Yao, ChengguiXu, FeiShuai, JianweiLi, Xiang...
11页查看更多>>摘要：The environmental temperature plays a critical role in the system functioning. In biological organisms, there often exists an optimal temperature for the most effective functions. In this work, we investigate the effect of temperature on the propagation of firing rate in a feed-forward multilayer neural network in which neurons in the first layer are stimulated by stochastic noises. We then show that the firing rate can be transmitted through the network within a temperature range. We also show that the propagation of the firing rate by synchronization is optimized at an appropriate temperature. Our findings provide new insights and improve our understanding of the optimal temperature observed in the experiments in the living biological systems. (c) 2022 Elsevier B.V. All rights reserved.
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Elsevier
Picoli, SergioBombo, GiorgioSantos, Edenize S. D.Depra, Pedro P....
10页查看更多>>摘要：Center of pressure (COP) signals have been widely used to investigate various aspects of human balance during quiet standing. Here, we compute a set of measures - including burstiness, memory and local variation - to quantify temporal patterns in COP zero-crossings. Specifically, we investigate the effect of stance type (bipedal and unipedal) on the proposed measures. Data were obtained from a group of 20 health and young subjects. The results suggest that these measures are able to detect differences in zero-crossing patterns between bipedal and unipedal stance. We also perform a test-retest reliability analysis for each measure and a pairwise correlation analysis for combinations of measures. Finally, we discuss some potential implications of our results for the study of human balance. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Xie, LingyunWei, BoXiao, Feng
10页查看更多>>摘要：In recent years, explosive synchronization (ES) has attracted extensive interest due to its great significance in the study of epileptic seizures and cascading failures in the real world. In this paper, a weighting method based on the frequency mismatches and distances between linked oscillators is proposed to construct a Kuramoto-like model to study ES of mobile oscillators. An interesting phenomenon that the weighting of oscillators can induce a sudden and irreversible synchronization transition with hysteresis loop is revealed. The transition between continuous synchronization and ES can be tuned by the weighting factors. Moreover, it is found that the critical coupling strength and hysteresis loop width are affected by the initial frequency distribution, the number of oscillators, the communication radius, the setting of boundary conditions and the constant absolute velocity of oscillators. (C)2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Xiong, Chong-WeiTang, MingWang, Xiao-HuaShi, Jia...
10页查看更多>>摘要：The complex network theory is helpful to design the self-organizing evolution mechanism of the network and generate wireless sensor networks (WSNs) with high quality of service. Focusing on the heterogeneous WSNs, we firstly propose an evolution model based on the fitness model in complex network and then propose two self-organizing evolution models based on the topology hops for heterogeneous WSNs. By considering the topology hops in the self-organizing evolution mechanism, the two models can effectively reduce the reverse connection and balance the load of nodes around the sink in network evolution process. Simulation results show that compared with three classical models, the proposed models provide a higher quality of service, such as longer network lifetime, better energy-balanced factor, shorter shortest path length and stronger robustness against malicious attacks. Our self-organizing evolution models provide a new perspective and reference for the design of heterogeneous WSNs with high quality of service. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Bezerra Martins, Francisco Leonardodo Nascimento, Jose Claudio
11页查看更多>>摘要：Several populational networks present complex topologies when implemented in evolutionary algorithms. A common feature of these topologies is the emergence of a power law. Power law behavior with different scaling factors can also be observed in genealogical networks, but we still cannot satisfactorily describe its dynamics or its relation to population evolution over time. In this paper, we use an algorithm to measure the impact of individuals in several numerical populations and study its dynamics of evolution through nonextensive statistics. Like this, we show evidence that the observed emergence of power law has a dynamic behavior over time. This dynamic development can be described using a family of q-exponential distributions whose parameters are time-dependent and follow a specific pattern. We also show evidence that elitism significantly influences the power law scaling factors observed. These results imply that the different power law shapes and deviations observed in genealogical networks are static images of a time-dependent dynamic development that can be satisfactorily described using q-exponential distributions. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Li, XianghuaDeng, YueYuan, XuesongWang, Zhen...
