一类压缩型映射的不动点定理

在完备的度量空间中,讨论了一类新型的非线性压缩映射ρ(Tx,Ty)≤a(ρ(x,y))ρ(x,Tx)+b(ρ(x,y))ρ(y,Ty)+c(ρ(x,y))ρ(x,y)通过构造迭代序列,指出该映射的不动点的存在性和唯一性,并给出相应的误差估计式,拓展和改进了有关文献的范围.     

Mechanical property and deformation mechanism of gold nanowire with non-uniform distribution of twinned boundaries:A molecular dynamics simulation study

The mechanical property and deformation mechanism of twinned gold nanowire with non-uniform distribution of twinned boundaries(TBs) are studied by the molecular dynamics(MD) method. It is found that the twin boundary spacing(TBS) has a great effect on the strength and plasticity of the nanowires with uniform distribution of TBs. And the strength enhances with the decrease of TBS, while its plasticity declines. For the nanowires with non-uniform distribution of TBs, the differences in distribution among different TBSs have little effect on the Young's modulus or strength, and the compromise in strength appears. But the differences have a remarkable effect on the plasticity of twinned gold nanowire. The twinned gold nanowire with higher local symmetry ratio has better plasticity. The initial dislocations always form in the largest TBS and the fracture always appears at or near the twin boundaries adjacent to the smallest TBS. Some simulation results are consistent with the experimental results.     

Effect of biaxial strain and hydrostatic pressure on the magnetic properties of bilayer CrI3

Two-dimensional van der Waals magnetic materials are intriguing for applications in the future spintronics devices, so it is crucial to explore strategy to control the magnetic properties. Here, we carried out first-principles calculations and Monte Carlo simulations to investigate the effect of biaxial strain and hydrostatic pressure on the magnetic properties of the bilayer CrI₃. We found that the magnetic anisotropy, intralayer and interlayer exchange interactions, and Curie temperature can be tuned by biaxial strain and hydrostatic pressure. Large compressive biaxial strain may induce a ferromagneticto-antiferromagnetic transition of both CrI₃ layers. The hydrostatic pressure could enhance the intralayer exchange interaction significantly and hence largely boost the Curie temperature. The effect of the biaxial strain and hydrostatic pressure revealed in the bilayer CrI₃ may be generalized to other two-dimensional magnetic materials.     

Synthesis,characterization and α‐amylase and α‐glucosidase inhibition studies of novel vanadyl chalcone complexes

A series of chalcone ligands and their corresponding vanadyl complexes of composition [VO (L^I–IV)₂(H₂O)₂]SO₄ (where L^I = 1,3‐Diphenylprop‐2‐en‐1‐one, L^II = 3‐(2‐Hydroxy‐phenyl)‐1‐phenyl‐propenone, L^III = 3‐(3‐Nitro‐phenyl)‐1‐phenyl‐propenone, L^IV = 3‐(4‐Methoxy‐phenyl)‐1‐phenyl‐propenone) have been synthesized and characterized using various spectroscopic (Fourier‐transform infrared, electrospray ionization mass, nuclear magnetic resonance, electron paramagnetic resonance, thermogravimetric analysis, vibrating sample magnetometer) and physico‐analytic techniques. Antidiabetic activities of synthesized complexes along with chalcones were evaluated by performing in vitro and in silico α‐amylase and α‐glucosidase inhibition studies. The obtained results displayed moderate to significant inhibition activity against both the enzymes by vanadyl chalcone complexes. The most potent complexes were further investigated for the enzyme kinetic studies and displayed the mixed inhibition for both the enzymes. Further, antioxidant activity of vanadyl chalcone complexes was evaluated for their efficiency to release oxidative stress using 2,2‐diphenyl‐1‐picryl‐hydrazyl‐hydrate assay, and two complexes (Complexes 2 and 4 ) have demonstrated remarkable antioxidant activity. All the complexes were found to possess promising antidiabetic and antioxidant potential.     

Modifying the physicochemical properties,solubility and foaming capacity of milk proteins by ultrasound-assisted alkaline pH-shifting treatment

This study investigated the effects of different treatment of alkaline pH-shifting on milk protein concentrate (MPC), micellar casein concentrate (MCC) and whey protein isolate (WPI) assisted by the same ultrasound conditions, including changes in the physicochemical properties, solubility and foaming capacity. The solubility of milk proteins had a significant increase with gradual enhancement of ultrasound-assisted alkaline pH-shifting (p < 0.05), especially for MCC up to 99.50 %. Also, treatment made a significant decline in the particle size of MPC and MCC, as well as the turbidity of the proteins (p < 0.05). The foaming capacity of MPC, MCC, and WPI was all improved, especially at pH 11, and at this pH, the milk protein also showed the highest surface hydrophobicity. The best foaming capacity at pH 11 was the result of the combined effect of particle size, potential, protein conformation, solubility, and surface hydrophobicity. In conclusion, ultrasound-assisted pH-shifting treatment was found to be effective in improving the physicochemical properties and solubility and foaming capacity of milk proteins, especially MCC, with promising application prospect in food industry.     

水化硅酸钙纳米压痕分子动力学模拟方法优化

针对水化硅酸钙纳米压痕模型忽视了压头与基底之间相互作用的问题，由尺寸差异引起的金刚石压头难以计算的问题，以及Wittmann模型无法得到实际接触面积的问题，提出了新的模型与计算方法．结合分子动力学方法，采用金刚石压头-Wittmann模型基底的组合方式构建无定形态水化硅酸钙纳米压痕试验模型．在建模阶段，考虑到压头模型与基底模型粒子间尺寸差异，提出了等比例替换模型，通过公式推导并就不同尺寸模拟结果验证了等比例替换模型的可行性．在计算阶段，提出了局部前处理的弛豫方法进行模拟．确定最大荷载位置处的接触面积为546 nm2，进而求出水化硅酸钙模型硬度H为0.84 GPa、折合模量Er为30.52 GPa．并通过纳米压痕试验，验证了模拟结果的准确性，证明了模型的科学性，对今后水化硅酸钙(C-S-H)纳米层面的模拟具有重要借鉴意义．     

Hyperparameter on-line learning of stochastic resonance based threshold networks

Aiming at training the feed-forward threshold neural network consisting of nondifferentiable activation functions, the approach of noise injection forms a stochastic resonance based threshold network that can be optimized by various gradient-based optimizers. The introduction of injected noise extends the noise level into the parameter space of the designed threshold network, but leads to a highly non-convex optimization landscape of the loss function. Thus, the hyperparameter on-line learning procedure with respective to network weights and noise levels becomes of challenge. It is shown that the Adam optimizer, as an adaptive variant of stochastic gradient descent, manifests its superior learning ability in training the stochastic resonance based threshold network effectively. Experimental results demonstrate the significant improvement of performance of the designed threshold network trained by the Adam optimizer for function approximation and image classification.