to existing GNNs, and propose a simple but non-trivial variant of graph Laplacian regularization, called Propagation-regularization (P-reg), to boost the performance of existing GNN models. We provide formal analyses to show that P-reg not only infuses extra information (that is not captured by the traditional graph Laplacian regularization) into GNNs, but also has the capacity equivalent to an infinite-depth graph convolutional network. We demonstrate that P-reg can effectively boost the performance of existing GNN models on both node-level and graph-level tasks across many different datasets.Comment: AAAI202

Silicene Nanomesh

Similar to graphene, zero band gap limits the application of silicene in nanoelectronics despite of its high carrier mobility. By using first-principles calculations, we reveal that a band gap is opened in silicene nanomesh (SNM) when the width W of the wall between the neighboring holes is even. The size of the band gap increases with the reduced W and has a simple relation with the ratio of the removed Si atom and the total Si atom numbers of silicene. Quantum transport simulation reveals that the sub-10 nm single-gated SNM field effect transistors show excellent performance at zero temperature but such a performance is greatly degraded at room temperature

Preparation of supported skeletal Ni catalyst and its catalytic hydrogenation performance of C9 fraction from coking process

Currently, the inferior compressive strength of traditional Raney-Ni catalyst restricts its application in fixed-bed reactor. To approach this problem a series of supported skeletal Ni catalysts were prepared by mixing pseudo boehmite and Ni-Al alloy powder. In the process,the calcination temperature and atmosphere, mass ratio of pseudo boehmite to Ni-Al alloy powder and the sodium hydroxide solution concentration were investigated. The catalysts characterized by intelligent granule intensity tester(IGIT), scanning electron microscopy(SEM), X-ray photoelectron spectroscopy(XPS), X-ray diffraction (XRD),low temperature nitrogen adsorption, temperature programmed reduction of hydrogen (H2-TPR), and thermogravimetric-differential thermal analysis (TG-DTA).The results were shown that the calcination atmosphere had a considerable impact on the compressive strength of the catalyst. Compared with air atmosphere, the compressive strength of the catalyst increased from 12.62 N/mm to 23.96N/mm, obviously, in argon atmosphere, which was almost twice as much as the former.The inherent reason for this was that the argon obviously inhibited the transform of NiAl3 to Ni2Al3 in which the latter was the key factor to improve compressive strength. Additionally, coke-oven C9 hydrogenation was used to evaluate the performance of the catalyst and the results indicated that the conversion of indene, the key component of coke-oven C9, was as high as 90% in 1000h under the optimum reaction conditions:T=220oC, P(H2)=2.5MPa, H2/oil=200(v/v), LHSV=3.0h-1. Our data demonstrated that the supported skeletal Ni catalyst have a good industrial prospect in the fixed-bed reactor in future

Forest insurance market participants’ game behavior in China: an analysis based on tripartite dynamic game model

Purpose: In forest insurance market, there are three main participants including the insurance company, the forest farmer and the government. As different participant has different benefit object, there will be a complex and dynamic game relationship among all participants. The purpose of this paper is to make the game relationship among all participants in forest insurance market clear, and then to put forward some policy suggestions on the implementation of forest insurance from the view of game theory. Design/methodology/approach: Firstly, the static game model between the insurance company and the forest farmer is set up. According to the result of static game model, it’s difficult to implement forest insurance without government. Secondly, the tripartite dynamic game model among the government, the insurance company and the forest farmer is proposed, and the equilibrium solution of tripartite dynamic game model is acquired. Finally, the behavioral characteristics of all participants are analyzed according to the equilibrium solution of tripartite dynamic game model. Findings: The government’s allowance will be an important positive factor to implement forest insurance. The loss of the insurance company, which the lower insurance premium brings, can be compensated by the allowance from the government. The more the government provides allowance, the more actively the insurance company will implement forest insurance at a low insurance premium. In this situation, the forest farmer will be more likely to purchase the forest insurance, then the scope of forest insurance implementation will expend. Originality/value: There is a complex and dynamic game relationship among all participants in forest insurance market. Based on the tripartite dynamic game model, to make the game relationship between each participant clear is conducive to the implementation of forest insurance market in China.Peer Reviewe

Super-resolution hyper-spectral imaging for the direct visualization of local bandgap heterogeneity

Optical hyperspectral imaging based on absorption and scattering of photons at the visible and adjacent frequencies denotes one of the most informative and inclusive characterization methods in material research. Unfortunately, restricted by the diffraction limit of light, it is unable to resolve the nanoscale inhomogeneity in light-matter interactions, which is diagnostic of the local modulation in material structure and properties. Moreover, many nanomaterials have highly anisotropic optical properties that are outstandingly appealing yet hard to characterize through conventional optical methods. Therefore, there has been a pressing demand in the diverse fields including electronics, photonics, physics, and materials science to extend the optical hyperspectral imaging into the nanometer length scale. In this work, we report a super-resolution hyperspectral imaging technique that simultaneously measures optical absorption and scattering spectra with the illumination from a tungsten-halogen lamp. We demonstrated sub-5 nm spatial resolution in both visible and near-infrared wavelengths (415 to 980 nm) for the hyperspectral imaging of strained single-walled carbon nanotubes (SWNT) and reconstructed true-color images to reveal the longitudinal and transverse optical transition-induced light absorption and scattering in the SWNTs. This is the first time transverse optical absorption in SWNTs were clearly observed experimentally. The new technique provides rich near-field spectroscopic information that had made it possible to analyze the spatial modulation of band-structure along a single SWNT induced through strain engineering.Comment: 4 Figure

Isolation and identification of pathogens of Morchella sextelata bacterial disease

Morel mushroom (Morchella spp.) is a rare edible and medicinal fungus distributed worldwide. It is highly desired by the majority of consumers. Bacterial diseases have been commonly observed during artificial cultivation of Morchella sextelata. Bacterial pathogens spread rapidly and cause a wide range of infections, severely affecting the yield and quality of M. sextelata. In this study, two strains of bacterial pathogens, named M-B and M-5, were isolated, cultured, and purified from the tissues of the infected M. sextelata. Koch’s postulates were used to determine the pathogenicity of bacteria affecting M. sextelata, and the pathogens were identified through morphological observation, physiological and biochemical analyses, and 16S rRNA gene sequence analysis. Subsequently, the effect of temperature on the growth of pathogenic bacteria, the inhibitory effect of the bacteria on M. sextelata on plates, and the changes in mycelial morphology of M. sextelata mycelium were analyzed when M. sextelata mycelium was double-cultured with pathogenic bacteria on plates. The results revealed that M-B was Pseudomonas chlororaphis subsp. aureofaciens and M-5 was Bacillus subtilis. Strain M-B started to multiply at 10–15°C, and strain M-5 started at 15–20°C. On the plates, the pathogenic bacteria also produced significant inhibition of M. sextelata mycelium, and the observation of mycelial morphology under the scanning electron microscopy revealed that the inhibited mycelium underwent obvious drying and crumpling, and the healthy mycelium were more plump. Thus, this study clarified the pathogens, optimal growth environment, and characteristics of M. sextelata bacterial diseases, thereby providing valuable basic data for the disease prevention and control of Morchella production