Peng, LuTang, JunMa, JunLuo, Jinming...
11页查看更多>>摘要：The synchronization of the nervous system is strongly related to diseases such as Parkinson's, epilepsy, and schizophrenia. Given that the existence of autapse has been proved experimentally, the influence of autapse on the synchronization in a neural network is studied numerically. The results show that increasing coupling intensity could destroy the synchronization of the neural firing pattern, and reduce the firing rate in the network. Especially, an inhibition zone, in which the neural firing is inhibited completely, exists for changes of both coupling intensity and time delay in all types of autapses. As a key factor for different types of autapses, the transmission time delay influences the synchronization complicatedly, i.e., increasing time delay could modulate synchronization for different types of autapse and parameter regions. The theoretical results in this paper shed some light on the study about the mechanism of neural synchronization. (C) 2022 Elsevier B.V. All rights reserved.
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NSTL
Elsevier
Valdez, L. D.Braunstein, L. A.
11页查看更多>>摘要：Real networks are vulnerable to random failures and malicious attacks. However, when a node is harmed or damaged, it may remain partially functional, which helps to maintain the overall network structure and functionality. In this paper, we study the network structure for a fractional percolation process (Shang, 2014), in which the state of a node can be either fully functional (FF), partially functional (PF), or dysfunctional (D). We develop new equations to calculate the relative size of the percolating cluster of FF and PF nodes, that are in agreement with our stochastic simulations. In addition, we find a regime in which the percolating cluster can be described as a coarse-grained bipartite network, namely, as a set of finite groups of FF nodes connected by PF nodes. Moreover, these groups behave as a set of "supernodes "with a power-law degree distribution. Finally, we show how this emergent structure explains the values of several critical exponents around the percolation threshold. (C)& nbsp;2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Zhou, YuyangZheng, ShuyanHu, ZhonghuiChen, Yanyan...
16页查看更多>>摘要：As the hub of urban railway transit, metro stations portray the skeleton structure of the public transit network. This study proposes a method of station classification from the dual perspectives of network structure and passenger flow. Each perspective considers the two aspects, one is the characteristics of the node itself, such as degree and the entrance and exit ridership; another considers the characteristics of the influence of other nodes, such as betweenness centrality and passing flow. Among them, the importance index of passing flow is calculated by the PageRank algorithm. According to these characteristics, metro stations are classified by k-means clustering algorithm after dimensionality reduction. The case study is conducted through nearly five million records from 278 stations in Beijing. From the classification results, stations are divided into six categories. Qualitative and quantitative regulations are proposed to reduce the risk of high ridership stations and improve the operation efficiency for few ridership stations.(C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Guo, YaoqiShi, FengyuanYu, ZhulingYao, Shanshan...
19页查看更多>>摘要：Based on the asymmetric multifractal detrending cross-correlation analysis (MF-ADCCA) method and the multifractal cross-correlation analysis (MFCCA) method, we propose a new method-the asymmetric multifractal cross-correlation analysis (MF-ACCA) method. The simulation results show that the algorithm can describe the asymmetric multifractal characteristics of two time series from qualitative and quantitative perspectives and we compare the MF-ACCA method and the MF-ADCCA method by using Binary ARFIMA model. In addition, the MF-ACCA method is used to analyze the asymmetric cross-correlation relationships among energy markets with different trends. We confirm that when a market experiences large fluctuations, the overall energy market in China ex-hibits multifractal characteristics, and the multifractal cross-correlations among energy markets are asymmetric. (C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Joseph, BijinChakrabarti, Bikas K.
