锗元素测定方法综述

锗在国防工业、航空航天和通信等领域中的战略性,锗含量的测定对于保证材料质量和满足国际标准至关重要。本文综述了锗含量测定方法的多种技术,包括分光光度法、原子荧光光谱法、原子吸收光谱法、电感耦合等离子体原子发射光谱法、电感耦合等离子体质谱法以及滴定法。在每个检测方法的介绍中,详细探讨了方法的原理、前处理步骤以及应用范围,并分别总结了各个方法的优势和不足。最后,强调了锗含量测定方法的意义,特别是在满足出口监管和促进科学研究方面的作用。同时对锗元素的测定方法进行了展望,为未来的发展提供了参考方向。     

振动噪声等高图的电驱动桥噪声预测及优化*

在项目开发前期通过优化电驱动桥扭矩特性的设计,可以规避噪声大问题。根据电驱动桥台架在对应扭矩下的振动噪声特性,提出了一套稳定高效的测试流程和分析方法。首先设计了一套完整的试验流程,制定了精准的数据分析方法。然后绘制出能够全面反映电驱动桥振动噪声特性的等高图。最后利用电驱动桥台架的振动噪声等高图,准确评估电驱动桥加速工况下振动噪声风险,为主机厂和电驱动桥零部件企业提供电驱动桥扭矩特性设计前期指导。利用该方法成功识别到某电驱动桥匀速及加速工况下电机及齿轮的啸叫问题。通过优化电驱动桥扭矩特性设计,电机48阶噪声峰值降低了8.5dB(A),确认该方法准确可靠,具备推广应用价值。     

Spider Silk-Improved Quartz-Enhanced Conductance Spectroscopy for Medical Mask Humidity Sensing

Spider silk is one of the hottest biomaterials researched currently, due to its excellent mechanical properties. This work reports a novel humidity sensing platform based on a spider silk-modified quartz tuning fork (SSM-QTF). Since spider silk is a kind of natural moisture-sensitive material, it does not demand additional sensitization. Quartz-enhanced conductance spectroscopy (QECS) was combined with the SSM-QTF to access humidity sensing sensitively. The results indicate that the resonance frequency of the SSM-QTF decreased monotonously with the ambient humidity. The detection sensitivity of the proposed SSM-QTF sensor was 12.7 ppm at 1 min. The SSM-QTF sensor showed good linearity of ~0.99. Using this sensor, we successfully measured the humidity of disposable medical masks for different periods of wearing time. The results showed that even a 20 min wearing time can lead to a >70% humidity in the mask enclosed space. It is suggested that a disposable medical mask should be changed <2 h.     

Phosphorylation of ERK-Dependent NF-κB Triggers NLRP3 Inflammasome Mediated by Vimentin in EV71-Infected Glioblastoma Cells

Enterovirus 71 (EV71) is a dominant pathogenic agent that may cause severe central nervous system (CNS) diseases among infants and young children in the Asia-pacific. The inflammasome is closely implicated in EV71-induced CNS injuries through a series of signaling pathways. However, the activation pathway of NLRP3 inflammasome involved in EV71-mediated CNS injuries remains poorly defined. In the studies, EV71 infection, ERK1/2 phosphorylation, and activation of NLRP3 are abolished in glioblastoma cells with low vimentin expression by CRISPR/Cas9-mediated knockdown. PD098059, an inhibitor of p-ERK, remarkably blocks the vimentin-mediated ERK1/2 phosphorylation in EV71-infected cells. Nuclear translocation of NF-κB p65 is dependent on p-ERK in a time-dependent manner. Moreover, NLRP3 activation and caspase-1 production are limited in EV71-infected cells upon the caffeic acid phenethyl ester (CAPE) administration, an inhibitor of NF-κB, which contributes to the inflammasome regulation. In conclusion, these results suggest that EV71-mediated NLRP3 inflammasome could be activated via the VIM-ERK-NF-κB pathway, and the treatment of the dephosphorylation of ERK and NF-κB inhibitors is beneficial to host defense in EV71-infected CNS.     

Interfacial Charge Transfer Induced Electronic Property Tuning of MoS_2 by Molecular Functionalization

The modulation of electrical properties of MoS_2 has attracted extensive research interest because of its potential applications in electronic and optoelectronic devices.Herein,interfacial charge transfer induced electronic property tuning of MoS_2 are investigated by in situ ultraviolet photoelectron spectroscopy and x-ray photoelectron spectroscopy measurements.A downward band-bending of MoS_2-related electronic states along with the decreasing work function,which are induced by the electron transfer from Cs overlayers to MoS_2,is observed after the functionalization of MoS_2 with Cs,leading to n-type doping.Meanwhile,when MoS_2 is modified with 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane(F_4-TCNQ),an upward band-bending of MoS_2-related electronic states along with the increasing work function is observed at the interfaces.This is attributed to the electron depletion within MoS_2 due to the strong electron withdrawing property of F_4-TCNQ,indicating p-type doping of MoS_2.Our findings reveal that surface transfer doping is an effective approach for electronic property tuning of MoS_2 and paves the way to optimize its performance in electronic and optoelectronic devices.     

REGULARITY OF WEAK SOLUTIONS TO A CLASS OF NONLINEAR PROBLEM

We study the regularity of weak solutions to a class of second order parabolic system under only the assumption of continuous coefficients.We prove that the wea...     

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.     

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.     

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.