Exploring nuclear symmetry energy with isospin dependence in neutron skin thickness of nuclei

We propose an alternative way to constrain the density dependence of the symmetry energy from the neutron skin thickness of nuclei which shows a linear relation to both the isospin asymmetry and the nuclear charge with a form of Z^2/3. The relation of the neutron skin thickness to the nuclear charge and isospin asymmetry is systematically studied with the data from antiprotonic atom measurement, and with the extended Thomas-Fermi approach incorporating the Skyrme energy density functional. An obviously linear relationship between the slope parameter L of the nuclear symmetry energy and the isospin asymmetry dependent parameter of the neutron skin thickness can be found, by adopting 70 Skyrme interactions in the calculations. Combining the available experimental data, the constraint of -20 MeV L 82 MeV on the slope parameter of the symmetry energy is obtained. The Skyrme interactions satisfying the constraint are selected.     

Fore-aft asymmetry of the 2H(n,γ)3H at very low energies

We have used the recent effective field theory (EFT) which is constructed from two-and three-nucleon interactions, using minimal substitution in the momentum dependence of these interactions. We present the calculations of the fore-aft asymmetry of γ-rays in the reaction ²H(n,γ)³H which are based on EFT up to next-to-next-to leading order (N²LO). The results are compared with the recently reported calculations and measurements of the fore-aft asymmetry of γ-rays from neutron-deuteron radiative capture. The calculated fore-aft asymmetry of the nd radiative capture process above deuteron breakup threshold is in good agreement with the available experimental data up to 20 MeV.     

A Method to Design Synthetic Cell-Cycle Networks

The interactions among proteins, DNA and RNA in an organism form elaborate cell-cycle networks which govern cell growth and proliferation. Understanding the common structure of cell-cycle networks will be of great benefit to science research. Here, inspired by the importance of the cell-cycle regulatory network of yeast which has been studied intensively, we focus on small networks with 11 nodes, equivalent to that of the cell-cycle regulatory network used by Li et al. [Proc. Natl. Acad. Sci. USA 101（2004）4781] Using a Boolean model, we study the correlation between structure and function, and a possible common structure. It is found that cascade-like networks with a great number of interactions between nodes are stable. Based on these findings, we are able to construct synthetic networks that have the same functions as the cell-cycle regulatory network.     

Cluster projective synchronization of complex networks with nonidentical dynamical nodes

We investigate a new cluster projective synchronization(CPS) scheme in time-varying delay coupled complex dynamical networks with nonidentical nodes.Based on the community structure of the networks,the controllers are designed differently for the nodes in one community,which have direct connections to the nodes in the other communities and the nodes without direct connections to the nodes in the other communities.Some sufficient criteria are derived to ensure the nodes in the same group projectively synchronize and there is also projective synchronization between nodes in different groups.Particularly,the weight configuration matrix is not assumed to be symmetric or irreducible.The numerical simulations are performed to verify the effectiveness of the theoretical results.     

Lepton Polarization Asymmetry in B → e^＋e^- Decay beyond the Standard Model

The lepton polarization asymmetry in the B → e^＋e^- decay, when one of the leptons is polarized, is investigated by using the most general form of the effective Hamiltonian. We find allowed regions for the new scalar Wilson coefficients, assuming that the experimental branching ratio is measured within 10% percent uncertainty. Then using these restrictions to the new coefficients the sensitivity of the lepton polarization asymmetry to them is studied. Moreover, it is observed that there are regions of terms describing the scalar interactions, where lepton polarization asymmetry differs from zero, which can serve as a good test for searching new physics beyond the standard model.     

Poor rich demarcation of Matthew effect on scale-free systems and its application

In a scale-free network,only a minority of nodes are connected very often,while the majority of nodes are connected rarely. However,what is the ratio of minority nodes to majority nodes resulting from the Matthew effect In this paper,based on a simple preferential random model,the poor-rich demarcation points are found to vary in a limited range,and form a poor-rich demarcation interval that approximates to k/m ∈ [3,4]. As a result,the (cumulative) degree distribution of a scale-free network can be divided into three intervals: the poor interval,the demarcation interval and the rich interval. The inequality of the degree distribution in each interval is measured. Finally,the Matthew effect is applied to the ABC analysis of project management.     

