We study the response of complex networks subject to attacks on vertices and edges. Several existing complex network models as well as real-world networks of scientific collaborations and Internet traffic are numerically investigated, and the network performance is quantitatively measured by the average inverse geodesic length and the size of the largest connected subgraph. For each case of attacks on vertices and edges, four different attacking strategies are used: removals by the descending order of the degree and the betweenness centrality, calculated for either the initial network or the current network during the removal procedure. It is found that the removals by the recalculated degrees and betweenness centralities are often more harmful than the attack strategies based on the initial network, suggesting that the network structure changes as important vertices or edges are removed. Furthermore, the correlation between the betweenness centrality and the degree in complex networks is studied.

We extend the standard scale-free network model to include a "triad formation step". We analyze the geometric properties of networks generated by this algorithm both analytically and by numerical calculations, and find that our model possesses the same characteristics as the standard scale-free networks like the power-law degree distribution and the small average geodesic length, but with the high-clustering at the same time. In our model, the clustering coefficient is also shown to be tunable simply by changing a control parameter-the average number of triad formation trials per time step.PACS numbers: 89.75.Fb, 89.75.Hc, A great number of systems in many branches of science can be modeled as large sparse graphs, sharing many geometrical properties [1]. For example: social networks, computer networks, and metabolic networks of certain organisms all have a logarithmically growing average geodesic (shortest path) length ℓ and an approximately algebraically decaying distribution of vertex degree. In addition to this, social networks typically show a high clustering, or local transitivity: If person A knows B and C, then B and C are likely to know each other.Works on the geometry of social networks, which is the main focus of the present paper, have originated from Rapoport's studies of disease spreading [2], and have been further developed in Refs. [3,4]. General mathematical models for random graphs with a structural bias are called the Markov graphs and were studied in Ref. [5]. In the physics literature, networks with high clustering are commonly modeled by the small-world network model of Watts and Strogatz (WS) [6], while networks with the power-law degree distribution by the scale-free network model of Barabási and Albert (BA) [7]. Although both models have a logarithmically increasing ℓ with the network size, each model lacks the property of the other model: the WS model shows a high clustering but without the power-law degree distribution, while the BA model with the scale-free nature does not possess the high clustering. In this work, we propose a network model which has both the perfect power-law degree distribution and the high clustering. Furthermore, in our model, the degree of the clustering, measured by the clustering coefficient (see below), is shown to be tunable and thus controllable by adjusting a parameter of the model.We start from the definition of a network as a graph G = (V, E), where V is the set of vertices and E is the set of edges [8]. An edge connects pairs of vertices in V and not more than one edge may connect a specific pair of vertices. To quantify the clustering, Watts and Strogatz introduced the clustering coefficient γ ≡ γ v with the average · · · for all vertices in V. The local clus- * Electronic address: holme@tp.umu.se † Electronic address: kim@tp.umu.se

MALAT1 has previously been described as a metastasis-promoting long non-coding RNA (lncRNA). Unexpectedly, we found that targeted inactivation of the Malat1 gene without altering the expression of its adjacent genes in a transgenic mouse model of breast cancer promoted lung metastasis, and importantly, this phenotype was reversed by genetic add-back of Malat1 . Similarly, knockout of MALAT1 in human breast cancer cells induced their metastatic ability, which was reversed by Malat1 re-expression. Conversely, overexpression of Malat1 suppressed breast cancer metastasis in transgenic, xenograft, and syngeneic models. Mechanistically, MALAT1 binds and inactivates the pro-metastatic transcription factor TEAD, blocking TEAD from associating with its co-activator YAP and target gene promoters. Moreover, MALAT1 levels inversely correlate with breast cancer progression and metastatic ability. These findings demonstrate that MALAT1 is a metastasis-suppressing lncRNA rather than a metastasis promoter in breast cancer, calling for rectification of the model for a highly abundant and conserved lncRNA.

