Crystal structures and optical properties of the δ-O2 phase and the ε-O8 phase have been investigated by using the ab initio pseudopotential plane-wave method. It is found that the phase transition is of the first order with a discontinuous volumetric change from the antiferromagnetic δ-O2 phase to the nonmagnetic ε-O8 phase, consistent with the experimental findings. The energy band calculations show that the direct band gap changes into an indirect band gap after the phase transition. The apparent change in the optical properties can be used for identifying the phase transition from δ-O2 to ε-O8.
Degree-degree correlation and heterogeneity in degree are important topological properties characterizing scale-free networks. We consider an evolutionary prisoners＇ dilemma game on scale-free networks and investigate how degree-degree correlation influences cooperation. It is found that the cooperator frequency displays resonance-like behavior with the variation of Pearson correlation coefficient. A measure on local heterogeneity in a network is proposed and it is realized that cooperation is proportional to the local heterogeneity.
Data mining (also known as Knowledge Discovery in Databases - KDD) is defined as the nontrivial extraction of implicit, previously unknown, and potentially useful information from data. The aims and objectives of data mining are to discover knowledge of interest to user needs.Data mining is really a useful tool in many domains such as marketing, decision making, etc. However, some basic issues of data mining are ignored. What is data mining? What is the product of a data mining process? What are we doing in a data mining process? Is there any rule we should obey in a data mining process? In order to discover patterns and knowledge really interesting and actionable to the real world Zhang et al proposed a domain-driven human-machine-cooperated data mining process.Zhao and Yao proposed an interactive user-driven classification method using the granule network. In our work, we find that data mining is a kind of knowledge transforming process to transform knowledge from data format into symbol format. Thus, no new knowledge could be generated (born) in a data mining process. In a data mining process, knowledge is just transformed from data format, which is not understandable for human, into symbol format,which is understandable for human and easy to be used.It is similar to the process of translating a book from Chinese into English.In this translating process,the knowledge itself in the book should remain unchanged. What will be changed is the format of the knowledge only. That is, the knowledge in the English book should be kept the same as the knowledge in the Chinese one.Otherwise, there must be some mistakes in the translating proces, that is, we are transforming knowledge from one format into another format while not producing new knowledge in a data mining process. The knowledge is originally stored in data (data is a representation format of knowledge). Unfortunately, we can not read, understand, or use it, since we can not understand data. With this understanding of data mining, we proposed a data-driven kno
We investigate the nonlinear thermal transport properties of a single interacting quantum dot with two energy levels tunnel-coupled to two electrodes using nonequilibrium Green function method and Hartree-Fock decoupling approximation. In the case of asymmetric tunnel-couplings to two electrodes, for example, when the upper level of the quantum dot is open for transport, whereas the lower level is blocked, our calculations predict a strong asymmetry for the heat （energy） current, which shows that the quantum dot system may act as a thermal rectifier in this specific situation.
Fe29Cerl and Fe19Ni81 antidot arrays, with different dimensions, are prepared with the rf magnetron sputtering method onto the porous alumina substrate. The size and shape of antidot arrays are characterized by scanning electron microscopy. The glancing angle x-ray diffraction patterns of Fe29C071 and FelgNi81 antidot arrays indicate the bcc and fcc structures, respectively. The coercivities of both the alloys show abnormal thickness dependence, which are discussed qualitatively by considering the pinning and the thickness effect to the films.
A system of nonlinear diffusion equations with three components is studied via the potential symmetry method. It is shown that the system admits the potential symmetries for certain diffusion terms. The invariant solutions assoeiated with the potential symmetries are obtained.
The Small world model has been successfully used to explore the abnormal pattern of brain information processing in some neuropsychiatric diseases, but not engaged in the study of cognitive functions. We apply the small-world measures： the clustering coefficient and average path length, to evaluate multi-channel event-related potential activity during the generation of global and local imagery. Results show that the brain functional networks of the global and local imagery generation are both small-world ones. In addition, the local imagery generation has a larger clustering coefficient, while the global imagery generation has a shorter average path length. These results support the global precedence in the global-local imagery generation, and reflect the different processing modes in which global imagery emphasizes particularly on global integration, while local imagery on local specialization. Our results indicate that small-world measures could be applied to quantify the difference of brain activities in different cognitive tasks, and further provide some explanations for cognitive behavior.
A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation （DISOPE） was proposed for nonlinear cascade systems under network environment. Under the distributed control structure, online optimization of the cascade system was composed of several cascaded agents that can cooperate and exchange information via network communication. By iterating on modified distributed linear optimal control problems on the basis of estimating parameters at every iteration the correct optimal control action of the nonlinear model predictive control problem of the cascade system could be obtained, assuming that the algorithm was convergent. This approach avoids solving the complex nonlinear optimization problem and significantly reduces the computational burden. The simulation results of the fossil fuel power unit are illustrated to verify the effectiveness and practicability of the proposed algorithm.
We study the inclusive production of doubly heavy baryon Ξcc at polarized photon collider. Our results show that proper choice of the initial beam polarizations may increase the production rate of Ξcc approximately 10%.
