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Search Results: 1 - 10 of 137216 matches for " Zhang Hai-Feng "
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Mean-field potential calculations of high-pressure equation of state for BeO

Zhang Qi-Li,Zhang Ping,Song Hai-Feng,Liu Hai-Feng,

中国物理 B , 2008,
Abstract: A systematic study of the Hugoniot equation of state, phase transition, and the other thermodynamic properties including the Hugoniot temperature, the electronic and ionic heat capacities, and the Gr\"{u}neisen parameter for shock-compressed BeO, has been carried out by calculating the total free energy. The method of calculations combines first-principles treatment for 0\,K and finite-T electronic contribution and the mean-field-potential approach for the vibrational contribution of the lattice ion to the total energy. Our calculated Hugoniot is in good agreement with the experimental data.
Spontaneous infiltration and wetting behaviors of a Zr-based alloy melt on a porous SiC substrate
Bo Zhang,Wen Li,Hong Li,Hai-feng Zhang
- , 2018, DOI: https://doi.org/10.1007/s12613-018-1630-7
Abstract: The spontaneous infiltration and wetting behaviors of a Zr-based alloy melt on porous a SiC ceramic plate were studied using the sessile drop method by continuous heating and holding for 1800 s at different temperatures in a high-vacuum furnace. The results showed that the Zr-based alloy melt could partly infiltrate the porous SiC substrate without pressure due to the effect of capillary pressure. Wettability and infiltration rates increased with increasing temperature, and interfacial reaction products (ZrC0.7 and TiC) were detected in the Zr-based alloy/SiC ceramic system, likely because of the reaction of the active elements Zr and Ti with elemental C. Furthermore, the redundant element Si diffused into the alloy melt.
Global stability of Hopfield neural networks under dynamical thresholds with distributed delays
Fei-Yu Zhang,Hai-Feng Huo
Discrete Dynamics in Nature and Society , 2006, DOI: 10.1155/ddns/2006/27941
Abstract: We study the dynamical behavior of a class of Hopfield neural networks with distributed delays under dynamical thresholds. Some new criteria ensuring the existence, uniqueness, and global asymptotic stability of equilibrium point are derived. In the results, we do not require the activation functions to satisfy the Lipschitz condition, and also not to be bounded, differentiable, or monotone nondecreasing. Moreover, the symmetry of the connection matrix is not also necessary. Thus, our results improve some previous works in the literature. These conditions have great importance in designs and applications of the global asymptotic stability for Hopfield neural networks involving distributed delays under dynamical thresholds.
Functional imaging and endoscopy
Jian-Guo Zhang,Hai-Feng Liu
World Journal of Gastroenterology , 2011, DOI: 10.3748/wjg.v17.i38.4277
Abstract: The emergence of endoscopy for the diagnosis of gastrointestinal diseases and the treatment of gastrointestinal diseases has brought great changes. The mere observation of anatomy with the imaging mode using modern endoscopy has played a significant role in this regard. However, increasing numbers of endoscopies have exposed additional deficiencies and defects such as anatomically similar diseases. Endoscopy can be used to examine lesions that are difficult to identify and diagnose. Early disease detection requires that substantive changes in biological function should be observed, but in the absence of marked morphological changes, endoscopic detection and diagnosis are difficult. Disease detection requires not only anatomic but also functional imaging to achieve a comprehensive interpretation and understanding. Therefore, we must ask if endoscopic examination can be integrated with both anatomic imaging and functional imaging. In recent years, as molecular biology and medical imaging technology have further developed, more functional imaging methods have emerged. This paper is a review of the literature related to endoscopic optical imaging methods in the hopes of initiating integration of functional imaging and anatomical imaging to yield a new and more effective type of endoscopy.
Efficient community-based control strategies in adaptive networks
Hui Yang,Ming Tang,Hai-Feng Zhang
Physics , 2012, DOI: 10.1088/1367-2630/14/12/123017
Abstract: Most researches on adaptive networks mainly concentrate on the properties of steady state, but neglect transient dynamics. In this study, we pay attention to the emergence of community structures in transient process and the effects of community-based control strategies on epidemic spreading. First, by normalizing modularity $Q$, we investigate the evolution of community structures during the transient process, and find that very strong community structures are induced by rewiring mechanism in the early stage of epidemic spreading, which remarkably delays the outbreaks of epidemic. Then we study the effects of control strategies started from different stages on the prevalence. Both immunization and quarantine strategies indicate that it is not "the earlier, the better" for the implementing of control measures. And the optimal control effect is obtained if control measures can be efficiently implemented in the period of strong community structure. For immunization strategy, immunizing the S nodes on SI links and immunizing S nodes randomly have similar control effects. Yet for quarantine strategy, quarantining the I nodes on SI links can yield far better effects than quarantining I nodes randomly. More significantly, community-based quarantine strategy plays more efficient performance than community-based immunization strategy. This study may shed new lights on the forecast and the prevention of epidemic among human population.
Effects of awareness diffusion and self-initiated awareness behavior on epidemic spreading - an approach based on multiplex networks
Jia-Qian Kan,Hai-Feng Zhang
Computer Science , 2015,
Abstract: In this paper, we study the interplay between the epidemic spreading and the diffusion of awareness in multiplex networks. In the model, an infectious disease can spread in one network representing the paths of epidemic spreading (contact network), leading to the diffusion of awareness in the other network (information network), and then the diffusion of awareness will cause individuals to take social distances, which in turn affects the epidemic spreading. As for the diffusion of awareness, we assume that, on the one hand, individuals can be informed by other aware neighbors in information network, on the other hand, the susceptible individuals can be self-awareness induced by the infected neighbors in the contact networks (local information) or mass media (global information). Through Markov chain approach and numerical computations, we find that the density of infected individuals and the epidemic threshold can be affected by the structures of the two networks and the effective transmission rate of the awareness. However, we prove that though the introduction of the self-awareness can lower the density of infection, which cannot increase the epidemic threshold no matter of the local information or global information. Our finding is remarkably different to many previous results--local information based behavioral response can alter the epidemic threshold.
Identifying influential spreaders in complex networks based on gravity formula
Ling-Ling Ma,Chuang Ma,Hai-Feng Zhang
Computer Science , 2015,
Abstract: How to identify the influential spreaders in social networks is crucial for accelerating/hindering information diffusion, increasing product exposure, controlling diseases and rumors, and so on. In this paper, by viewing the k-shell value of each node as its mass and the shortest path distance between any two nodes as their distance, then inspired by the idea of the gravity formula, we propose a gravity centrality index to identify the influential spreaders in complex networks. The comparison between the gravity centrality index with some well-known centralities, such as degree centrality, betweenness centrality, closeness centrality, and k-shell centrality, and so forth, indicates that our method can effectively identify the influential spreaders in real networks as well as artificial networks. We also use the classical Susceptible-Infected-Recovered (SIR) epidemic model to verify the good performance of our method.
Numerical Simulation of Wave Propagation and Phase Transition of Tin under Shock-Wave Loading

