Enantioselective three-component Ugi reaction catalyzed by chiral phosphoric acid

A catalytic enantioselective three-component Ugi reaction was developed. SPINOL-derived phosphoric acid with bulky 2,4,6-tricyclohexylphenyl groups at the 6,6′ positions was found to be the best catalyst to afford α-amino amide derivatives in good to excellent yields(62% to 99%) and enantiocontrol(81% to 99% enantiomeric excess). This asymmetric reaction was applicable well to an array of aliphatic aldehydes. The gram-scale synthesis, modification of dapsone, and enantioselective synthesis of(R)-Lacosamide underline the general utility of this methodology. Influence of dihedral angles and substituents of the chiral phosphoric acids on the enantioselectivity was also discussed in this article.     

用于数字电视的盲均衡技术研究

对目前在接收端采用均衡技术时常用的CMA算法和子空间算法的原理和性能进行了详细的讨论和说明,并给出各自的适用场合.     

Surface Functionalization of Magnetite Nanoparticles with Multipotent Antioxidant as Potential Magnetic Nanoantioxidants and Antimicrobial Agents

Functionalized magnetite nanoparticles (Fe₃O₄) were prepared using the coprecipitation method followed by functionalization with a multipotent antioxidant (MPAO). The MPAO was synthesized and analyzed using FTIR and NMR techniques. In this study, the functionalized nanoparticles (IONP@AO) were produced and evaluated using the FTIR, XRD, Raman, HRTEM, FESEM, VSM, and EDX techniques. The average determined particle size of IONP@AO was 10 nanometers. In addition, it demonstrated superparamagnetic properties. The magnitude of saturation magnetization value attained was 45 emu g⁻¹. Virtual screenings of the MPAO’s potential bioactivities and safety profile were performed using PASS analysis and ADMET studies before the synthesis step. For the DPPH test, IONP@AO was found to have a four-fold greater ability to scavenge free radicals than unfunctional IONP. The antimicrobial properties of IONP@AO were also demonstrated against a variety of bacteria and fungi. The interaction of developed nanoantioxiants with biomolecules makes it a broad-spectrum candidate in biomedicine and nanomedicine.     

基于L1正则化的随机梁式结构静力损伤识别方法

提出了一种结合摄动法和L1正则化方法的随机梁式结构静力损伤识别方法。考虑初始模型误差和测量误差的影响,建立了关于随机损伤指数的控制方程,并将摄动法和L1正则化方法相结合,对随机损伤指数的控制方程进行求解,进而从概率的角度对结构的损伤进行识别。损伤试验结果表明,和传统的最小二乘求解法相比,本文方法能够更为准确地识别多处局部损伤的位置及大小,对实际结构损伤检测具有较好的参考价值。     

Fusion Domain-Adaptation CNN Driven by Images and Vibration Signals for Fault Diagnosis of Gearbox Cross-Working Conditions

The vibration signal of gearboxes contains abundant fault information, which can be used for condition monitoring. However, vibration signal is ineffective for some non-structural failures. In order to resolve this dilemma, infrared thermal images are introduced to combine with vibration signals via fusion domain-adaptation convolutional neural network (FDACNN), which can diagnose both structural and non-structural failures under various working conditions. First, the measured raw signals are converted into frequency and squared envelope spectrum to characterize the health states of the gearbox. Second, the sequences of the frequency and squared envelope spectrum are arranged into two-dimensional format, which are combined with infrared thermal images to form fusion data. Finally, the adversarial network is introduced to realize the state recognition of structural and non-structural faults in the unlabeled target domain. An experiment of gearbox test rigs was used for effectiveness validation by measuring both vibration and infrared thermal images. The results suggest that the proposed FDACNN method performs best in cross-domain fault diagnosis of gearboxes via multi-source heterogeneous data compared with the other four methods.     

