Chirality of molecular nanostructures on surfaces via molecular assembly and reaction: manifestation and control

The formation of chiral nanostructures via molecular assembly and reaction on solid surfaces is a ubiquitous surface process due to the symmetry-breaking at 2D surface. Studying chirality during the adsorption, assembly, and reaction of molecules on 2D solid surfaces at molecular level not only sheds deep insights into the enantioselective heterogeneous catalysis, chiral recognition, origin and evolution of chirality, and many important physical chemistry processes but also provides an important strategy to create chiral nanostructures. Here, we give a survey of recent advances in chiral expression and control in molecular assemblies and reactions on surfaces. We firstly give a brief introduction to the general concepts of chiral molecular nanostructures on surfaces. And then we focus on the induction and control of chirality expressed in molecular assemblies. The recent developments in the control strategies such as chiral co-adsorber, chiral auxiliary, chiral solvent, chiral templated surfaces, as well as the underlying mechanism to achieve the chiral induction and amplification, are reviewed. After that, we review the studies of chirality expressed in on-surface synthesis which has been proved to be a promising strategy to fabricate covalently bonded low-dimensional nanostructures and materials. In this respect, we introduce the chiral expression in the intramolecular and intermolecular coupling reactions on surfaces. In addition, we survey the methods to steer the stereoselectivity of on-surface reactions including the design of precursor structure, steric hindrance effect, substrate, kinetic parameters et al. Finally, the future outlook in this field is discussed.     

HL-2M常规偏滤器位形抽气对碳杂质分布影响的模拟分析

在小角度V型结构的HL-2M常规偏滤器位形下,采用SOLPS 5.0程序研究了抽气速率Sp对装置粒子排除控制能力及溅射产生的碳杂质分布的影响.模拟结果表明,当进入边缘区域的能量为4MW、上游密度为n sep=3.0×10 m-3时,过高的抽气速率(大于40m3?s-1)将迅速降低靶板附近中性粒子压强和等离子体密度,并引...     

Equality and Freedom as Uncertainty in Groups

In this paper, I investigate a connection between a common characterisation of freedom and how uncertainty is managed in a Bayesian hierarchical model. To do this, I consider a distributed factorization of a group’s optimization of free energy, in which each agent is attempting to align with the group and with its own model. I show how this can lead to equilibria for groups, defined by the capacity of the model being used, essentially how many different datasets it can handle. In particular, I show that there is a “sweet spot” in the capacity of a normal model in each agent’s decentralized optimization, and that this “sweet spot” corresponds to minimal free energy for the group. At the sweet spot, an agent can predict what the group will do and the group is not surprised by the agent. However, there is an asymmetry. A higher capacity model for an agent makes it harder for the individual to learn, as there are more parameters. Simultaneously, a higher capacity model for the group, implemented as a higher capacity model for each member agent, makes it easier for a group to integrate a new member. To optimize for a group of agents then requires one to make a trade-off in capacity, as each individual agent seeks to decrease capacity, but there is pressure from the group to increase capacity of all members. This pressure exists because as individual agent’s capacities are reduced, so too are their abilities to model other agents, and thereby to establish pro-social behavioural patterns. I then consider a basic two-level (dual process) Bayesian model of social reasoning and a set of three parameters of capacity that are required to implement such a model. Considering these three capacities as dependent elements in a free energy minimization for a group leads to a “sweet surface” in a three-dimensional space defining the triplet of parameters that each agent must use should they hope to minimize free energy as a group. Finally, I relate these three parameters to three notions of freedom and equality in human social organization, and postulate a correspondence between freedom and model capacity. That is, models with higher capacity, have more freedom as they can interact with more datasets.     

Effect of Interventions for Improving Lumbar Motor Control on Low Back Pain in Sedentary Office Workers: A Randomized Controlled Trials

Objective: To clarify the effect of intervention with dynamic motor control exercise (DMCE) for the lumbar region on low back pain in sedentary office workers (SOWs). Methods: The participants comprised 32 SOWs with low back pain who were randomly categorized into two groups: the DMCE group and the normal trunk exercise (NTE) group. Both groups performed each exercise for three days per week for 8 weeks. The primary endpoints were evaluated for the lumbar and hip flexion angles during trunk forward bending, effect of low back pain on activities of daily living (using the Oswestry Disability Index), and intensity of low back pain (using the Visual Analog Scale) pre- and post-intervention. The extent of changes was calculated by subtracting the pre-intervention value from the post-intervention value and was compared between the two groups using an unpaired t-test. Results: The extent of changes in the lumbar flexion and hip flexion angles at 10° of trunk forward bending were significantly greater in the DMCE group than in the NTE group, and no significant differences were noted between the two groups at other angles of trunk forward bending. The extent of changes in the Oswestry Disability Index and the Visual Analog Scale scores were significantly greater in the DMCE group than in the NTE group. Conclusion: DMCE is effective in improving motor control in the lumbar region and hip joints, thereby ameliorating low back pain in SOWs.     

