Effects of Strain Rate,Temperature and Grain Size on the Mechanical Properties and Microstructure Evolutions of Polycrystalline Nickel Nanowires: A Molecular Dynamics Simulation

Through molecular dynamics(MD)simulation,the dependencies of temperature,grain size and strain rate on the mechanical properties were studied.The simulation results demonstrated that the strain rate from 0.05 to 2 ns~(–1 )affected the Young’s modulus of nickel nanowires slightly,whereas the yield stress increased.The Young’s modulus decreased approximately linearly;however,the yield stress firstly increased and subsequently dropped as the temperature increased.The Young’s modulus and yield stress increased as the mean grain size increased from 2.66 to6.72 nm.Moreover,certain efforts have been made in the microstructure evolution with mechanical properties association under uniaxial tension.Certain phenomena such as the formation of twin structures,which were found in nanowires with larger grain size at higher strain rate and lower temperature,as well as the movement of grain boundaries and dislocation,were detected and discussed in detail.The results demonstrated that the plastic deformation was mainly accommodated by the motion of grain boundaries for smaller grain size.However,for larger grain size,the formations of stacking faults and twins were the main mechanisms of plastic deformation in the polycrystalline nickel nanowire.     

Fuzzy Views on Black-Litterman Portfolio Selection Model

In this paper, views of investor are described in fuzzy sets, and two fuzzy Black-Litterman models are constructed with fuzzy views and fuzzy random views respectively. In the models, expected returns and uncertainty matrix of views are redefined and the views are formulated by fuzzy approaches suitably. Then the models are tested with data from Chinese financial markets. Empirical results show that the fuzzy random views model performs the best, and both the fuzzy models are better than the traditional ones, demonstrating that the fuzzy approaches can contain more information in the views and measure the uncertainty more correctly.     

新生代农民工收入消费统计分析——基于郑州市817位新生代农民工调查数据

近年来,我国农民工群体正处在代际更替的阶段,新生代农民工有其独特的消费观念、消费结构和消费行为。同时,新生代农民工也面临生产生活方式和消费方式的变化,其收入提高与消费行为转变更是实现我国经济转型的重要推动力。基于此,本文选取郑州市作为样本地区,对新生代农民工的收入状况、消费观念和消费行为进行实地调查,运用Logist模型分析其收入状况、消费观念对其消费行为选择的影响。最后,从改善新生代农民工收入状况、人力资本提升和消费观念的引导等方面提出科学、合理的建议。     

租赁设备的状态维修决策建模与优化

随着物联网技术飞速发展,租赁设备大多安装有传感系统,可以及时地对设备关键部件和整体运行状态进行检测,进而可基于设备的健康状态为其安排更为合理的维修方案,在降低租赁商维修费用的同时,尽量少地干预客户的正常施工,并且保证租赁设备在客户施工场所的可靠运行.本文研究了基于状态检测的租赁设备的最优维修问题,研究中引入了顺序状态检测,定义了基于状态的控制限维修策略,并建立了以维修开销最小为目标的解析模型,以决策系统最优的检测间隔和预防维修阈值.除检测、维修等基本费用外,模型中还进一步考虑了租赁系统的故障罚金和故障后维修超时罚金.在模型的求解中,推导了维修干预下设备任意时刻的检测概率和状态概率分布,作为模型构建和求解的依据.数值实验结果验证并表明了面向租赁设备的基于状态的维修策略的有效性.     

Speeding Up the GVW Algorithm via a Substituting Method

Journal of Systems Science and Complexity - The GVW algorithm is an efficient signature-based algorithm for computing Gröbner bases. In this paper, the authors consider the implementation of...     

Simultaneous anti-windup synthesis for linear systems subject to actuator saturation

A synthesis method for global stability and performance of input constrained linear systems, which uses a linear outputfeedback controller and a static anti-windup compensator is investigated. Different from the traditional two-step anti-windup design procedure, the proposed method synthesizes all controller parameters simultaneously. Sufficient conditions for global stability and minimizing the induced L2 gain are formulated and solved as a linear matrix inequalities(LMIs) optimization problem, which also provides an opportunity to search for a better performance tradeoff between the linear controller and the anti-windup compensator.The well-posedness of the close-loop system is also guaranteed.Simulation results show the effectiveness of the proposed method.     

基于期刊阅读群划分的期刊服务探索——以北京青年政治学院图书馆为例

新媒体时代的到来,使图书馆传统的期刊服务面临着新的挑战。为更好地做好期刊服务,分析了期刊阅读群各自的特点,探讨了基于期刊阅读群划分的期刊服务,包括面向教学科研期刊阅读群的深层次服务、面向学生阶段性阅读群的引导型服务以及面向休闲浅阅读群的灵活性服务。     

Aristotle Said “Happiness is a State of Activity” — Predicting Mood Through Body Sensing with Smartwatches

We measure and predict states of Activation and Happiness using a body sensing application connected to smartwatches. Through the sensors of commercially available smartwatches we collect individual mood states and correlate them with body sensing data such as acceleration, heart rate, light level data, and location, through the GPS sensor built into the smartphone connected to the smartwatch. We polled users on the smartwatch for seven weeks four times per day asking for their mood state. We found that both Happiness and Activation are negatively correlated with heart beats and with the levels of light. People tend to be happier when they are moving more intensely and are feeling less activated during weekends. We also found that people with a lower Conscientiousness and Neuroticism and higher Agreeableness tend to be happy more frequently. In addition, more Activation can be predicted by lower Openness to experience and higher Agreeableness and Conscientiousness. Lastly, we find that tracking people’s geographical coordinates might play an important role in predicting Happiness and Activation. The methodology we propose is a first step towards building an automated mood tracking system, to be used for better teamwork and in combination with social network analysis studies.