A dynamic free-entry oligopoly with sluggish entry and exit adjustments

We study a dynamic free-entry oligopoly with sluggish entry and exit of firms under general demand and cost functions. We show that the number of firms in a steady-state open-loop solution for a dynamic free-entry oligopoly is smaller than that at static equilibrium and that the number of firms in a steady-state memoryless closed-loop solution is larger than that in an open-loop solution.     

Lewis Pair Polymerization of Epoxides via Zwitterionic Species as a Route to High‐Molar‐Mass Polyethers

A dual catalytic setup based on N‐heterocyclic olefins (NHOs) and magnesium bis(hexamethyldisilazide) (Mg(HMDS)₂) was used to prepare poly(propylene oxide) with a molar mass (M_n) >500 000 g mol^?1, in some cases even >10⁶ g mol^?1, as determined by GPC/light scattering. This is achieved by combining the rapid polymerization characteristics of a zwitterionic, Lewis pair type mechanism with the efficient epoxide activation by the Mg^II species. Transfer‐to‐monomer, traditionally frustrating attempts at synthesizing polyethers with a high degree of polymerization, is practically removed as a limiting factor by this approach. NMR and MALDI‐ToF MS experiments reveal key aspects of the proposed mechanism, whereby the polymerization is initiated via nucleophilic attack by the NHO on the activated monomer, generating a zwitterionic species. This strategy can also be extended to other epoxides, including functionalized monomers.     

基于利他偏好的电商供应链最优决策与契约协调

构建了由一个占主导地位的电商平台和一个处于跟随地位的制造商组成的Stackelberg主从博弈模型,研究了电商平台有无利他偏好时电商供应链的最优决策和契约协调问题,并通过数值算例验证了本文的主要结论.研究表明:电商平台的利他偏好行为能够促使自身服务水平提高、正向影响制造商的最优销售价格并削弱自身利润.但电商平台的让利行为能够提高制造商的利润水平、缓和供应链冲突并改善供应链整体绩效."销售佣金比例+服务成本共担"契约能够完美的协调电商供应链,使双方最优利润获得帕累托改进,从而保证电商平台有足够的激励执行利他偏好行为.另外,进一步分析发现电商平台的利他偏好正向影响制造商支付给电商平台的固定技术服务费、制造商占有的电商供应链利润份额和服务成本分担比例,负向影响自身的销售佣金比例.     

Selectivity Effects in Bimetallic Catalysis

An emerging area of homogeneous catalysis is the use of catalysts featuring two closely associated metal sites. This approach complements the traditional focus on single‐site catalysts and makes available new parameters with which to optimize catalytic behavior. Single‐site catalysts are optimized through changing 1) the identity of the metal, and 2) the steric and electronic properties of the ligands. Bimetallic catalysts introduce new optimization parameters such as 3) catalyst nuclearity (mononuclear vs. binuclear), and 4) bimetallic pairing (relative compatibility of two metal sites). In order to harness these new optimization parameters in developing systems, it is necessary to first understand the origin of bimetallic selectivity effects that already have been documented. This Concept article highlights bimetallic effects on the chemo‐, regio‐, and stereoselectivity of catalytic transformations, using selected case studies from the recent literature as illustrative examples.     

Control over the Self‐Assembly Modes of PtII Complexes by Alkyl Chain Variation: From Slipped to Parallel π‐Stacks

We report the self‐assembly of a new family of hydrophobic, bis(pyridyl) Pt^II complexes featuring an extended oligophenyleneethynylene‐derived π‐surface appended with six long (dodecyloxy ( 2 )) or short (methoxy ( 3 )) side groups. Complex 2 , containing dodecyloxy chains, forms fibrous assemblies with a slipped arrangement of the monomer units (d_Pt???Pt≈14 Å) in both nonpolar solvents and the solid state. Dispersion‐corrected PM6 calculations suggest that this organization is driven by cooperative π–π, C?H???Cl and π–Pt interactions, which is supported by EXAFS and 2D NMR spectroscopic analysis. In contrast, nearly parallel π‐stacks (d_Pt???Pt≈4.4 Å) stabilized by multiple π–π and C?H???Cl contacts are obtained in the crystalline state for 3 lacking long side chains, as shown by X‐ray analysis and PM6 calculations. Our results reveal not only the key role of alkyl chain length in controlling self‐assembly modes but also show the relevance of Pt‐bound chlorine ligands as new supramolecular synthons.     

MOEPGA: A novel method to detect protein complexes in yeast protein–protein interaction networks based on MultiObjective Evolutionary Programming Genetic Algorithm

The identification of protein complexes in protein–protein interaction (PPI) networks has greatly advanced our understanding of biological organisms. Existing computational methods to detect protein complexes are usually based on specific network topological properties of PPI networks. However, due to the inherent complexity of the network structures, the identification of protein complexes may not be fully addressed by using single network topological property. In this study, we propose a novel MultiObjective Evolutionary Programming Genetic Algorithm (MOEPGA) which integrates multiple network topological features to detect biologically meaningful protein complexes. Our approach first systematically analyzes the multiobjective problem in terms of identifying protein complexes from PPI networks, and then constructs the objective function of the iterative algorithm based on three common topological properties of protein complexes from the benchmark dataset, finally we describe our algorithm, which mainly consists of three steps, population initialization, subgraph mutation and subgraph selection operation. To show the utility of our method, we compared MOEPGA with several state-of-the-art algorithms on two yeast PPI datasets. The experiment results demonstrate that the proposed method can not only find more protein complexes but also achieve higher accuracy in terms of fscore. Moreover, our approach can cover a certain number of proteins in the input PPI network in terms of the normalized clustering score. Taken together, our method can serve as a powerful framework to detect protein complexes in yeast PPI networks, thereby facilitating the identification of the underlying biological functions.