Reference model based consensus control of second-order multi-agent systems

This paper deals with the consensus problem of multi-agent systems with second-order dynamics.The objective is to design algorithms such that all agents will have same positions and velocities.First,a reference model based consensus algorithm is proposed.It is proved that the consensus can be achieved if the communication graph has a spanning tree.Different from most of the consensus algorithms proposed in the literature,the parameters of the control laws are different among agents.Therefore,each agent can design its control law independently.Secondly,it gives a consensus algorithm for the case that the velocities of the agents are not available.Thirdly,the effectiveness of the input delay and the communication delay is considered.It shows that consensus can be achieved if the input delay of every agent is smaller than a bound related to parameters in its control law.Finally,some numerical examples are given to illustrate the proposed results.     

Linear and nonlinear generalized consensuses of multi-agent systems

Consensus in directed networks of multiple agents, as an important topic, has become an active research subject. Over the past several years, some types of consensus problems have been studied. In this paper, we propose a novel type of consensus, the generalized consensus （GC）, which includes the traditional consensus, the anti-consensus, and the cluster consensus as its special cases. Based on the Lyapunov＇s direct method and the graph theory, a simple control algorithm is designed to achieve the generalized consensus in a network of agents. Numerical simulations of linear and nonlinear GC are used to verify the effectiveness of the theoretical analysis.     

Evolution of a protein domain interaction network

In this paper, we attempt to understand complex network evolution from the underlying evolutionary relationship between biological organisms. Firstly, we construct a Pfam domain interaction network for each of the 470 completely sequenced organisms, and therefore each organism is correlated with a specific Pfam domain interaction network; secondly, we infer the evolutionary relationship of these organisms with the nearest neighbour joining method; thirdly, we use the evolutionary relationship between organisms constructed in the second step as the evolutionary course of the Pfam domain interaction network constructed in the first step. This analysis of the evolutionary course shows: (i) there is a conserved sub-network structure in network evolution; in this sub-network, nodes with lower degree prefer to maintain their connectivity invariant, and hubs tend to maintain their role as a hub is attached preferentially to new added nodes; (ii) few nodes are conserved as hubs; most of the other nodes are conserved as one with very low degree; (iii) in the course of network evolution, new nodes are added to the network either individually in most cases or as clusters with relative high clustering coefficients in a very few cases.     

Consensus protocol for multi-agent continuous systems

Based on the algebraic graph theory, the networked multi-agent continuous systems are investigated. Firstly, the digraph （directed graph） represents the topology of a networked system, and then a consensus convergence criterion of system is proposed. Secondly, the issue of stability of multi-agent systems and the consensus convergence problem of information states are all analysed. Furthermore, the consensus equilibrium point of system is proved to be global and asymptotically reach the convex combination of initial states. Finally, two examples are taken to show the effectiveness of the results obtained in this paper.     

Interspecific competition underlying mutualistic networks

Multiple classes of interactions may exist affecting one another in a given system. For the mutualistic networks of plants and pollinating animals, it has been known that the degree distribution is broad but often deviates from power-law form more significantly for plants than animals. To illuminate the origin of such asymmetry, we study a model network in which links are assigned under generalized preferential-selection rules between two groups of nodes and find the sensitive dependence of the resulting connectivity pattern on the model parameters. The nonlinearity of preferential selection can come from interspecific interactions among animals and among plants. The model-based analysis of real-world mutualistic networks suggests that a new animal determines its partners not only by their abundance but also under the competition with existing animal species, which leads to the stretched-exponential degree distributions of plants.     

Asymmetry through time dependency

Given a single network of interactions, asymmetry arises when the links aredirected. For example, if protein A upregulates protein B and protein Bupregulates protein C, then (in the absence of any further relationships between them) Amay affect C but not vice versa. This type of imbalance is reflected in the associatedadjacency matrix, which will lack symmetry. A different type of imbalance can arise wheninteractions appear and disappear over time. If A meets B today and B meets C tomorrow,then (in the absence of any further relationships between them) A may pass a message ordisease to C, but not vice versa. Hence, even when each interaction is a two-way exchange,the effect of time ordering can introduce asymmetry. This observation is very closelyrelated to the fact that matrix multiplication is not commutative. In this work, wedescribe a method that has been designed to reveal asymmetry in static networks and showhow it may be combined with a measure that summarizes the potential information flowbetween nodes in the temporal case. This results in a new method that quantifies theasymmetry arising through time ordering. We show by example that the new tool can be usedto visualize and quantify the amount of asymmetry caused by the arrow of time.     

