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DDC: 530 × Version: publishedVersion × search.filters.applied.f.series: Scientific Reports 7 (2017), Nr. 1 ×

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    Sample-based approach can outperform the classical dynamical analysis - Experimental confirmation of the basin stability method
    (London : Nature Publishing Group, 2017) Brzeski, P.; Wojewoda, J.; Kapitaniak, T.; Kurths, J.; Perlikowski, P.
    In this paper we show the first broad experimental confirmation of the basin stability approach. The basin stability is one of the sample-based approach methods for analysis of the complex, multidimensional dynamical systems. We show that investigated method is a reliable tool for the analysis of dynamical systems and we prove that it has a significant advantages which make it appropriate for many applications in which classical analysis methods are difficult to apply. We study theoretically and experimentally the dynamics of a forced double pendulum. We examine the ranges of stability for nine different solutions of the system in a two parameter space, namely the amplitude and the frequency of excitation. We apply the path-following and the extended basin stability methods (Brzeski et al., Meccanica 51(11), 2016) and we verify obtained theoretical results in experimental investigations. Comparison of the presented results show that the sample-based approach offers comparable precision to the classical method of analysis. However, it is much simpler to apply and can be used despite the type of dynamical system and its dimensions. Moreover, the sample-based approach has some unique advantages and can be applied without the precise knowledge of parameter values.
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    Reconstruction of Complex Network based on the Noise via QR Decomposition and Compressed Sensing
    (London : Nature Publishing Group, 2017) Li, L.; Xu, D.; Peng, H.; Kurths, J.; Yang, Y.
    It is generally known that the states of network nodes are stable and have strong correlations in a linear network system. We find that without the control input, the method of compressed sensing can not succeed in reconstructing complex networks in which the states of nodes are generated through the linear network system. However, noise can drive the dynamics between nodes to break the stability of the system state. Therefore, a new method integrating QR decomposition and compressed sensing is proposed to solve the reconstruction problem of complex networks under the assistance of the input noise. The state matrix of the system is decomposed by QR decomposition. We construct the measurement matrix with the aid of Gaussian noise so that the sparse input matrix can be reconstructed by compressed sensing. We also discover that noise can build a bridge between the dynamics and the topological structure. Experiments are presented to show that the proposed method is more accurate and more efficient to reconstruct four model networks and six real networks by the comparisons between the proposed method and only compressed sensing. In addition, the proposed method can reconstruct not only the sparse complex networks, but also the dense complex networks.
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    Programing stimuli-responsiveness of gelatin with electron beams: Basic effects and development of a hydration-controlled biocompatible demonstrator
    (London : Nature Publishing Group, 2017) Riedel, Stefanie; Heyart, Benedikt; Apel, Katharina S.; Mayr, Stefan G.
    Biomimetic materials with programmable stimuli responsiveness constitute a highly attractive material class for building bioactuators, sensors and active control elements in future biomedical applications. With this background, we demonstrate how energetic electron beams can be utilized to construct tailored stimuli responsive actuators for biomedical applications. Composed of collagen-derived gelatin, they reveal a mechanical response to hydration and changes in pH-value and ion concentration, while maintaining their excellent biocompatibility and biodegradability. While this is explicitly demonstrated by systematic characterizing an electron-beam synthesized gelatin-based actuator of cantilever geometry, the underlying materials processes are also discussed, based on the fundamental physical and chemical principles. When applied within classical electron beam lithography systems, these findings pave the way for a novel class of highly versatile integrated bioactuators from micro-to macroscales.