e., Turing or wave instability), while its complementary subsystem can also be unstable. https://www.selleckchem.com/products/ms-275.html (3) It is shown that the presence of an immobile unstable subsystem, which leads to destabilization of waves within an infinite range of wavenumbers, in a spatially discrete case can result in the generation of large-scale stationary or oscillatory patterns. (4) It is demonstrated that under the presence of subcritical Turing and supercritical wave bifurcations, the interaction of two diffusion instabilities can result in the spontaneous formation of Turing structures outside the region of Turing instability.We show how to couple phase-oscillators on a graph so that collective dynamics "searches" for the coloring of that graph as it relaxes toward the dynamical equilibrium. This translates a combinatorial optimization problem (graph coloring) into a functional optimization problem (finding and evaluating the global minimum of dynamical non-equilibrium potential, done by the natural system's evolution). Using a sample of graphs, we show that our method can serve as a viable alternative to the traditional combinatorial algorithms. Moreover, we show that, with the same computational cost, our method efficiently solves the harder problem of improper coloring of weighed graphs.Global organization of three-dimensional (3D) Lagrangian chaotic transport is difficult to infer without extensive computation. For 3D time-periodic flows with one invariant, we show how constraints on deformation that arise from volume-preservation and periodic lines result in resonant degenerate points that periodically have zero net deformation. These points organize all Lagrangian transport in such flows through coordination of lower-order and higher-order periodic lines and prefigure unique transport structures that arise after perturbation and breaking of the invariant. Degenerate points of periodic lines and the extended 3D structures associated with them are easily identified through the trace of the deformation tensor calculated along periodic lines. These results reveal the importance of degenerate points in understanding transport in one-invariant fluid flows.Acute myocardial ischemia is an imbalance between myocardial blood supply and demand, which is caused by the cessation of blood flow within the heart resulting from an obstruction in one of the major coronary arteries. A severe blockage may result in a region of nonperfused tissue known as ischemic core (IC). As a result, a border zone (BZ) between perfused and nonperfused regions is created due to differences in blood and oxygen supplies. Recent experimental findings reveal a complex "finger-like" geometry in BZ; however, its effect on arrhythmogenicity is not clear. Ephaptic coupling, which relies on the intercalated disk between cell ends, has been suggested to play an active role in mediating intercellular electrical communication when gap junctions are impaired. In this paper, we explored the interplay between ephaptic coupling and the geometry of BZ on action potential propagation across the ischemic region. Our study shows that ephaptic coupling can greatly suppress the occurrence of a conduction block, which points to its beneficial effect. The beneficial effect of ephaptic coupling is more evident in BZ with the "finger-like" geometry. In addition, the complex geometry of BZ, i.e., more frequent, deeper, and wider "fingers," promotes the conduction through the ischemic region. In contrast, the larger size of IC impedes the cardiac conduction across the ischemic region. Our results also show that ephaptic coupling promotes the impact of the complex geometry of BZ on signal propagation; however, it inhibits the impact of IC size.This paper reports a generic method for constructing n-fold covers of 3D conservative chaotic systems, which is derived from the theory of the generalized Hamiltonian system. Three typical example systems are constructed based on the proposed method, and their different n-fold cover chaotic flows are investigated theoretically and numerically. For each example system, the motion trajectories are both conservative and chaotic, which can be verified by the Lyapunov exponents, and it is interesting to find that the emergence of n-fold cover conservative chaos mainly relays on the corresponding Hamiltonian. Numerical results show that the proposed generic method is effective to construct n-fold covers of 3D conservative chaotic systems, such as a 3-fold cover in the direction of the y-axis, 2×3-fold cover on the x-y plane, and 2×3×2-fold cover in the 3D phase space. This study also demonstrates that based on appropriate skew-symmetric nonconstant matrices, the n-fold cover conservative chaos can be obtained by changing the Hamiltonian.We introduce "state space persistence analysis" for deducing the symbolic dynamics of time series data obtained from high-dimensional chaotic attractors. To this end, we adapt a topological data analysis technique known as persistent homology for the characterization of state space projections of chaotic trajectories and periodic orbits. By comparing the shapes along a chaotic trajectory to those of the periodic orbits, state space persistence analysis quantifies the shape similarity of chaotic trajectory segments and periodic orbits. We demonstrate the method by applying it to the three-dimensional Rössler system and a 30-dimensional discretization of the Kuramoto-Sivashinsky partial differential equation in (1+1) dimensions.A catastrophic bifurcation in non-linear dynamical systems, called crisis, often leads to their convergence to an undesirable non-chaotic state after some initial chaotic transients. Preventing such behavior has been quite challenging. We demonstrate that deep Reinforcement Learning (RL) is able to restore chaos in a transiently chaotic regime of the Lorenz system of equations. Without requiring any a priori knowledge of the underlying dynamics of the governing equations, the RL agent discovers an effective strategy for perturbing the parameters of the Lorenz system such that the chaotic trajectory is sustained. We analyze the agent's autonomous control-decisions and identify and implement a simple control-law that successfully restores chaos in the Lorenz system. Our results demonstrate the utility of using deep RL for controlling the occurrence of catastrophes in non-linear dynamical systems.