SONG Hai-Feng,LIU Hai-Feng,ZHANG Guang-Cai,ZHAO Yan-Hong,

中国物理快报 , 2009,
Diversity surveys of soil bacterial community by cultivation-based methods and molecular fingerprinting techniques
LUO Hai-feng,QI Hong-yan,ZHANG Hong-xun,
LUO Hai-feng
,QI Hong-yan,ZHANG Hong-xun

环境科学学报(英文版) , 2004,
Abstract: By combining the cultivation methods with molecular fingerprinting techniques, the diversity surveys of soil bacterial community in 13 areas of China were carried out. The cultivable heterotrophic diversity was investigated by colony morphology on solid LB medium. Genetic diversity was measured as bands on denaturing gradient gel electrophoresis(DGGE) by the extraction and purification of the total soil DNA, and amplification of bacterial 16S rDNA fragments by polymerase chain reaction(PCR). The Shannon-Wiener indices of diversity(H), richness(S) and evenness(E H) were employed to estimate the diversity of soil bacterial community. The results showed that there was an obvious diversification existed in soil from the different areas. However, the genetic diversity estimated by PCR-DGGE can provide more comprehensive information on bacterial community than the cultivation-based methods. Therefore, it is suggested to combine the traditional methods with genetic fingerprinting techniques to survey and estimate soil bacterial diversity.
An Alternative Covering Design Algorithm of Multi-layer Neural Networks

ZHANG Ling,ZHANG Bo,YIN Hai-feng,

软件学报 , 1999,
Abstract: 文章根据多层前向权、阈值神经网络的设计原则,将设计过程分成两步进行:先用尽可能少的领域将样本中的各类分隔开来,然后再用作者提出的交叉覆盖算法进行网络设计.文章给出两个很有代表性的模拟例子,一个是平面上两根螺线的分离问题,另一个是“无穷样本学习”的例子.模拟结果证明了此方法的有效性.
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