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Including mixed and also air particle make any difference in a forecast tool with regard to ozonation regarding natural and organic micropollutants inside wastewater.
A system of two coupled map-based oscillators is studied. As units, we use identical logistic maps in two-periodic modes. In this system, increasing coupling strength significantly changes deterministic regimes of collective dynamics with coexisting periodic, quasiperiodic, and chaotic attractors. We study how random noise deforms these dynamical regimes in parameter zones of mono- and bistability, causes "order-chaos" transformations, and destroys regimes of in-phase and anti-phase synchronization. In the analytical study of these noise-induced phenomena, a stochastic sensitivity technique and a method of confidence domains for periodic and multi-band chaotic attractors are used. In this analysis, a key role of chaotic transients and geometry of "riddled" basins is revealed.After a brief introduction to the theory underlying block-entropy and its relation to the dynamics of complex systems as well as certain information theory aspects, we study musical texts coming from two distinct musical traditions, Japanese and Western European, encoded via symbolic dynamics. We quantify their information content, also known as the degree of "non-randomness" which essentially defines the complexity of the text. We analyze the departure of "total randomness" to the constraints underlying the dynamics of the symbol generating process. Following Shannon on his attribution of these constraints as the key factors of the emergence of complexity, we observe that it can be accurately assessed by the texts' block-entropy vs block-length scaling laws.Mathematical epidemiology that describes the complex dynamics on social networks has become increasingly popular. However, a few methods have tackled the problem of coupling network topology with complex incidence mechanisms. Here, we propose a simplicial susceptible-infected-recovered-susceptible (SIRS) model to investigate the epidemic spreading via combining the network higher-order structure with a nonlinear incidence rate. A network-based social system is reshaped to a simplicial complex, in which the spreading or infection occurs with nonlinear reinforcement characterized by the simplex dimensions. Compared with the previous simplicial susceptible-infected-susceptible (SIS) models, the proposed SIRS model can not only capture the discontinuous transition and the bistability of a complex system but also capture the periodic phenomenon of epidemic outbreaks. More significantly, the two thresholds associated with the bistable region and the critical value of the reinforcement factor are derived. We further analyze the stability of equilibrium points of the proposed model and obtain the condition of existence of the bistable states and limit cycles. this website This work expands the simplicial SIS models to SIRS models and sheds light on a novel perspective of combining the higher-order structure of complex systems with nonlinear incidence rates.Mono-silicon crystals, free of defects, are essential for the integrated circuit industry. Chaotic swing in the flexible shaft rotating-lifting (FSRL) system of the mono-silicon crystal puller causes harm to the quality of the crystal and must be suppressed in the crystal growth procedure. From the control system viewpoint, the constraints of the FSRL system can be summarized as not having measurable state variables for state feedback control, and only one parameter is available to be manipulated, namely, the rotation speed. From the application side, an additional constraint is that the control should affect the crystallization physical growth process as little as possible. These constraints make the chaos suppression in the FSRL system a challenging task. In this work, the analytical periodic solution of the swing in the FSRL system is derived using perturbation analysis. A bi-directional impulse control method is then proposed for suppressing chaos. This control method does not alter the average rotation speed. It is thus optimum regarding the crystallization process as compared with the single direction impulse control. The effectiveness and the robustness of the proposed chaos control method to parameter uncertainties are validated by the simulations.We analyze the existence of chaotic and regular dynamics, transient chaos phenomenon, and multistability in the parameter space of two electrically interacting FitzHugh-Nagumo (FHN) neurons. By using extensive numerical experiments to investigate the particular organization between periodic and chaotic domains in the parameter space, we obtained three important findings (i) there are self-organized generic stable periodic structures along specific directions immersed in a chaotic portion of the parameter space; (ii) the existence of transient chaos phenomenon is responsible for long chaotic temporal evolution preceding the asymptotic (periodic) dynamics for particular parametric combinations in the parameter space; and (iii) the existence of various multistable domains in the parameter space with an arbitrary number of attractors. Additionally, we also prove through numerical simulations that chaos, transient chaos, and multistability prevail even for different coupling strengths between identical FHN neurons. It is possible to find multistable attractors in the phase and parameter spaces and to steer them apart by increasing the asymmetry in the coupling force between neurons. Such a strategy can be essential to experimental matters, as setting the right parameter ranges. As the FHN model shares the crucial properties presented by the more realistic Hodgkin-Huxley-like neurons, our results can be extended to high-dimensional coupled neuron models.Writing a history of a scientific theory is always difficult because it requires to focus on some key contributors and to "reconstruct" some supposed influences. In the 1970s, a new way of performing science under