外企与国企培训战略对比

人才培训战略是企业人力资源战略的基础。本通过外资企业与国内企业的培训战略对比，并对国内企业中人才培训存在的不足与缺点进行了分析与探讨。     

Neural network representations of quantum many-body states

Machine learning is currently the most active interdisciplinary field having numerous applications;additionally,machine-learning techniques are used to research quantum many-body problems.In this study,we first propose neural network quantum states(NNQSs)with general input observables and explore a few related properties,such as the tensor product and local unitary operation.Second,we determine the necessary and sufficient conditions for the representability of a general graph state using normalized NNQS.Finally,to quantify the approximation degree of a given pure state,we define the best approximation degree using normalized NNQSs.Furthermore,we observe that some 7V-qubit states can be represented by a normalized NNQS,such as separable pure states,Bell states and GHZ states.     

A statistical mechanics approach to Granovetter theory

In this paper we try to bridge breakthroughs in quantitative sociology/econometrics, pioneered during the last decades by Mac Fadden, Brock–Durlauf, Granovetter and Watts–Strogatz, by introducing a minimal model able to reproduce essentially all the features of social behavior highlighted by these authors.     

Small scale behavior of financial data

A new approach is presented to describe the change in the statistics of the log return distribution of financial data as a function of the timescale. To this purpose a measure is introduced, which quantifies the distance of a considered distribution to a reference distribution. The existence of a small timescale regime is demonstrated, which exhibits different properties compared to the normal timescale regime for timescales larger than one minute. This regime seems to be universal for individual stocks. It is shown that the existence of this small timescale regime is not dependent on the special choice of the distance measure or the reference distribution. These findings have important implications for risk analysis, in particular for the probability of extreme events.     

Jamming and crystallization in athermal polymer packings

Dense packings of chains of hard spheres possess characteristic features that do not have a counterpart in corresponding packings of monomeric spheres especially near the maximally random jammed (MRJ) state. From the modelling perspective the additional requirement that spheres keep their connectivity while maximizing the occupied volume fraction imposes severe constraints on generation algorithms of dense chain configurations. The extremely sluggish dynamics imposed by the uncrossability of chains precludes the use of deterministic or stochastic dynamics to generate all but dilute polymer packings. As a viable alternative, especially tailored chain-connectivity-altering Monte Carlo (MC) algorithms have been developed that bypass this kinetic hindrance and have actually been able to produce packings of hard-sphere chains in a volume fraction range spanning from infinite dilution up to the MRJ state. Such very dense athermal polymer packings share a number of structural features with packings of monomeric hard spheres, but also display unique characteristics due to the constraints imposed by connectivity. We give an overview of the most relevant results of our recent modeling work on packings of freely-jointed chains of tangent hard spheres about the MRJ state, local structure, chain dimensions and their scaling with density, topological constraints in the form of entanglements and knots, contact network at jamming, and entropically driven crystallization.     

Identification of functionally key residues in maltose transporter with an elastic network model-based thermodynamic method

Periplasmic binding protein-dependent maltose transport system (MBP-MalFGK₂) of Escherichia coli, an important member of the Adenosine triphosphate-binding cassette transporter superfamily, is in charge of the transportation of maltoses across cellular membrane. Studies have shown that this transport processes are activated by the binding of maltose and are accompanied by large-scale cooperative movements between different domains which are mediated by a network of important residues related to signal transduction and allosteric regulation. In this paper, the functionally crucial residues and long-range allosteric pathway of the regulation of the system by substrate were identified by utilising a coarse-grained thermodynamic method proposed by our group. The residues whose perturbations markedly change the binding free energy between maltoses and MBP-MalFGK₂ were considered to be key residues. In result, the key residues in 62 clusters distributed in different subdomains were identified successfully, and the results from our calculation are highly consistent with experimental and theoretical observations. Furthermore, we explored the long-range cooperation within the transporter. These studies will help us better understand the physical mechanism of the effects of the maltose on MBP-MalFGK₂ by long-range allosteric modulation.     