混沌状态下永磁同步发电机的故障诊断——LMI法研究

本文以永磁同步风力发电机为研究对象, 在两相同步旋转坐标系下建立了永磁同步发电机的数学模型. 应用时间尺度和线性仿射变换建立了系统混沌模型, 验证了系统在某些参数和工作条件下会出现混沌运动. 随后在考虑系统不确定性的情况下设计了故障观测器, 在系统发生故障时, 通过所设计的故障观测器能对混沌状态下永磁同步发电机的故障做出准确估计. 仿真结果表明基于线性矩阵不等式方法的故障观测器能够对系统故障做出快速准确的诊断. 关键词： 永磁同步发电机 混沌 非线性不确定系统 故障诊断     

Studies on controllability of directed networks with extremal optimization

Almost all natural, social and man-made-engineered systems can be represented by a complex network to describe their dynamic behaviors. To make a real-world complex network controllable with its desired topology, the study on network controllability has been one of the most critical and attractive subjects for both network and control communities. In this paper, based on a given directed–weighted network with both state and control nodes, a novel optimization tool with extremal dynamics to generate an optimal network topology with minimum control nodes and complete controllability under Kalman’s rank condition has been developed. The experimental results on a number of popular benchmark networks show the proposed tool is effective to identify the minimum control nodes which are sufficient to guide the whole network’s dynamics and provide the evolution of network topology during the optimization process. We also find the conclusion: “the sparse networks need more control nodes than the dense, and the homogeneous networks need fewer control nodes compared to the heterogeneous” (Liu et al., 2011  [18]), is also applicable to network complete controllability. These findings help us to understand the network dynamics and make a real-world network under the desired control. Moreover, compared with the relevant research results on structural controllability with minimum driver nodes, the proposed solution methodology may also be applied to other constrained network optimization problems beyond complete controllability with minimum control nodes.     

Fluorinated Eu‐Doped SnO2 Nanostructures with Simultaneous Phase and Shape Control and Improved Photoluminescence

Fluorinated Eu‐doped SnO₂ nanostructures with tunable morphology (shuttle‐like and ring‐like) are prepared by a hydrothermal method, using NaF as the morphology controlling agent. X‐ray diffraction, field‐emission scanning electron microscopy, high‐resolution transmission electron microscopy, X‐ray photoelectron spectroscopy, and energy dispersive spectroscopy are used to characterize their phase, shape, lattice structure, composition, and element distribution. The data suggest that Eu³⁺ ions are uniformly embedded into SnO₂ nanocrystallites either through substitution of Sn⁴⁺ ions or through formation of Eu‐F bonds, allowing for high‐level Eu³⁺ doping. Photoluminescence features such as transition intensity ratios and Stark splitting indicate diverse localization of Eu³⁺ ions in the SnO₂ nanoparticles, either in the crystalline lattice or in the grain boundaries. Due to formation of Eu‐F and Sn‐F bonds, the fluorinated surface of SnO₂ nanocrystallites efficiently inhibits the hydroxyl quenching effect, which accounts for their improved photoluminescence intensity.     

基于高斯伪谱方法的混沌系统最优控制

针对混沌系统最优控制问题,提出一种基于高斯伪谱方法的数值求解新算法. 首先在勒让德-高斯点上构造Lagrange插值多项式并近似表示混沌系统最优控制中的状态变量和控制变量;接着将连续空间的最优控制问题转化为非线性规划问题;然后通过序列二次规划（SQP）算法获得最优解;最后对三个典型混沌系统的仿真实验结果表明,新方法能有效和快速地实现混沌系统的最优控制. 关键词： 混沌系统 最优控制 高斯伪谱法 非线性规划     

A low-temperature high-pressure apparatus with a temperature control system

Abstract

A low-temperature high-pressure apparatus was designed using commercial cryogenic equipment. Pressures up to 1 GPa and temperatures down to 40 K can be obtained in a volume of up to 30 cm³. The apparatus is of the piston-cylinder type with a piston diameter of 45 mm, and the pressure can be varied at all temperatures, An adaptive temperature control system keeps the temperature inside the pressure cylinder constant to within ±0.1 K.