the name "chaos" emerged, combining the mathematics from the nonlinear dynamical systems theory and numerical simulations. To provide a direct testimony of how contributors can be influenced by other scientists or works, we here collected some writings about the early times of a few contributors to chaos theory. The purpose is to exhibit the diversity in the paths and to bring some elements-which were never published-illustrating the atmosphere of this period. Some peculiarities of chaos theory are also discussed.The current definition of rate-induced tipping is tied to the idea of a pullback attractor limiting in forward and backward time to a stable quasi-static equilibrium. Here, we propose a new definition that encompasses the standard definition in the literature for certain scalar systems and includes previously excluded N-dimensional systems that exhibit rate-dependent critical transitions.We construct reduced order models for two classes of globally coupled multi-component oscillatory systems, selected as prototype models that exhibit synchronization. These are the Kuramoto model, considered both in its original formulation and with a suitable change of coordinates, and a model for the circadian clock. The systems of interest possess strong reduction properties, as their dynamics can be efficiently described with a low-dimensional set of coordinates. Specifically, the solution and selected quantities of interest are well approximated at the reduced level, and the reduced models recover the expected transition to synchronized states as the coupling strengths vary. Assuming that the interactions depend only on the averages of the system variables, the surrogate models ensure a significant computational speedup for large systems.Financial networks have been the object of intense quantitative analysis during the last few decades. Their structure and the dynamical processes on top of them are of utmost importance to understand the emergent collective behavior behind economic and financial crises. In this paper, we propose a stylized model to understand the "domino effect" of distress in client-supplier networks. We provide a theoretical analysis of the model, and we apply it to several synthetic networks and a real customer-supplier network, supplied by one of the largest banks in Europe. Besides, the proposed model allows us to investigate possible scenarios for the functioning of the financial distress propagation and to assess the economic health of the full network. The main novelty of this model is the combination of two stochastic terms an additive noise, accounting by the capability of trading and paying obligations, and a multiplicative noise representing the variations of the market. Both parameters are crucial to determining the maximum default probability and the diffusion process characteristics.We report the discovery of a regular lattice of exceptional quint points in a periodically driven oscillator, namely, in the frequency-amplitude control parameter space of a photochemically periodically perturbed ruthenium-catalyzed Belousov-Zhabotinsky reaction model. Quint points are singular boundary points where five distinct stable oscillatory phases coalesce. While spikes of the activator show a smooth and continuous variation, the spikes of the inhibitor show an intricate but regular branching into a myriad of stable phases that have fivefold contact points. Such boundary points form a wide parameter lattice as a function of the frequency and amplitude of light absorption. These findings revise current knowledge about the topology of the control parameter space of a celebrated prototypical example of an oscillating chemical reaction.It is the purpose of this paper to justify the use of modulation equations for pattern forming systems in the case of multiple Turing instabilities with critical wave numbers having a ratio 12 by proving approximation results, presenting attractivity results, and discussing the existence of modulating fronts.Identification of multiple influential spreaders on complex networks is of great significance, which can help us speed up information diffusion and prevent disease from spreading to some extent. The traditional top-k strategy to solve an influence maximization problem based on node centrality is unsuitable for selecting several spreaders simultaneously because of influence overlapping. Besides, other heuristic methods have a poor ability to keep the balance between efficiency and computing time. In this paper, an efficient method is proposed to identify the decentralized influential spreaders on networks by edge percolation under the Susceptible-Infected-Recovered (SIR) model. Thanks to the average size of the connected component where one node is located under the edge percolation equivalent to the final spread range of this node under the SIR model approximately, it inspires us to choose suitable spreaders maximize the spread of influence. The experimental results show that our method has high efficiency compared with other benchmark methods on three synthetic networks and six empirical networks, and it also requires less time and cost.Modern view of network resilience and epidemic spreading has been shaped by percolation tools from statistical physics, where nodes and edges are removed or immunized randomly from a large-scale network. In this paper, we produce a theoretical framework for studying targeted immunization in networks, where only n nodes can be observed at a time with the most connected one among them being immunized and the immunity it has acquired may be lost subject to a decay probability ρ. We examine analytically the percolation properties as well as scaling laws, which uncover distinctive characters for Erdős-Rényi and power-law networks in the two dimensions of n and ρ. We study both the case of a fixed immunity loss rate as well as an asymptotic total loss scenario, paving the way to further understand temporary immunity in complex percolation processes with limited knowledge.
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