Boettcher, StefanGago, Paula A.Sibani, Paolo
8页查看更多>>摘要：Cooperative events requiring a rare large fluctuation are a defining characteristic for the onset of glassy relaxation across many materials. The importance of such intermittent events has been noted in systems as diverse as superconductors, metallic glasses, gels, colloids, and granular piles. Here, we show that prohibiting the attainment of new record-high energy fluctuations - by explicitly imposing a "lid"on the fluctuation spectrum - impedes further relaxation in the glassy phase. This lid allows us to directly measure the impact of record events on the evolving system in extensive simulations of aging in such vastly distinct glass formers as spin glasses and tapped granular piles. Interpreting our results in terms of a dynamics of records succeeds in explaining the ubiquity of both, the logarithmic decay of the energy and the memory effects encoded in the scaling of two-time correlation functions of aging systems. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:
NSTL
Elsevier
Koverda, V. P.Skokov, V. N.
12页查看更多>>摘要：In a system of equations simulating of nonequilibrium phase transitions under external periodic action, chaotic regimes with the onset of strange attractors are found. The region of chaotic behavior in the coordinates of the frequency and amplitude of the periodic action is determined. Critical transitions of a merging between attractors are found, which are characterized by low-frequency 1/f behavior of power spectra and power-law distributions of amplitudes. Outside the chaotic region, the additional effect of white noise on the system leads to noise-induced dynamical chaos. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Ding, HengQian, YuZheng, XiaoyanBai, Haijian...
21页查看更多>>摘要：Homogeneous traffic density is the precondition of macroscopic fundamental diagrams (MFDs) that exist in a regional road network. However, traffic density may be transformed by the effects of traffic flow transmission and parking generation in a dynamic system. Once the homogeneous and uniform traffic density is changed, the shape of the MFD curve is likely affected, and thus, the output efficiency of the road network decreases. Based on the existing research of the aggregation evaluation model of parking generation in a regional road network, the study analyses the relationship between the variation in parking generation aggregation and the variation ratio in the trip completion flow of the network through further analysis. On this basis, a dynamic parking charge-perimeter control coupled (DPCPCC) method in a macro road network is proposed to balance the traffic flow density in a dynamically congested sub-region that exists in multiple public parking lots and to improve the efficiency of traffic flow for the entire road network. Furthermore, the method optimizes the entire parking charge rate of each MFD sub-region, aiming for the lowest generalized cost, reduces the delay time of the road network by adjusting the perimeter control rate, and changes the traffic aggregation index by dynamic charging strategies to improve the congested sub-region outflow efficiency. Finally, the regional road network in the Binhu New District of Hefei is taken as an example, and three control scenarios consisting of the DPCPCC method, the static parking charge-perimeter control coupled (SPCPCC) method, and the proportional-integral (PI) method are analysed and compared. According to the analysis of the relationship between the parking generation aggregation index and MFD changes and the application of this relationship to verify the regional road network dynamic charging model, the results reveal that the DPCPCC method can reduce the marginal social cost and improve the operation efficiency of the road network compared with the SPCPCC and PI control methods. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Lu, XinbiaoZhang, ChiQin, Buzhi
9页查看更多>>摘要：In the original Vicsek model, the motion direction of a particle is updated according to its all neighbors' mean direction. However, the convergence speed of the system is usually low due to the too many interacting particles, which is especially true when the particle densities are high. Therefore, a new rule is proposed to make the motion direction of all particles reach consensus more quickly. The Euclidean distances between its neighbors and the particle are arranged from far to near, and we only take the average direction of the farthest part neighbors as the motion direction of the particle at the next moment, which replace the original Vicsek model. The simulation results demonstrate that the improved Vicsek model has faster convergence speed than the original Vicsek model under different particle number and different system parameters. Furthermore, the convergence speed will reach the fastest with an appropriate number of neighbors according to the new rule, and the improved model is much easier to obtain consensus even for the noise disturbance. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Leng, HuiZhao, YiWang, Dong
12页查看更多>>摘要：In social contagions, an individual to trust the behavioral information transmitted by neighbors depends on the level of the social status of neighbors as well as the closeness degree with neighbors. From the view of network topology, we propose the trust probability with multiple influence factors: node degree and the number of common neighbors. Furthermore, a weight factor is set to adjust the influence extent of the above two factors. As a result, in the context of the trust probability, we investigate social contagions with focus on social reinforcement and memory effect on networks, which are modeled by the threshold model. The message passing approach is adopted so as to formulate the state evolution of each node on the basis of network topology. Through extensive numerical simulations, we find that the trust probability can suppress social contagions, so does increasing the trust probability gap. Notably, the number of common neighbors as an influence factor of the trust probability is able to increase the final behavior adoption size, while node degree takes the opposite effect. The theoretical results are confirmed to agree well with the numerical results by the Monte Carlo method. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Shang, RonghuaZhang, WeitongZhang, JingwenFeng, Jie...