一类异构多智能体系统固定和切换拓扑下的一致性分析

对包含一阶二阶智能体的异构系统有向图中的一致性问题进行研究.对该系统采用了一种线性分布式一致性协议,基于图论和矩阵分析的方法,分析了在固定和切换拓扑情况下系统获得一致性的充分条件,该条件与控制参数和通信拓扑有关.给出了固定拓扑中系统的一致平衡点,证明了仅通信拓扑中的根节点对平衡点起作用.数值仿真验证了理论分析的正确性.     

Mössbauer effect studies of some trimeric iron compounds

Mössbauer spectra of some basic iron (III) carboxylates are reported. The zero field spectra are quadrupole doublets with a characteristic temperature dependent asymmetry. In applied magnetic fields at 4·2°K large hyperfine magnetic fields are observed. These can only result from a Hamiltonian which is not symmetric in all three sites. This asymmetry may be due to a structural asymmetry or to small intercluster magnetic interactions.     

Synchronization in complex networks with age ordering

The propensity for synchronization is studied in a complex network of asymmetrically coupled units, where the asymmetry in a given link is determined by the relative age of the involved nodes. In growing scale-free networks, synchronization is enhanced when couplings from older to younger nodes are dominant. We describe the requirements for such an effect in a more general context and compare with the situations in nongrowing random networks with and without a degree ordering.     

Social power and opinion formation in complex networks

In this paper we investigate the effects of social power on the evolution of opinions in model networks as well as in a number of real social networks. A continuous opinion formation model is considered and the analysis is performed through numerical simulation. Social power is given to a proportion of agents selected either randomly or based on their degrees. As artificial network structures, we consider scale-free networks constructed through preferential attachment and Watts–Strogatz networks. Numerical simulations show that scale-free networks with degree-based social power on the hub nodes have an optimal case where the largest number of the nodes reaches a consensus. However, given power to a random selection of nodes could not improve consensus properties. Introducing social power in Watts–Strogatz networks could not significantly change the consensus profile.     

Leptogenesis from spin-gravity coupling following inflation

The energy levels of the left- and the right-handed neutrinos are split in the background of gravitational waves generated during inflation, which, in presence of lepton-number-violating interactions, gives rise to a net lepton asymmetry at equilibrium. Lepton number violation is achieved by the same dimension five operator which gives rise to neutrino masses after electroweak symmetry breaking. A net baryon asymmetry of the same magnitude can be generated from this lepton asymmetry by electroweak sphaleron processes.     

Electric induction interactions between molecules through fifth-order perturbation theory

Electric induction interactions in a system of N molecules of arbitrary asymmetry are examined in the first five orders of non-degenerate perturbation theory. The results are used to evaluate fourth-order induction interactions between two hydrogen fluoride molecules     

Leptogenesis and composite heavy neutrinos with gauge-mediated interactions

Leptogenesis is an appealing framework to account for the baryon asymmetry in the universe. To this end physics beyond the standard model is demanded. In this paper we investigate the possibility to attain successful leptogenesis with composite Majorana neutrinos. We work in the framework of effective gauge-mediated and contact interactions without any reference to an underlying compositeness theory. This approach is the one adopted in all current experimental searches for composite fermions at colliders. In the case of gauge-mediated interactions, we calculate the CP asymmetry in heavy composite neutrino decays. Both the direct and the indirect CP asymmetry are derived and resonant leptogenesis is also discussed. We find that the Sakharov conditions can be met and, for some choice of the parameters, the correct order of magnitude of the baryon asymmetry is reproduced.     

A simple consensus algorithm for distributed averaging in random geographical networks

Random geographical networks are realistic models for wireless sensor networks which are used in many applications. Achieving average consensus is very important in sensor networks and the faster the consensus is, the durable the sensors?? life, and thus, the better the performance of the network. In this paper we compared the performance of a number of linear consensus algorithms with application to distributed averaging in random geographical networks. Interestingly, the simplest algorithm ?C where only the degree of receiving nodes is needed for the averaging ?C had the best performance in terms of the consensus time. Furthermore, we proved that the network has guaranteed convergence with this simple algorithm.