9页查看更多>>摘要：We study analytically the change in the wealth (x) distribution P(x) against saving propensity lambda in a closed economy, using the Kinetic theory. We estimate the Gini (g) and Kolkata (k) indices by deriving (using P(x)) the Lorenz function L(f), giving the cumulative fraction L of wealth possessed by fraction f of the people ordered in ascending order of wealth. First, using the exact result for P(x) when lambda = 0 we derive L(f), and from there the index values g and k. We then proceed with an approximate gamma distribution form of P(x) for non-zero values of lambda. Then we derive the results for g and k at lambda = 0.25 and as lambda -> 1. We note that for lambda -> 1 the wealth distribution P(x) becomes a Dirac delta-function. Using this and assuming that form for larger values of lambda we proceed for an approximate estimate for P(x) centered around the most probable wealth (a function of lambda). We utilize this approximate form to evaluate L(f), and using this along with the known analytical expression for g, we derive an analytical expression for k(lambda). These analytical results for g and k at different lambda are compared with numerical (Monte Carlo) results from the study of the Chakraborti-Chakrabarti model. Next we derive analytically a relation between g and k. From the analytical expressions of g and k, we proceed for a thermodynamic mapping to show that the former corresponds to entropy and the latter corresponds to the inverse temperature. (C)& nbsp;2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Li, XiaopengHan, WeiweiYang, WenjunWang, Juan...
18页查看更多>>摘要：Due to the contradiction between the finiteness of resources and people's infinite demand for them, we cannot deny the impact of the limited resources on human behavior. To this end, we construct a novel resource-based conditional interaction model from a tiny perspective, in which not only can limited resources be redistributed among the population, but resources owned by players also affect whether they can interact with each other or not. To be specific, a player who successfully imitates his neighbor's strategy will have to pay epsilon proportion of his resources to the opponent as the learning cost. In addition, if and only if the resource difference between the focal player x and one of his neighbors y is within an acceptable tolerance interval tau, they will indisputably interact with each other. We mainly resort to the prisoner's dilemma game and asynchronous strategy update to verify the effectiveness of the model. By resorting to extensive Monte Carlo simulations, we find that there exists an optimal acceptable tolerance interval tau, varying with the value of cost-to-benefit ratio u, to make the promotion of cooperation the most obvious. We also confirm that players' irrational behavior can be influenced by this resource-based partner selection. However, if we introduce one kind of minimal resource protection mechanism into our proposed model, the level of cooperation cannot be further elevated, or even be hindered when compared with the case without the minimal resource protection mechanism. In the end, we further verify the robustness and effectiveness of the proposed model through other social dilemmas, network topologies, and synchronous strategy update pattern. To a certain extent, we wish that our efforts can wipe out some barriers for researching the evolution of cooperation within the selfish population. (C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
von Schantz, AntonEhtamo, Harri
20页查看更多>>摘要：In an emergency situation, the evacuation of a large crowd from a complex building can become slow or even dangerous without a working evacuation plan. The use of rescue guides that lead the crowd out of the building can improve the evacuation efficiency. An important issue is how to choose the number, positions, and exit assignments of these guides to minimize the evacuation time of the crowd. Here, we model the evacuating crowd as a multi-agent system with the social force model and simple interaction rules for guides and their followers. We formulate the problem of minimizing the evacuation time using rescue guides as a stochastic optimization problem. Then, we solve it with a procedure combining numerical simulation and a genetic algorithm (GA). The GA iteratively searches for the optimal evacuation plan, while numerical simulations evaluate the evacuation time of the plans. We apply the procedure on a test case and on an evacuation of a fictional conference building. The procedure is able to solve the number of guides, their initial positions and exit assignments in a single although complicated optimization. The attained results show that the procedure converges to an optimal evacuation plan, which minimizes the evacuation time and mitigates congestion and the effect of random deviations in agents' motion. (C)& nbsp;2022 The Author(s). Published by Elsevier B.V.
原文链接:- NSTL
- Elsevier
Yang, XiaoxiaZhang, RuiPan, FuquanYang, Yi...