Measuring persistence in a stationary time series using the complex network theory

A growing interest exists currently in the analysis of time series by the complex network theory. Here we present a simple and quick way for mapping time series to complex networks. Using a simple rule allows us to transform time series into a textual sequence then we divide it into words with fixed size. Distinct words are nodes of the network, and we have complete control on the network scale by adjusting the word size. Two nodes are linked if their associated words co-occur in sequence. We show that the network topological measures quantify the persistence and the long range correlations in fractional Brownian processes. For a particular word size we assume some relations between the topological measures and the Hurst exponent which characterised the persistence in fractional Brownian processes.     

PEMFC气体扩散层干燥过程孔隙网络模拟

本文采用三维孔隙网络模型从孔隙尺度上对质子交换膜燃料电池气体扩散层中水分蒸发的干燥过程进行了模拟,并考虑了阴极流道的影响.计算结果表明毛细力在气体扩散层的干燥过程中起主要作用,气相从阴极流道底部开始,以沿气体扩散层厚度方向侵入为先,直到到达气体扩散层底部,随后气相才向流道肩部水平延伸侵入.蒸发速率随气体扩散层中水饱和度...     

”Illusion of control” in Time-Horizon Minority and Parrondo Games

Human beings like to believe they are in control of their destiny. This ubiquitous trait seems to increase motivation and persistence, and is probably evolutionarily adaptive [J.D. Taylor, S.E. Brown, Psych. Bull. 103, 193 (1988); A. Bandura, Self-efficacy: the exercise of control (WH Freeman, New York, 1997)]. But how good really is our ability to control? How successful is our track record in these areas? There is little understanding of when and under what circumstances we may over-estimate [E. Langer, J. Pers. Soc. Psych. 7, 185 (1975)] or even lose our ability to control and optimize outcomes, especially when they are the result of aggregations of individual optimization processes. Here, we demonstrate analytically using the theory of Markov Chains and by numerical simulations in two classes of games, the Time-Horizon Minority Game [M.L. Hart, P. Jefferies, N.F. Johnson, Phys. A 311, 275 (2002)] and the Parrondo Game [J.M.R. Parrondo, G.P. Harmer, D. Abbott, Phys. Rev. Lett. 85, 5226 (2000); J.M.R. Parrondo, How to cheat a bad mathematician (ISI, Italy, 1996)], that agents who optimize their strategy based on past information may actually perform worse than non-optimizing agents. In other words, low-entropy (more informative) strategies under-perform high-entropy (or random) strategies. This provides a precise definition of the “illusion of control” in certain set-ups a priori defined to emphasize the importance of optimization. An erratum to this article is available at .     

Aberrant default mode network in subjects with amnestic mild cognitive impairment using resting-state functional MRI

Amnestic mild cognitive impairment (aMCI) is a syndrome associated with faster memory decline than normal aging and frequently represents the prodromal phase of Alzheimer's disease. When a person is not actively engaged in a goal-directed task, spontaneous functional magnetic resonance imaging (fMRI) signals can reveal functionally connected brain networks, including the so-called default mode network (DMN). To date, only a few studies have investigated DMN functions in aMCI populations. In this study, group-independent component analysis was conducted for resting-state fMRI data, with slices acquired perpendicular to the long axis of the hippocampus, from eight subjects with aMCI and eight normal control subjects. Subjects with aMCI showed an increased DMN activity in middle cingulate cortex, medial prefrontal cortex and left inferior parietal cortex compared to the normal control group. Decreased DMN activity for the aMCI group compared to the normal control group was noted in lateral prefrontal cortex, left medial temporal lobe (MTL), left medial temporal gyrus, posterior cingulate cortex/retrosplenial cortex/precuneus and right angular gyrus. Although MTL volume difference between the two groups was not statistically significant, a decreased activity in left MTL was observed for the aMCI group. Positive correlations between the DMN activity and memory scores were noted for left lateral prefrontal cortex, left medial temporal gyrus and right angular gyrus. These findings support the premise that alterations of the DMN occur in aMCI and may indicate deficiencies in functional, intrinsic brain architecture that correlate with memory function, even before significant MTL atrophy is detectable by structural MRI.