通用法制备石墨烯/硫化铜微米花和石墨烯/硫化亚锡 微米花及在水污染处理中的应用

以L-组氨酸辅助和微波加热相结合,得到了石墨烯/硫化铜微米花和石墨烯/硫化亚锡微米花的通用制备技术.通过扫描电子显微镜(SEM)、透射电子显微镜(TEM)、X射线衍射分析(XRD)、傅里叶变换红外光谱仪(FTIR)、X光电子能谱(XPS)等手段对样品进行了形貌观察和物相分析,并阐明了获得石墨烯/硫化铜花瓣和石墨烯/硫化亚锡花瓣的形成机理.对其光催化性能的研究结果表明,在可见光照射下,石墨烯/硫化铜花瓣和石墨烯/硫化亚锡花瓣能够降解溶液中83.5;(40 min内)和90.4;(50 min内)的甲基橙,表现出优异的可见光催化效果.     

Deep Hierarchical Ensemble Model for Suicide Detection on Imbalanced Social Media Data

As a serious worldwide problem, suicide often causes huge and irreversible losses to families and society. Therefore, it is necessary to detect and help individuals with suicidal ideation in time. In recent years, the prosperous development of social media has provided new perspectives on suicide detection, but related research still faces some difficulties, such as data imbalance and expression implicitness. In this paper, we propose a Deep Hierarchical Ensemble model for Suicide Detection (DHE-SD) based on a hierarchical ensemble strategy, and construct a dataset based on Sina Weibo, which contains more than 550 thousand posts from 4521 users. To verify the effectiveness of the model, we also conduct experiments on a public Weibo dataset containing 7329 users’ posts. The proposed model achieves the best performance on both the constructed dataset and the public dataset. In addition, in order to make the model applicable to a wider population, we use the proposed sentence-level mask mechanism to delete user posts with strong suicidal ideation. Experiments show that the proposed model can still effectively identify social media users with suicidal ideation even when the performance of the baseline models decrease significantly.     

单、双核钌羰基化合物Ru（CO）n（n=5，4，3）和Ru2（CO）n（n=9，8）的理论研究

采用两种密度泛函方法对中性单核Ru（CO）n（n=5,4,3）和双核Ru2（CO）n（n=9,8）化合物进行理论计算,优化出16个稳定异构体．研究发现,和Os（CO）5类似,Ru（CO）5存在两个能量接近的最低异构体．Ru（CO）4的能量最低异构体为C2v对称性的单态构型．Ru（CO）3能量最低异构体为G对称性的单态构型．Ru2（c0）。的两个能量接近的最低异构体分别含有单个桥羰基和3个桥羰基．双核不饱和Ru2（CO）8的能量最低异构体为含有两个桥羰基的单态Q构型．通过比较M2（CO）n（M=Fe,Ru,Os;n=9,8）的能量最低构型,发现Fe和Ru倾向于形成含有多个桥配位羰基的构型,而Os则更倾向于形成不含桥配位羰基的构型．对离解能的研究表明,和失去一个羰基生成Ru2（CO）8相比,Ru2（CO）9更容易离解为Ru（CO）5和Ru（CO）4．     

壬基酚聚氧乙烯醚型Gemini季铵盐表面活性剂的合成 及其表面性质的研究

合成了系列壬基酚聚氧乙烯醚型Gemini季铵盐表面活性剂(GNPQA), 用核磁、红外和元素分析对它们的结构进行了表征, 考察了反应条件对转化率的影响, 并用表面张力法和稳态荧光探针法对GNPQA的表面性能及胶束聚集数(N)进行了研究. 结果表明, 较优的反应条件: 反应时间为12 h, 反应温度为70 ℃, 反应原料摩尔比为n(双聚壬基酚聚氧乙烯醚)∶n(三乙胺)∶n(环氧氯丙烷)＝1∶1∶1; GNPQA的临界胶束浓度(CMC)值较相应的单体壬基酚聚氧乙烯醚型季铵盐表面活性剂(NPQA)降低了1～2个数量级, 显示了较高的表面活性; 当GNPQA溶液浓度为5～9倍CMC时, N值随浓度增大而线性增大; 随着氧乙烯(EO)单元数的增长, GNPQA的CMC和N值均逐渐减小; 结合GNPQA的表面性能参数和N值的变化规律, 探讨了这类表面活性剂表面及胶束聚集体的结构形态.