23页查看更多>>摘要：Evacuation path of pedestrians at subway station can directly affect the evacuation efficiency, and then affect the service level of the station. A Fisk stochastic user equilibrium model considering the congestion factor is established to assist evacuation path planning, which could avoid the bottleneck area and dangerous situation in advance. By comparing the field statistical data with simulation data of the number of pedestrians at the entrance gate of subway station, it is verified that the social force model and the minimum cost model can basically reproduce the movement law and path selection behavior of pedestrians at the subway station. Simulation experiment is carried out to compare the evacuation efficiency at the subway station under the stochastic user equilibrium model and the minimum cost model. The results indicate that the number of pedestrians at each gate is relatively balanced which can avoid overcrowding under the stochastic user equilibrium model. The total evacuation time can be reduced by 15%, and the individual evacuation time can be saved about 0.57 min. By comparing the 3D overall pedestrian trajectory and the 2D local pedestrian trajectory, it is found that the stochastic user equilibrium model is of great significance for evacuation path optimization at the subway station. The quantitative relationship between the number of pedestrians and evacuation time at the subway station is given through regression analysis under stochastic user equilibrium model and minimum cost model. The suspension of escalators can obviously result in congestion at the gate and increase the total evacuation time. When pedestrian density at the station is low, closing a certain exit can significantly improve the pedestrian traffic efficiency at the gate and greatly reduce the total evacuation time. The stochastic user equilibrium evacuation path planning model constructed in this paper provides a guidance strategy for pedestrian evacuation, which could improve the efficiency and safety of subway evacuation system. (C)& nbsp;2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Ducuara, Andres F.Susa, Cristian E.Reina, John H.
12页查看更多>>摘要：We investigate the behaviour of quantum CHSH-nonlocality, F3-steering, and usefulness for teleportation in an interacting two-qubit dissipative system. We show regimes where these three quantum correlations can be extracted by means of local filtering operations, despite them not being displayed in the bare natural time evolution. Moreover, we show the existence of local hidden state (LHS) and local hidden variable (LHV) models for some states during the dynamics and thus, showing that apparently-useless physical systems could still exhibit quantum correlations, which are hidden from us, but that can still be revealed by means of local filtering operations and therefore, displaying the phenomenon of hidden quantum correlations. Furthermore, we report on extreme versions of these phenomena, where the revealed correlations achieve the maximal amount allowed by quantum theory. This phenomenon of maximal hidden correlations relies on the qubits collective damping, and may take place even in long-distance separated qubits. Despite the immediate appeal of the physical system displaying such an extreme phenomenon, we furthermore show however, that there actually exists a trade-off between the amount of quantum correlations which can be extracted and the filtering probability with which such protocol can be implemented. Explicitly, the higher the amount of correlations to be extracted, the more difficult it becomes for the protocol to be implemented (lower filtering probability). This is consequently showing us the remarkable fact that whilst the phenomenon of maximal hidden quantum correlations does naturally emerge during the evolution of physical systems, Nature does not completely give it away for free, by imposing a limit to the rate at which this can be done. From a theoretical point of view, the existence of such trade-off imposes a fundamental limit to the extraction of quantum correlations by local filtering operations. From a practical point of view on the other hand, the results here presented determine the amount of resources that should be invested in order to extract such maximal hidden quantum correlations.(c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Cullen, Andrew C.Alpcan, TansuKalloniatis, Alexander C.
14页查看更多>>摘要：We apply computational Game Theory to a unification of physics-based models that represent decision-making across a number of agents within both cooperative and competitive processes. Here the competitors try to both positively influence their own returns, while negatively affecting those of their competitors. Modelling these interactions with the so-called Boyd-Kuramoto-Lanchester (BKL) complex dynamical system model yields results that can be applied to business, gaming and security contexts. This paper studies a class of decision problems on the BKL model, where a large set of coupled, switching dynamical systems are analysed using game-theoretic methods.& nbsp;Due to their size, the computational cost of solving these BKL games becomes the dominant factor in the solution process. To resolve this, we introduce a novel Nash Dominant solver, which is both numerically efficient and exact. The performance of this new solution technique is compared to traditional exact solvers, which traverse the entire game tree, as well as to approximate solvers such as Myopic and Monte Carlo Tree Search (MCTS). These techniques are assessed, and used to gain insights into both nonlinear dynamical systems and strategic decision making in adversarial environments. Crown Copyright (C) 2022 Published by Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
