Identification of potential inhibitors of coronavirus hemagglutinin-esterase using molecular docking,molecular dynamics simulation and binding free energy calculation

Molecular Diversity - The pandemic outbreak of the Corona viral infection has become a critical global health issue. Biophysical and structural evidence shows that spike protein possesses a high...     

供应链视角下的增值税改革影响研究

构建了一个制造商和一个零售商所组成的两级供应链模型,研究增值税税率下调对供应链决策和社会福利的影响.结果表明,下调制造商、零售商增值税税率都会使产品零售价降低,提高零售商和制造商的利润.下调增值税税率给制造商带来的利润增量大于给零售商带来的利润增量.制造商税率下调导致批发价降低,零售商税率下调反而提高批发价.社会福利的变化趋势与潜在需求规模有关.当潜在需求规模较高时,社会福利总是随降税幅度的增大而增大,且税率降低后的社会福利大于税率降低前;当潜在需求规模中等时,社会福利随降税幅度的增大而减小,但税率降低后的社会福利仍大于税率降低前;当潜在需求规模较小时,社会福利随降税幅度的增大而减小,增值税税率下调损害了社会福利.     

A smooth homotopy method for incomplete markets

Mathematical Programming - In the general equilibrium with incomplete asset markets (GEI) model, the excess demand functions are typically not continuous at the prices for which the assets have...     

概率语言多属性群决策方法及其在新型智慧城市市民获得感评价中的应用

针对公众参与的语言信息多属性群决策问题，研究了考虑参与者满意度的概率语言多属性群决策方法。首先，根据参与者的语言评价信息确定并规范化概率语言决策矩阵。然后，对大群体进行共识分析，由最大化参与者群体的满意度构建线性规划模型，确定参与者群组的权重；构造正、负理想方案的评价向量，构建多目标规划模型，用拉格朗日乘子法求解属性权重；定义各方案的加权贴近度，并以此对方案进行排序和优选。最后，通过新型智慧城市市民获得感评价案例验证了模型的可行性和有效性。     

The Synergistic Photocatalytic Effect of H3PW12O40 and Pt Nanoparticles Comodified UiO-66-NH2 on the Reduction of Aqueous Cr(VI) under Original pH

Kinetics and Catalysis - A ternary synergistic photocatalyst H3PW12O40/Pt/UiO-66-NH2 was successfully fabricated for the first time through a simple solvothermal synthetic strategy. We found that...     

A branch-and-bound method for the minimum k−enclosing ball problem

The minimum k-enclosing ball problem seeks the ball with smallest radius that contains at least k of m given points. This problem is NP-hard. We present a branch-and-bound algorithm on the tree of the subsets of k points to solve this problem. Our method is able to solve the problem exactly in a short amount of time for small and medium sized datasets.     

Novel synthesis of sensor for selective detection of Fe+3 ions under various solvents

Naked-eye colored chemo dosimeter based on vanilline based conjugated sensor was synthesized and characterized. The main point of this paper is that the solvent also affects on selectivity of metals. Vanilline based conjugate sensor exhibited high selectivity and sensitivity for detection of Ferric ions (Fe⁺³) in all (both polar and nonpolar) solvents according to absorbance which can be observed by naked eye. The selectivity was more prominent in nonpolar or less polar solvent due to solubility factor of ions and sensor but not for polar. The detection of limit of the synthesized probes was shown up to 0.84 ppm. The dielectric constant of solvents affected on the complex formation of ligand with transition metal ions. A filter paper strip system was used for rapid monitoring of detection by color variation.     

Problem-driven scenario generation: an analytical approach for stochastic programs with tail risk measure

Mathematical Programming - Scenario generation is the construction of a discrete random vector to represent parameters of uncertain values in a stochastic program. Most approaches to scenario...     

Maximum cross-correlated kurtosis-based unsaturated stochastic resonance and its application to bearing fault diagnosis

Considering the random impulses of mechanical noise and the limitations involved while identifying mechanical fault impulse signals via traditional measurement indices of signal-to-noise ratio, which require the characteristic frequency to be known in advance, this study proposes an adaptive unsaturated stochastic resonance method employing maximum cross-correlated kurtosis as the signal detection index. The proposed method combines the features of a cross-correlated coefficient to indicate periodic fault transients and those of spectrum kurtosis to locate these transients in the frequency domain. Actual vibration signals collected from motor and gear bearings subjected to heavy noise are used to demonstrate the effectiveness of the proposed method. Through a coarse tree-based machine learning method, the proposed method is verified to be more suitable for explaining the periodic impulse components of bearing signals, as compared to the ensemble empirical mode decomposition denoising method and unsaturated stochastic resonance using the kurtosis-intercorrelation index.