Copper-catalyzed arylation of amines using diphenyl pyrrolidine-2-phosphonate as the new ligand

[Chemical reaction: See text] We have developed a general, efficient, and inexpensive catalyst system for arylation of amines by using 10 mol % of CuI as the copper source, 20 mol % of diphenyl pyrrolidine-2-phosphonate (DPP) as the ligand, K3PO4 as the base, and DMF containing 2% water (v/v) as the solvent.     

Mesoscale organization of CuO nanoribbons: formation of "dandelions"

A two-tiered organizing scheme with multiple-length scales for construction of dandelion-like hollow CuO microspheres has been elucidated: (1) mesoscale formation of rhombic building units from smaller nanoribbons via oriented aggregation and (2) macroscopic organization of these units into the CuO microspheres. This self-assembly concept may also be applicable to other metal oxides by creating geometric constraints for constructional units.     

VIB金属蝎型配合物(Scorpionate)的研究进展

综述了VIB金属(Mo、W)多吡唑硼配合物近年来的研究进展。详细地叙述了第二代多吡唑硼配体的合成与表征。     

Strained aromatic oligoamide macrocycles as new molecular clips

Can one join both ends of a helix? A helical aromatic oligoamide was macrocyclized into a saddle-shaped bifunctional clip molecule that self-assembles into discrete circular dodecamers in the solid state and shows great potential for binding aromatic acid guests in solution. The cyclization step requires that the helix is only partly denatured in the reaction medium.     

绿色合成氧化剂高铁酸盐

高铁酸盐是绿色、无污染、高选择性和高活性的强氧化剂，其氧化性能比KMn04、O3和Cl还强，可以氧化醇类、含氮化合物、甚至烃类等有机化合物，高铁酸盐在有机物氧化合成中的应用具有很好的发展前景。本文介绍了有关高铁酸盐的制备方法、性质及有机物氧化合成方面的研究进展。     

Synthesis, Structure and Conductivity of the New Charge-transfer Salt (ET)_2(CH_2=CH-CH_2-SO_3)·H_2O

ET is one of the most famous electron-donor molecules, which forms charge-transfer complexes (abbr. CT-complexes) with various types of counterions. These complexes have received intense attention because a wide range of physical properties such as conductivity and superconductivity1, ferromagnetism2-4 and nonlinear optical properties5 was found in these materials. Although the majority of the ET-based CT-complexes were prepared by combining with inorganic counterions, CT-complexes with o…     

Stereochemical analysis of isopentenyl diphosphate isomerase type II from Staphylococcus aureus using chemically synthesized (S)- and (R)-[2-2H]isopentenyl diphosphates

[chemical reaction: see text]. To study the catalysis of isopentenyl diphosphate (IPP) isomerase type II from Staphylococcus aureus, which is a flavoprotein catalyzing the interconversion of IPP and dimethylallyl diphosphate, we have chemically synthesized (S)- and (R)-[2-2H]IPP and carried out stereochemical analysis of the reaction. Our results show that the C-2 deprotonation of IPP by this enzyme is pro-R stereospecific, suggesting a similar stereochemical course as the type I enzyme.     

KEADA: Identifying Key Classes in Software Systems Using Dynamic Analysis and Entropy-Based Metrics

Software maintenance is indispensable in the software development process. Developers need to spend a lot of time and energy to understand the software when maintaining the software, which increases the difficulty of software maintenance. It is a feasible method to understand the software through the key classes of the software. Identifying the key classes of the software can help developers understand the software more quickly. Existing techniques on key class identification mainly use static analysis techniques to extract software structure information. Such structure information may contain redundant relationships that may not exist when the software runs and ignores the actual interaction times between classes. In this paper, we propose an approach based on dynamic analysis and entropy-based metrics to identify key classes in the Java GUI software system, called KEADA (identifying KEy clAsses based on Dynamic Analysis and entropy-based metrics). First, KEADA extracts software structure information by recording the calling relationship between classes during the software running process; such structure information takes into account the actual interaction of classes. Second, KEADA represents the structure information as a weighted directed network and further calculates the importance of each node using an entropy-based metric OSE (One-order Structural Entropy). Third, KEADA ranks classes in descending order according to their OSE values and selects a small number of classes as the key class candidates. In order to verify the effectiveness of our approach, we conducted experiments on three Java GUI software systems and compared them with seven state-of-the-art approaches. We used the Friedman test to evaluate all approaches, and the results demonstrate that our approach performs best in all software systems.