Catálogo de publicaciones - revistas

<jats:p>Network information mining is the study of the network topology, which may answer a large number of application-based questions towards the structural evolution and the function of a real system. The question can be related to how the real system evolves or how individuals interact with each other in social networks. Although the evolution of the real system may seem to be found regularly, capturing patterns on the whole process of evolution is not trivial. Link prediction is one of the most important technologies in network information mining, which can help us understand the evolution mechanism of real-life network. Link prediction aims to uncover missing links or quantify the likelihood of the emergence of nonexistent links from known network structures. Currently, widely existing methods of link prediction almost focus on short-path networks that usually have a myriad of close triangular structures. However, these algorithms on highly sparse or long-path networks have poor performance. Here, we propose a new index that is associated with the principles of structural equivalence and shortest path length (SESPL) to estimate the likelihood of link existence in long-path networks. Through a test of 548 real networks, we find that SESPL is more effective and efficient than other similarity-based predictors in long-path networks. Meanwhile, we also exploit the performance of SESPL predictor and of embedding-based approaches via machine learning techniques. The results show that the performance of SESPL can achieve a gain of 44.09% over GraphWave and 7.93% over Node2vec. Finally, according to the matrix of maximal information coefficient (MIC) between all the similarity-based predictors, SESPL is a new independent feature in the space of traditional similarity features.</jats:p>

<jats:p>A flurry of studies indicates that population size has a positive effect on innovation, however, cross-country empirical evidence remains sparse. In this paper, we add to the literature by investigating the relationship between population size and innovation efficiency at the country level through constructing three relative indexes based on the datasets of patent applications and Research and Development (R&amp;D) investment. Different from previous studies based on absolute innovation indicators, the relative indexes can reflect the core innovation efficiency of economies by excluding the impact from the difference of economic development level, with a view putting all economies into a comparable standard framework. For all of the three relative indexes, their long-term trends show significant correlations with population size, and the economy with a larger population usually has better and stable performance on the trends of innovation efficiency. In addition, we find that there is a critical population size, over which the economy would be more likely to have a spontaneous improvement on innovation efficiency. This study provides direct evidence in supporting the population size advantage on the trends of innovation efficiency at the economy level and provides new insight to understand the rapid development of innovation in a few populous countries.</jats:p>

<jats:p>Accurate identification of influential nodes facilitates the control of rumor propagation and interrupts the spread of computer viruses. Many classical approaches have been proposed by researchers regarding different aspects. To explore the impact of location information in depth, this paper proposes an improved global structure model to characterize the influence of nodes. The method considers both the node’s self-information and the role of the location information of neighboring nodes. First, degree centrality of each node is calculated, and then degree value of each node is used to represent self-influence, and degree values of the neighbor layer nodes are divided by the power of the path length, which is path attenuation used to represent global influence. Finally, an extended improved global structure model that considers the nearest neighbor information after combining self-influence and global influence is proposed to identify influential nodes. In this paper, the propagation process of a real network is obtained by simulation with the SIR model, and the effectiveness of the proposed method is verified from two aspects of discrimination and accuracy. The experimental results show that the proposed method is more accurate in identifying influential nodes than other comparative methods with multiple networks.</jats:p>

<jats:p>The identification of key nodes plays an important role in improving the robustness of the transportation network. For different types of transportation networks, the effect of the same identification method may be different. It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks. Based on the knowledge of complex networks, the metro networks and the bus networks are selected as the objects, and the key nodes are identified by the node degree identification method, the neighbor node degree identification method, the weighted <jats:italic>k</jats:italic>-shell degree neighborhood identification method (KSD), the degree <jats:italic>k</jats:italic>-shell identification method (DKS), and the degree <jats:italic>k</jats:italic>-shell neighborhood identification method (DKSN). Take the network efficiency and the largest connected subgraph as the effective indicators. The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.</jats:p>