15页查看更多>>摘要：Local community detection is to discover local community where the seed is located. Most algorithms extend local community by edge information, without considering high-order information in network. The high-order information which is also named as network motif is very important for forming a community. There are also methods that focus on higher-order structure but ignore the sparsely connected edges, resulting in that fail to extend some edge points. In addition, when the seed is the edge node, how to choose the first node to integrate into the community will determine whether the community expands in a right direction. Therefore, a local community detection algorithm based on higher-order structure and edge information (HSEI) is proposed. Firstly, different ways selecting the first node joining local community according to the motif degree of seed are used. Secondly, a new motif-based modularity function is proposed to extend local community, so that the extended community will be connected more tightly. A new motif-based community central node is defined to help extend the central part of local community. For the edge of community and the area with sparse connections, edge information is used to mine the membership strength between nodes and communities, so as to obtain more complete local community members. Compared with five state-of-the-art algorithms, the proposed method achieves better results on the generated networks with different parameters and six real networks. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Thomas, Gilberto L.Fortuna, IsmaelPerrone, Gabriel C.Graner, Francois...
12页查看更多>>摘要：Cell migration plays essential roles in development, wound healing, diseases, and in the maintenance of a complex body. Experiments in collective cell migration generally measure quantities such as cell displacement and velocity. The observed short-time diffusion regime for mean square displacement in single-cell migration experiments on flat surfaces calls into question the definition of cell velocity and the measurement protocol. Theoretical results in stochastic modeling for single-cell migration have shown that this fast diffusive regime is explained by a white noise acting on displacement on the direction perpendicular to the migrating cell polarization axis (not on velocity). The prediction is that only the component of velocity parallel to the polarization axis is a well-defined quantity, with a robust measurement protocol. Here, we ask whether we can find a definition of a migrating-cell polarization that is able to predict the cell's subsequent displacement, based on measurements of its shape. Supported by experimental evidence that cell nucleus lags behind the cell center of mass in a migrating cell, we propose a robust parametrization for cell migration where the distance between cell nucleus and the cell's center of mass defines cell shape polarization. We tested the proposed methods by applying to a simulation model for three-dimensional cells performed in the CompuCell3D environment, previously shown to reproduce biological cells kinematics migrating on a flat surface. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Fang, WeiweiZhuo, WenhaoYan, JingwenSong, Youyi...
14页查看更多>>摘要：Accurate forecasting of future traffic flow has a wide range of applications, which is a fundamental component of intelligent transportation systems. However, timely and accurate traffic forecasting remains an open challenge due to the high nonlinearity and volatility of traffic flow data. Canonical long short-term memory (LSTM) networks are easily drawn to focus on min-to-min fluctuations rather than the long term dependencies of the traffic flow evolution. To address this issue, we propose to introduce an attention mechanism to the long short-term memory network for short-term traffic flow forecasting. The attention mechanism helps the network model to assign different weights to different inputs, focus on critical and important information, and make accurate predictions. Extensive experiments on four benchmark data sets show that the LSTM network equipped with an attention mechanism has superior performance compared with commonly used and state-of-the-art models. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Huang, DifangWu, BoyaoChen, MuziLi, Nan...
18页查看更多>>摘要：The connectivity of stock markets reflects the information efficiency of capital markets and contributes to interior risk contagion and spillover effects. We compare Shanghai Stock Exchange A-shares (SSE A-shares) during tranquil periods, with high leverage periods associated with the 2015 subprime mortgage crisis. We use Pearson correlations of returns, the maximum strongly connected subgraph, and 3 sigma - principle to iteratively determine the threshold value for building a dynamic correlation network of SSE A-shares. Analyses are carried out based on the networking structure, intra-sector connectivity, and node status, identifying several contributions. First, compared with tranquil periods, the SSE A-shares network experiences a more significant small-world and connective effect during the subprime mortgage crisis and the high leverage period in 2015. Second, the finance, energy and utilities sectors have a stronger intra-industry connectivity than other sectors. Third, HUB nodes drive the growth of the SSE A-shares market during bull periods, while stocks have a think-tail degree distribution in bear periods and show distinct characteristics in terms of market value and finance. Granger linear and non-linear causality networks are also considered for the comparison purpose. Studies on the evolution of inter-cycle connectivity in the SSE A-share market may help investors improve portfolios and develop more robust risk management policies. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
