变形镜部分驱动器断电失效对校正性能的影响

变形镜在长期工作的过程中,压电陶瓷驱动器因累积疲劳效应会导致其失效,从而导致校正性能的降低.从变形镜的影响函数出发,将失效驱动器的电压置零,采用有限元方法建立变形镜疲劳失效模型,重点分析畸变波前的形态分布、入射光束的类型和驱动器的排布方式等对校正能力的影响.实验结果表明,在部分驱动器失效的情况下,变形镜应当根据高斯型随...     

Learning size-adaptive molecular substructures for explainable drug–drug interaction prediction by substructure-aware graph neural network

Drug–drug interactions (DDIs) can trigger unexpected pharmacological effects on the body, and the causal mechanisms are often unknown. Graph neural networks (GNNs) have been developed to better understand DDIs. However, identifying key substructures that contribute most to the DDI prediction is a challenge for GNNs. In this study, we presented a substructure-aware graph neural network, a message passing neural network equipped with a novel substructure attention mechanism and a substructure–substructure interaction module (SSIM) for DDI prediction (SA-DDI). Specifically, the substructure attention was designed to capture size- and shape-adaptive substructures based on the chemical intuition that the sizes and shapes are often irregular for functional groups in molecules. DDIs are fundamentally caused by chemical substructure interactions. Thus, the SSIM was used to model the substructure–substructure interactions by highlighting important substructures while de-emphasizing the minor ones for DDI prediction. We evaluated our approach in two real-world datasets and compared the proposed method with the state-of-the-art DDI prediction models. The SA-DDI surpassed other approaches on the two datasets. Moreover, the visual interpretation results showed that the SA-DDI was sensitive to the structure information of drugs and was able to detect the key substructures for DDIs. These advantages demonstrated that the proposed method improved the generalization and interpretation capability of DDI prediction modeling.

SA-DDI is designed to learn size-adaptive molecular substructures for drug–drug interaction prediction and can provide explanations that are consistent with pharmacologists.     

Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic Space

Community detection and structural hole spanner (the node bridging different communities) identification, revealing the mesoscopic and microscopic structural properties of complex networks, have drawn much attention in recent years. As the determinant of mesoscopic structure, communities and structural hole spanners discover the clustering and hierarchy of networks, which has a key impact on transmission phenomena such as epidemic transmission, information diffusion, etc. However, most existing studies address the two tasks independently, which ignores the structural correlation between mesoscale and microscale and suffers from high computational costs. In this article, we propose an algorithm for simultaneously detecting communities and structural hole spanners via hyperbolic embedding (SDHE). Specifically, we first embed networks into a hyperbolic plane, in which, the angular distribution of the nodes reveals community structures of the embedded network. Then, we analyze the critical gap to detect communities and the angular region where structural hole spanners may exist. Finally, we identify structural hole spanners via two-step connectivity. Experimental results on synthetic networks and real networks demonstrate the effectiveness of our proposed algorithm compared with several state-of-the-art methods.     

光学表面非均匀中频误差的评价与修正

针对光学元件使用过程中中频误差将导致光学元件的激光破坏这一问题,提出一种中频误差突出频率提取方法。采用基于统计学的多样本数据处理,对于每一种采样方向都可以得到数个较为突出的不合格频率。利用这些频率进行确定性加工后,在特定方向,空间频率0.044 1 mm-1,0.085 8 mm-1,0.041 7 mm-1所出现的不合格次数分别降至加工前的23.9%,18.3%,29.2%,而整体中频误差减少至50.1%。结果表明,此方法降低了由光学表面中频误差方向性与局部性引起的不确定性。     

非结构子网格压力方法

纯拉氏流体力学计算失败的根源是砂漏运动和虚假涡旋,运用子网格拉氏质量与其相关的子网格密度得到子网格压力,子网格压力产生的扰动隅角力能消除这些虚假运动,以便消除困扰拉氏流体力学算法的网格畸变带来的数值计算困难.将包括子网格压力的相容流体算法推广到非结构网格,研制包括非结构子网格压力的相容流体程序,对Saltzman活塞问题进行数值模拟,从数值结果分析可知,非结构子网格压力方法能抑制虚假涡旋,消除砂漏畸变.     