11页查看更多>>摘要：The mobile phone data have become crucial in behavioral analysis to detect habits of human mobility and reveal rules of behaviors. Previously, questionnaires were often used to identify urban functional areas, with vast labor and poor timeliness. To address the issue, this paper applies data-driven behavioral analysis to identify functional areas for governments to construct urban design, offer site selection and manage transportation. Moreover, data-driven behavioral analysis can also be applied in student behaviors to help schools adjust facility arrangements, develop learning efficiency and provide high-quality services. Therefore, based on mobile phone data in Changchun, this paper utilizes a two-stage clustering method combining human mobility to identify urban functional areas, including business, working, residential and low passenger-flow areas. The interesting finding is that local prosperity in Changchun is prominent and the proportion of low passenger-flow areas can reflect the development level. Furthermore, this paper compares student behaviors in three schools, which shows each school varies in distribution features of students. Experiments provide enlightening insights to reveal the spatial structure of cities and comprehend the living state of students.(c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Pelen, Neslihan NesliyeGolgeli, Meltem
16页查看更多>>摘要：During disasters and emergencies (earthquakes, pandemics, economic crises etc.), we also face a second challenge, pollution of information. The transmitted information may be false, potentially harmful and speculative. Today, the main source of information seems to be the social media, which behaves as a vector via sharing news. In this manuscript, the concept of the transmission dynamics of vector-borne diseases is adapted to the transmission dynamics of vector-borne disinformation. The dynamical behavior of the model is analyzed, the disinformation-free and disinformation endemic equilibria of the model are found and both their local and global stabilities are presented. Finally, numerical simulations are carried out to support the analytical results of the dynamical transmission of disinformation.(C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Shen, YaoZhou, Chi-ChunChen, Yu-Zhu
11页查看更多>>摘要：In this paper, we show that the elementary excitations of interacting spin lattice models, such as the Ising models, the Heisenberg models and the abelian Kitaev anyons, can be regarded as the quasiparticles of Gentile statistics. The advantage of the quasiparticle viewpoint is that eigenvalues and eigenstates of these models can be directly obtained by creating and annihilating Gentile quasiparticles. We provide the eigenstates and eigenvalues of d-dimensional Ising model with periodic boundary conditions. We also provide the eigenvalues of the Heisenberg models, the abelian Kitaev anyons, 2-dimensional and 3-dimensional general spin lattice models. In addition, we point out that one kind of next nearest neighbor interacting models and more general interacting model may correspond to several kinds of quasiparticles of Gentile statistics. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Hajirahimi, ZahraKhashei, Mehdi
20页查看更多>>摘要：Accurate forecasting of real-world systems becomes a highly challenging task due to the inherent complexity of time series modeling. Hybrid models have been successfully applied to deal with such problems and yield desired forecasting accuracy. The fundamental objective of hybridization is to exploit the unit modeling benefits of every single model and lift its disadvantages. For reaching these goals, individual models are combined in two main parallel and series frameworks. The parallel hybridization method relied on employing different individual models and integrated the weighted forecasts to capture the advantages contained in all models, concurrently. However, existing parallel hybrid models suffer from some crucial shortcomings that need to be addressed and eliminated. One of the critical deficiencies of parallel models is that the residual obtained by different models is not modeled, and the unprocessed patterns have remained in the data. The principal goal of this paper is to alleviate this deficiency of parallel hybrid models using the capability of the series hybridization strategy in modeling remaining patterns in residuals. Thus, the key innovation of this study is to combine parallel hybrid models employing a series hybridization scheme to yield an enhanced forecasting model and overcome the drawback of the parallel models. Despite the vast hybrid models proposed for combining individual models, this paper aims to combine both the above mentioned hybrid structures instead of individual models. For this purpose, the novel hybrid model named Series Hybridization of Parallel (SHOP) model is proposed, which integrates a parallel hybrid model by series hybridization approach. In this research, Autoregressive Integrated Moving Average (ARIMA) and Multilayer perceptrons (MLP) models are used to implement the proposed hybrid SHOP structure. In this way, the SHOP contains a series hybridization of parallel hybridization of ARIMA and MLP models. The effectiveness of the SHOP model is verified by applying it to four benchmark data sets, including the closing of the DAX index, the closing of the Nikkei 225 index (N225), the opening of the Dow Jones Industrial Average Index (DJIAI), and the wind speed data in Colorado State. The predictive power of the SHOP model is evaluated by comparing the obtained results with ARIMA, MLP, LSTM, RBFNN, SVM, and traditional series and parallel hybridization of ARIMA and MLP models. Remarkably, the obtained forecasting accuracy from the SHOP model is outstanding than other models. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Lima, P. M.Erlhagen, W.Kulikova, M., VKulikov, G. Yu...
20页查看更多>>摘要：The main goal of the present work is to investigate the effect of noise in some neural fields, used to simulate working memory processes. The underlying mathematical model is a stochastic integro-differential equation. In order to approximate this equation we apply a numerical scheme which uses the Galerkin method for the space discretization. In this way we obtain a system of stochastic differential equations, which are then approximated in two different ways, using the Euler-Maruyama and the Ito-Taylor methods. We apply this numerical scheme to explain how a population of cortical neurons may encode in its firing pattern simultaneously the nature and time of sequential stimulus events. Numerical examples are presented and their results are discussed. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
