Catalyst-and additive-free selective sulfonylation/cyclization of 1,6-enynes with arylazo sulfones leading to sulfonylated γ-butyrolactams

A convenient and regioselective sulfonylation/cyclization of 1,6-enynes with arylazo sulfones has been developed to access a series of sulfonylated γ-butyrolactams.The present reaction could be efficiently conducted under catalyst-and additive-free conditions,in which C-S and C-C bonds were selectively constructed in one-pot procedure.     

An unexpected all-metal aromatic tetranuclear silver cluster in human copper chaperone Atox1

Metal clusters, such as iron–sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins. Herein we report the formation and crystal structure of a planar square tetranuclear silver cluster when silver ions were mixed with human copper chaperone Atox1. Quantum chemical studies reveal that two Ag 5s¹ electrons in the tetranuclear silver cluster fully occupy the one bonding molecular orbital, with the assumption that this Ag₄ cluster is Ag₄²⁺, leading to extensive electron delocalization over the planar square and significant stabilization. This bonding pattern of the tetranuclear silver cluster represents an aromatic all-metal structure that follows a 4n + 2 electron counting rule (n = 0). This is the first time an all-metal aromatic silver cluster was observed in a protein.

Metal clusters, such as iron–sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins.     

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.     

Sargassum fusiforme Polysaccharide-Based Hydrogel Microspheres Enhance Crystal Violet Dye Adsorption Properties

In this study, a polysaccharide-based hydrogel microsphere (SFP/SA) was prepared using S. fusiforme polysaccharide (SFP) and sodium alginate (SA). Fourier transform infrared spectroscopy (FT-IR) demonstrated that SFP was effectively loaded onto the hydrogel microsphere. Texture profile analysis (TPA) and differential scanning calorimetry (DSC) showed that, with the increase of SFP concentration, the hardness of SFP/SA decreased, while the springiness and cohesiveness of SFP/SA increased, and the thermal stability of SFP/SA improved. The equilibrium adsorption capacity of SFP/SA increased from 8.20 mg/g (without SFP) to 67.95 mg/g (SFP accounted 80%) without swelling, and from 35.05 mg/g (without SFP) to 81.98 mg/g (SFP accounted 80%) after 24 h swelling. The adsorption of crystal violet (CV) dye by SFP/SA followed pseudo-first order and pseudo-second order kinetics (both with R² > 0.99). The diffusion of intraparticle in CV dye was not the only influencing factor. Moreover, the adsorption of CV dye for SFP/SA (SFP accounted 60%) fit the Langmuir and Temkin isotherm models. SFP/SA exhibited good regenerative adsorption capacity. Its adsorption rate remained at > 97% at the 10th consecutive cycle while SFP accounted for 80%. The results showed that the addition of Sargassum fusiforme polysaccharide could increase the springiness, cohesiveness and thermal stability of the hydrogel microsphere, as well as improve the adsorption capacity of crystal violet dye.     

基于1–10GHz空地链路信号的雨强监测方法可行性研究

空地链路上的微波信号受降雨影响, 会产生功率衰减和去极化效应. 基于这些物理特性, 本文提出利用1–10 GHz空地链路信号的降雨干扰项获取雨强的方法, 并开展了相关理论研究. 根据空地链路信号与雨滴复杂的相互作用, 研究了空地链路信号频率为1–10 GHz时, 雨强 (rain rate, R) 对衰减 (attenuation, A) 和交叉极化分辨率 (cross-polarization discrimination, XPD)的影响, 分别建立了A-R和XPD-R关系模型. 通过数值模拟, 分别分析了利用上述两个关系模型估测雨强的可行性, 并系统研究了不同频率、极化方式和仰角条件下的适用性. 研究结果表明, 对于水平极化或圆极化, 且频率较高的空地链路信号, 利用A-R关系反演强降雨具有理论上的可行性; 对于不同频率和极化方式的信号, XPD-R关系模型都可以用于反演雨强, 并且对于1–50 mm·h^-1范围内的雨强, XPD较为敏感; 不同仰角条件下, A-R和XPD-R 模型都适用. 在4–10 GHz时, 本文的XPD-R模型和国际电信联盟ITU-R中XPD预测模型的结果非常接近. 所得出的结论对于下一步开展相关的验证实验, 拓展卫星系统的气象应用, 实时估测降雨强度, 实现全球降雨观测具有重要的参考价值. 关键词： 空地链路信号 雨强 衰减特性 交叉极化分辨率(XPD)     

p-型层状氧化锌的热电性质研究

采用第一性原理和玻尔兹曼输运理论,我们系统的研究了p-型二层氧化锌的热电性质.基于对单层氧化锌的晶格优化,计算得到其无虚频的声子谱,证明了它的热力学稳定性.由此构建了热力学性质稳定的二层氧化锌.采用实空间有限差分法生成了二层氧化锌的二阶和三阶力常数,然后得到了其声子散射和晶格热导率,使用两种计算方法得到了其晶格热导率在室温下分别为κ_ι~(BTE)=2.65 W/m·K和κ_ι~(RTA)=2.38 W/m·K.并且得到了p-型二层氧化锌在300 K至900 K等差温度下的热电优值为0.052～0.601,证明通过调节温度可以获得较高的热电优值.     

面向客户群的服务方案配置规则挖掘方法

产品/服务配置规则获取的主要方式是用数据挖掘技术从设计实例数据库中提取.客户化服务方案配置规则为服务功能需求和方案特征间的关联规则.考虑到常用关联规则挖掘算法Apriori具有运算复杂的缺点,提出基于PIETM(Principle of Inclusion—Exclusion and Transaction Mapping)算法的配置规则挖掘方法,考虑置信度和有趣度指标,提取强关联规则.针对配置实例数据库数据量较大时,配置规则挖掘的效率会降低且会产生大量冗余规则的问题,采用二元语义模型表达定性的服务功能需求,将同类客户群的功能需求进行合并,替换多样化的功能需求,减少规则的冗余.最后以一工程机械制造企业服务方案配置规则挖掘为例,验证了所提方法的有效性.     

Chinese regional energy efficiency change and its determinants analysis: Malmquist index and Tobit model

China becomes the largest energy consumer in 2010 but its energy productivity is well below the world average. To meet China’s fast growing energy using, energy efficiency should be especially emphasized under China’s energy policy. This paper focuses on the regional level of energy efficiency change in China. And we analyze total factor energy efficiency for 30 Chinese provinces over the period 1998–2009 using Malmquist index method and Tobit analysis. The Malmquist estimation results suggest there is a dropping change trend of energy productivity growth. Chinese energy efficiency still faces with huge regional disparity, but the energy technical efficiency reflects convergence in the nationwide and west region. As a result of Tobit regression, we find that industrial structure, energy consumption structure and institutional factor have different influences on energy efficiency.