The source of the gravitational-wave (GW) signal GW170817, very likely a binary neutron star merger, was also observed electromagnetically, providing the first multi-messenger observations of this type. The two-week-long electromagnetic (EM) counterpart had a signature indicative of an r-process-induced optical transient known as a kilonova. This Letter examines how the mass of the dynamical ej...

Introduction: In this paper, a novel complexity measure is proposed to detect dynamical changes in nonlinear systems using ordinal pattern analysis of time series data taken from the system. Epilepsy is considered as a dynamical change in nonlinear and complex brain system. The ability of the proposed measure for characterizing the normal and epileptic EEG signals when the signal is short or is...

A new Chemo–Dynamical Smoothed Particle Hydrodynamic (CD-SPH) code is presented. The disk galaxy is described as a multi–fragmented gas and star system, embedded in a cold dark matter halo with a rigid potential field. The star formation (SF) process, SNII, SNIa and PN events, and the chemical enrichment of gas, have all been considered within the framework of the standard SPH model, which we u...

We investigate experimentally the connection between short time dynamics and long time dynamical heterogeneities within a dense granular media under cyclic shear. We show that dynamical heterogeneities result from a two time scales process. Short time but already collective events consisting in clustered cage jumps concentrate most of the nonaffine displacements. On larger time scales, such clu...

Defining the importance of nodes in a complex network has been a fundamental problem in analyzing the structural organization of a network, as well as the dynamical processes on it. Traditionally, the measures of node importance usually depend either on the local neighborhood or global properties of a network. Many real-world networks, however, demonstrate finely detailed structure at various o...

Business processes are mostly very complex and take place in a dynamic and distributed field. Information technology support for these processes requires an advanced process management system which enhances currently available workflow management services with respect to integration, flexibility, and adaptation. In order to apply intelligent agent technologies to process management two differen...

Rich and complex time-series data, such as those generated from engineering systems, financial markets, videos or neural recordings, are now a common feature of modern data analysis. Explaining the phenomena underlying these diverse data sets requires flexible and accurate models. In this paper, we promote Gaussian process dynamical systems (GPDS) as a rich model class that is appropriate for s...

Dynamical Systems (DS) for robot motion modeling are well-suited for efficient robot learning and control. Our focus in this extended abstract is on autonomous dynamical systems, which represent a motion plan completely without dependency on time. We develop a method that allows to locally reshape an existing, stable autonomous DS without risking introduction of additional equilibrium points or...

Process modeling languages such as "Dynamical Grammars" are highly expressive in the processes they model using stochastic and deterministic dynamical systems, and can be given formal semantics in terms of an operator algebra. However such process languages may be more limited in the types of objects whose dynamics is easily expressible. For many applications in biology, the dynamics of spatial...