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.     

Hierarchical Community Detection Based on Partial Matrix Convergence Using Random Walks

Random walks are a standard tool for modeling the spreading process in social and biological systems.But in the face of large-scale networks,to achieve convergence,iterative calculation of the transition matrix in random walk methods consumes a lot of time.In this paper,we propose a three-stage hierarchical community detection algorithm based on Partial Matrix Approximation Convergence(PMAC) using random walks.First,this algorithm identifies the initial core nodes in a network by classical measurement and then utilizes the error function of the partial transition matrix convergence of the core nodes to determine the number of random walks steps.As such,the PMAC of the core nodes replaces the final convergence of all the nodes in the whole matrix.Finally,based on the approximation convergence transition matrix,we cluster the communities around core nodes and use a closeness index to merge two communities.By recursively repeating the process,a dendrogram of the communities is eventually constructed.We validated the performance of the PMAC by comparing its results with those of two representative methods for three real-world networks with different scales.     

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.     

等候区手术患者家属的心理影响因素及干预措施

目的:探讨等候区手术患者家属的心理影响因素及其干预措施.方法:通过临床护理实践及查阅相关文献进行总结分析.结果:影响因素及其干预措施包括详解病情及手术风险性;对手术环境及术中情况的告知;完善急诊手术患者家属心理干预;根据不同文化水平进行健康宣教;尽量以病情为主,设计最经济有效的治疗方案;提高医护人员从业技能及道德品质.结论:对等候区手术患者家属进行积极有效的心理干预,可很大程度上减轻患者家属的焦虑程度,缓和医患关系,一定程度上提升了医疗质量.     

数字量子模拟已经应用到两费米子体系了（英文）

In a recent work,a group of researchers led by Gui-Lu Long of Tsinghua University proposed a digital quantum simulation algorithm for the dynamics of interacting quantum systems in real space.They experimentally implemented the algorithm to simulate the dynamics of two interacting fermions using a nuclear magnetic resonance(NMR)setup[1].     

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.     

Early SIV and HIV infection promotes the LILRB2/MHC-I inhibitory axis in cDCs

Classical dendritic cells (cDCs) play a pivotal role in the early events that tip the immune response toward persistence or viral control. In vitro studies indicate that HIV infection induces the dysregulation of cDCs through binding of the LILRB2 inhibitory receptor to its MHC-I ligands and the strength of this interaction was proposed to drive disease progression. However, the dynamics of the LILRB2/MHC-I inhibitory axis in cDCs during early immune responses against HIV are yet unknown. Here, we show that early HIV-1 infection induces a strong and simultaneous increase of LILRB2 and MHC-I expression on the surface of blood cDCs. We further characterized the early dynamics of LILRB2 and MHC-I expression by showing that SIVmac251 infection of macaques promotes coordinated up-regulation of LILRB2 and MHC-I on cDCs and monocytes/macrophages, from blood and lymph nodes. Orientation towards the LILRB2/MHC-I inhibitory axis starts from the first days of infection and is transiently induced in the entire cDC population in acute phase. Analysis of the factors involved indicates that HIV-1 replication, TLR7/8 triggering, and treatment by IL-10 or type I IFNs increase LILRB2 expression. Finally, enhancement of the LILRB2/MHC-I inhibitory axis is specific to HIV-1 and SIVmac251 infections, as expression of LILRB2 on cDCs decreased in naturally controlled chikungunya virus infection of macaques. Altogether, our data reveal a unique up-regulation of LILRB2 and its MHC-I ligands on cDCs in the early phase of SIV/HIV infection, which may account for immune dysregulation at a critical stage of the anti-viral response.     

基于小波分析对地面电场信号的去噪及闪电信息提取

基于小波分析方法,通过对7种小波函数在误差控制和阈值方法选取上的对比,参考信噪比及均方误差等计算结果,选取了较为合理的Rigrsure阈值分析方法和sym5小波函数作为地面大气电场信号的去噪处理方法.该方法不仅能够较好地对电场信号波形平滑处理,降低电场波形中噪声信号的叠加度,还可保留闪电引起的电场的快速变化.在此基础上,利用差分计算方法实现了对闪电信号的自动识别,引入了总闪电频数误差及分时段闪电频数与人工分析结果的相关系数等2个参考量来选取差分计算方法中电场差分阈值,通过该方法可以实现闪电频数和极性等有关信息的提取.