Impact of the Acetaldehyde-Mediated Condensation on the Phenolic Composition and Antioxidant Activity of Vitis vinifera L. Cv. Merlot Wine

Acetaldehyde is a critical reactant on modifying the phenolic profile during red wine aging, suggesting that the acetaldehyde-mediated condensation can be responsible for the variation of antioxidant activity during the aging of this beverage. The present study employs exogenous acetaldehyde at six levels of treatment (7.86 ± 0.10–259.02 ± 4.95 mg/L) before the bottle aging of Merlot wines to encourage phenolic modification. Acetaldehyde and antioxidant activity of wine were evaluated at 0, 15, 30, 45, 60 and 75 days of storage, while monomeric and polymeric phenolics were analyzed at 0, 30 and 75 days of storage. The loss of acetaldehyde was fitted to a first-order reaction model, the rate constant (k) demonstrated that different chemical reaction happened in wines containing a different initial acetaldehyde. The disappearance of monomeric phenolics and the formation of polymeric phenolics induced by acetaldehyde could be divided into two phases, the antioxidant activity of wine did not alter significantly in the first phase, although most monomeric phenolics vanished, but the second phase would dramatically reduce the antioxidant activity of wine. Furthermore, a higher level of acetaldehyde could shorten the reaction time of the first phase. These results indicate that careful vinification handling aiming at controlling the acetaldehyde allows one to maintain prolonged biological activity during wine aging.     

Progress in superconducting qubits from the perspective of coherence and readout

Superconducting qubits are Josephson junction-based circuits that exhibit macroscopic quantum behavior and can be manipulated as artificial atoms.Benefiting from the well-developed technology of microfabrication and microwave engineering,superconducting qubits have great advantages in design flexibility,controllability,and scalability.Over the past decade,there has been rapid progress in the field,which greatly improved our understanding of qubit decoherence and circuit optimization.The single-qubit coherence time has been steadily raised to the order of 10 to 100μs,allowing for the demonstration of high-fidelity gate operations and measurement-based feedback control.Here we review recent progress in the coherence and readout of superconducting qubits.     

金属-有机骨架材料二聚铜-苯-1，3，5-三羧酸酯中烷烃扩散机理的分子模拟研究

采用分子动力学方法研究了直链烷烃C₁—C₄在二聚铜-苯-1,3,5-三羧酸酯（Cu-BTC）中的扩散机理.首先计算了4种烷烃的自扩散系数,并进一步通过质心分布图与分子轨迹图详细讨论了主、次孔道中各种类型的扩散路径.研究结果表明,不同烷烃在Cu-BTC中表现出的不同或近似的宏观扩散速率,是由微观上受到不同的扩散路径阻力并偏好不同的扩散路径所造成的.这些信息可提高人们对该类材料的认识,并为材料的实际应用以及新材料设计提供理论指导. 关键词： 分子模拟 二聚铜-苯-1 5-三羧酸酯 烷烃 扩散机理     

双轴应变条件下单层MoSe2电子结构和拉曼光谱的第一性原理计算

二硒化钼的层间相互作用强,单层结构具有更低的带隙和更好的稳定性.由于独特的光学性质和优异的电学性能受到研究人员的广泛关注.本文基于密度泛函理论的第一原理,计算和分析了在双轴拉伸压缩应变条件下单层MoSe₂能带结构,拉曼光谱和声子谱的变化规律以及性质产生的原因.在拉伸压缩应变作用下,直接带隙转变为间接带隙.当拉伸应变达到12%时,材料发生半导体-金属相变.当压缩应变达到6%时,声子谱中开始出现虚频率,表明结构开始变得不稳定.     

等厚薄板翼型的气动力特性研究

本文从吹风实验及数据分析两方面来研究等厚薄板翼型的气动力特性。在实验中对单园弧、双圆弧、抛物线三种类型的薄板翼型进行了孤立翼型的吹风试验，得出了各翼型升力系数，阻力系数随冲角变化的结果。然后利用非交错网格下的ＳＩＭＰＬＥ方法，计算了等厚薄板翼型流场，计算结果和实验结果吻合较好。