We study evolving networks based on the Barabási-Albert scale-free network model with vertices sensitive to overload breakdown. The load of a vertex is defined as the betweenness centrality of the vertex. Two cases of load limitation are considered, corresponding to the fact that the average number of connections per vertex is increasing with the network's size ("extrinsic communication activity"), or that it is constant ("intrinsic communication activity"). Avalanchelike breakdowns for both load limitations are observed. In order to avoid such avalanches we argue that the capacity of the vertices has to grow with the size of the system. An interesting irregular dynamics of the formation of the giant component (for the intrinsic communication activity case) is also studied. Implications on the growth of the Internet are discussed.

We investigate collective synchronization in a system of coupled oscillators on small-world networks. The order parameters which measure synchronization of phases and frequencies are introduced and analyzed by means of dynamic simulations and finite-size scaling. Phase synchronization is observed to emerge in the presence of even a tiny fraction P of shortcuts and to display saturated behavior for P > ∼ 0.5. This indicates that the same synchronizability as the random network (P = 1) can be achieved with relatively small number of shortcuts. The transient behavior of the synchronization, obtained from the measurement of the relaxation time, is also discussed. Systems of coupled nonlinear oscillators, which serve as prototype models for various oscillatory systems in nature, have attracted much attention. Those systems exhibit remarkable phenomena of collective synchronization, which have been observed in a variety of physical, biological, and chemical systems [1]. Up to date, existing studies on collective synchronization have mostly been performed either on the local regular networks such as d-dimensional cubic lattices or on the globally connected geometry. In recent years, there has been suggested the possibility that a number of diverse systems in nature may have the same topological structure as the smallworld networks [2], which are intermediate of the local regular networks and the fully random networks. Such small-world networks are usually characterized by two interesting features: high clustering, which is a characteristic of regular networks, and the short path length, which is typically observed in random networks [2]. Most studies on small-world networks have been focused on the geometrical and topological characterization of the networks, with little attention paid to dynamics defined on them. Recently, some studies have considered dynamical systems put on small-world networks [3,4], where such desirable features as faster propagation of information, better computational power, and stronger synchronizability have been observed. In Ref.[3], frequency synchronization on the small-world network has been noticed in the presence of a small amount of randomly rewired connections and the possibility of the transition to global entrainment with the mean-field nature has been pointed out. However, quantitative analysis has not been performed and proper understanding is still lacking. For example, the critical rewiring probability beyond which true long-range order is present at finite coupling strength has not been addressed.In this paper we study the detailed aspects of the collective synchronizations on small-world networks, as the rewiring probability and the coupling strength are varied.In general, frequency synchronization can be attained without synchronization of phases, and we explore both to investigate the synchronizationdesynchronization transition. Via careful finite-size scaling, we find the following: (i) Phase synchronization as well as frequency one, which is absent in one-dimensional regula...

The authors examined cultural preferences for formal versus intuitive reasoning among East Asian (Chinese and Korean), Asian American, and European American university students. We investigated categorization (Studies 1 and 2), conceptual structure (Study 3), and deductive reasoning (Studies 3 and 4). In each study a cognitive conflict was activated between formal and intuitive strategies of reasoning. European Americans, more than Chinese and Koreans, set aside intuition in favor of formal reasoning. Conversely, Chinese and Koreans relied on intuitive strategies more than European Americans. Asian Americans' reasoning was either identical to that of European Americans, or intermediate. Differences emerged against a background of similar reasoning tendencies across cultures in the absence of conflict between formal and intuitive strategies.

While shorter characteristic path length has in general been believed to enhance synchronizability of a coupled oscillator system on a complex network, the suppressing tendency of the heterogeneity of the degree distribution, even for shorter characteristic path length, has also been reported. To see this, we investigate the effects of various factors such as the degree, characteristic path length, heterogeneity, and betweenness centrality on synchronization, and find a consistent trend between the synchronization and the betweenness centrality. The betweenness centrality is thus proposed as a good indicator for synchronizability.

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