Global well‐posedness of the 2D Euler‐Boussinesq system with stratification effects

This paper is concerned with the Cauchy problem of the two‐dimensional Euler–Boussinesq system with stratification effects. We obtain the global existence of a unique solution to this system without assumptions of small initial data in Sobolev spaces. Copyright © 2017 John Wiley & Sons, Ltd.     

Coupling of CFD Simulations and Population Balance Modeling to Predict Brownian Coagulation in an Emulsion Polymerization Reactor

In this study a framework consisting of a computational fluid dynamics simulation coupled to a population balance model for the modeling of emulsion polymerizations is proposed. The combined approach is used to understand the impact of changing length and time scales, as well as mixing conditions on the particle size distribution (PSD) of a polymer latex under different conditions. It is shown that the effect of agitation rate can have a profound impact on the distribution of ionic species in the reactor, and thus on the evolution of the PSD.

     

The Quest for Mononuclear Gold(II) and Its Potential Role in Photocatalysis and Drug Action

The chemistry of gold strongly focuses on the ubiquitous oxidation states +I and +III. The intermediate oxidation state +II is generally avoided in mononuclear gold species. In recent years, gold(II) has been increasingly suggested as a key intermediate in artificial photosynthesis systems, with gold(III) moieties acting as electron acceptors, as well as in gold‐catalyzed photoredox catalysis and radical chemistry. This Minireview provides a concise summary of confirmed and characterized mononuclear open‐shell gold(II) complexes. Recent findings on structural motifs and reactivity patterns will be discussed. Exciting developments in the fields of photosynthesis, photocatalysis, and potential roles in medicinal chemistry will be outlined.     

Metal–Support Cooperative Catalysts for Environmentally Benign Molecular Transformations

Metal–support cooperative catalysts have been developed for sustainable and environmentally benign molecular transformations. The active metal centers and supports in these catalysts could cooperatively activate substrates, resulting in high catalytic performance for liquid‐phase reactions under mild conditions. These catalysts involved hydrotalcite‐supported gold and silver nanoparticles with high catalytic activity for organic reactions such as aerobic oxidation, oxidative carbonylation, and chemoselective reduction of epoxides to alkenes and nitrostyrenes to aminostyrenes using alcohols and CO/H₂O as reducing reagents. This high catalytic performance was due to cooperative catalysis between the metal nanoparticles and basic sites of the hydrotalcite support. To increase the metal–support cooperative effect, core–shell nanostructured catalysts consisting of gold or silver nanoparticles in the core and ceria supports in the shell were designed. These core–shell nanocomposite catalysts were effective for the chemoselective hydrogenation of nitrostyrenes to aminostyrenes, unsaturated aldehydes to allyl alcohols, and alkynes to alkenes using H₂ as a clean reductant. In addition, these solid catalysts could be recovered easily from the reaction mixture by simple filtration, and were reusable with high catalytic activity.     

Effects of Shape of Crowders on Dynamics of a Polymer Chain Closure

Using 3D Langevin dynamics simulations,we investigate the effects of the shape of crowders on the dynamics of a polymer chain closure.The chain closure in spherical crowders is dominated by the increased medium viscosity so that it gets slower with the increasing volume fraction of crowders.By contrast,the dynamics of chain closure becomes very complicated with increasing volume fraction of crowders in spherocylindrical crowders.Notably,the mean closure time is found to have a dramatic decrease at a range of volume fraction of crowders 0.36-0.44.We then elucidate that an isotropic to nematic transition of spherocylindrical crowders at this range of volume fraction of crowders is responsible for the unexpected dramatic decrease in the mean closure time.     

8×4×2~n设计纯净两因子交互作用成分最大数的界

混水平部分因析设计在各类试验中有广泛应用.纯净效应准则是用于选取最优部分因析设计的重要准则之一.本文考虑含有一个八水平因子、一个四水平因子和若干二水平因子的8×4×2~n混水平设计,给出了分辨度为Ⅲ和Ⅳ的该类混水平设计包含纯净两因子交互作用成分最大数的上界和下界.下界通过构造特定设计而得到.     

应用图论分析与最优化理论来数据挖掘大规模水牛普里昂蛋白结构数据

图论、最优化理论显然在蛋白质结构的研究中大有用场. 首先, 调查/回顾了研究蛋白质结构的所有图论模型. 其后, 建立了一个图论模型: 让蛋白质的侧链来作为图的顶点, 应用图论的诸如团、 $k$-团、 社群、 枢纽、聚类等概念来建立图的边. 然后, 应用数学最优化的现代摩登数据挖掘算法/方法来分析水牛普里昂蛋白结构的大数据. 成功与令人耳目一新的数值结果将展示给朋友们.     

考虑损伤的修正梯度弹性理论

梯度弹性理论在描述材料微结构起主导作用的力学行为时具有显著优势,将其与损伤理论相结合,可在材料破坏研究中考虑微结构的影响.基于修正梯度弹性理论,将应变张量、应变梯度张量和损伤变量作为Helmholtz自由能函数的状态变量,并在自然状态附近对自由能函数作Taylor展开,进而由热力学基本定律,推导出修正梯度弹性损伤理论本构方程的一般形式.编制有限元程序,模拟土样损伤局部化带的发展演化过程.结果表明,修正梯度弹性损伤理论消除了网格依赖性;损伤局部化带不是与损伤同时发生,而是在损伤发展到一定程度后再逐渐显现出来.     

A Cross-Entropy Approach to the Estimation of Generalized Linear Multilevel Models

In this article, we use the cross-entropy method for noisy optimization for fitting generalized linear multilevel models through maximum likelihood. We propose specifications of the instrumental distributions for positive and bounded parameters that improve the computational performance. We also introduce a new stopping criterion, which has the advantage of being problem-independent. In a second step we find, by means of extensive Monte Carlo experiments, the most suitable values of the input parameters of the algorithm. Finally, we compare the method to the benchmark estimation technique based on numerical integration. The cross-entropy approach turns out to be preferable from both the statistical and the computational point of view. In the last part of the article, the method is used to model the probability of firm exits in the healthcare industry in Italy. Supplemental materials are available online.     

Maximum likelihood estimation for stochastic volatility in mean models with heavy‐tailed distributions

In this article, we introduce a likelihood‐based estimation method for the stochastic volatility in mean (SVM) model with scale mixtures of normal (SMN) distributions. Our estimation method is based on the fact that the powerful hidden Markov model (HMM) machinery can be applied in order to evaluate an arbitrarily accurate approximation of the likelihood of an SVM model with SMN distributions. Likelihood‐based estimation of the parameters of stochastic volatility models, in general, and SVM models with SMN distributions, in particular, is usually regarded as challenging as the likelihood is a high‐dimensional multiple integral. However, the HMM approximation, which is very easy to implement, makes numerical maximum of the likelihood feasible and leads to simple formulae for forecast distributions, for computing appropriately defined residuals, and for decoding, that is, estimating the volatility of the process. Copyright © 2017 John Wiley & Sons, Ltd.