<jats:p>Perturbation analysis and scale expansion are used to derive the (2+1)-dimensional coupled nonlinear Schrödinger (CNLS) equations that can describe interactions of two Rossby waves propagating in stratified fluids. The (2+1)-dimensional equations can reflect and describe the wave propagation more intuitively and accurately. The properties of the two waves in the process of propagation can be analyzed by the solution obtained from the equations using the Hirota bilinear method, and the influence factors of modulational instability are analyzed. The results suggest that, when two Rossby waves with slightly different wave numbers propagate in the stratified fluids, the intensity of bright soliton decreases with the increases of dark soliton coefficients. In addition, the size of modulational instable area is related to the amplitude and wave number in <jats:italic>y</jats:italic> direction.</jats:p>

<jats:p>This paper examines the effect of the observation time on source identification of a discrete-time susceptible-infected-recovered diffusion process in a network with snapshot of partial nodes. We formulate the source identification problem as a maximum likelihood (ML) estimator and develop a statistical inference method based on Monte Carlo simulation (MCS) to estimate the source location and the initial time of diffusion. Experimental results in synthetic networks and real-world networks demonstrate evident impact of the observation time as well as the fraction of the observers on the concerned problem.</jats:p>

<jats:p>The process of ionizing normal saline induced by femtosecond laser is studied from the perspective of gas production rate and composition. When the repetition rate is less than 1000 Hz, each laser pulse independently generates ionization gas. At the same time, we discovered the inhibitory effect of meglumini diatrizoici on the ionization process and explained the reasons for this inhibition. Finally, the gas composition proved that the primary gas production mechanism of the femtosecond laser is the decomposition of water molecular, and the composition of the solution after the reaction proved the decomposition effect of the laser on meglumine.</jats:p>

<jats:p>We investigate the topological phase transition and the enhanced topological effect in a cavity optomechanical system with periodical modulation. By calculating the steady-state equations of the system, the steady-state conditions of cavity fields and the restricted conditions of effective optomechanical couplings are demonstrated. It is found that the cavity optomechanical system can be modulated to different topological Su–Schrieffer–Heeger (SSH) phases via designing the optomechanical couplings legitimately. Meanwhile, combining the effective optomechanical couplings and the probability distributions of gap states, we reveal the topological phase transition between trivial SSH phase and nontrivial SSH phase via adjusting the decay rates of cavity fields. Moreover, we find that the enhanced topological effect of gap states can be achieved by enlarging the size of system and adjusting the decay rates of cavity fields.</jats:p>

<jats:p>We investigate how the correlated actions of quantum channels affect the robustness of entangled states. We consider the Bell-like state and random two-qubit pure states in the correlated depolarizing, bit flip, bit-phase flip, and phase flip channels. It is found that the robustness of two-qubit pure states can be noticeably enhanced due to the correlations between consecutive actions of these noisy channels, and the Bell-like state is always the most robust one. We also consider the robustness of three-qubit pure states in correlated noisy channels. For the correlated bit flip and phase flip channels, the result shows that although the most robust and most fragile states are locally unitary equivalent, they exhibit different robustness in different correlated channels, and the effect of channel correlations on them is also significantly different. However, for the correlated depolarizing and bit-phase flip channels, the robustness of two special three-qubit pure states is exactly the same. Moreover, compared with the random three-qubit pure states, they are neither the most robust states nor the most fragile states.</jats:p>

<jats:p>We study the single-photon blockade (1PB), two-photon blockade (2PB), and photon-induced tunneling (PIT) effects in a cavity–atom optomechanical system in which a two-level atom is coupled to a single-model cavity field via a two-photon interaction. By analyzing the eigenenergy spectrum of the system, we obtain a perfect 1PB with a high occupancy probability of single-photon excitation, which means that a high-quality and efficient single-photon source can be generated. However, PIT often occurs in many cases when we consider 2PB in analogy to 1PB. In addition, we find that a 2PB region will present in the optomechanical system, which can be proved by calculating the correlation function of the model analytically.</jats:p>