Juergen Kurths

Potsdam Institute for Climate Impact Research | PIK · Transdisciplinary Concepts and Methods - Research Domain IV

This paper investigates the pinning asymptotic stabilization of Probabilistic Boolean Networks (PBNs) by a digraph approach. In order to stabilize the PBN asymptotically, a Mode-Independent Pinning Control (MIPC) is designed to make the target state a fixed point, and transform the state transition digraph into one that has a spanning branching roo...

Propagation delay arises in a coupling channel due to the finite propagation speed of signals and the dispersive nature of the channel. In this paper we study effects of propagation delay that appears in the indirect coupling path of direct (diffusive)-indirect (environmental) coupled oscillators. In sharp contrast to the direct coupled oscillators...

Here, we demonstrate the therapeutic effects of transcranial photobiomodulation (tPBM, 1267 nm, 32 J/cm², a 9-day course) in mice with the injected model of Alzheimer’s disease (AD) associated with accumulation of beta-amyloid (Aβ) in the brain resulting in neurocognitive deficit vs. the control group (CG) (the neurological severity score (NNS), AD...

The blood-brain barrier (BBB) poses a significant challenge for drug delivery to the brain. The limitations of our knowledge about the nature of BBB explain the slow progress in the therapy of brain diseases and absence of methods for drug delivery to the brain in clinical practice. Here, we show that the BBB opens for high-molecular-weight compoun...

We study changes in the blood–brain barrier (BBB) permeability in mice caused by a 2-h intermittent sound and discuss their reflection in the electrical activity of the brain. Using the detrended fluctuation analysis (DFA), multiresolution wavelet analysis (MWA) and their recent modifications, we compare the capabilities of reliably characterizing...

We performed a scientometric analysis of Chaos papers from 1991 to 2019, applying a careful disambiguation process for identifying the authors correctly. First, we used standard scientometric tools based on descriptive statistics. This analysis enabled us to compute productivity and the degree of collaboration. The evolution in the number of author...

Multiresolution wavelet analysis (MWA) is a powerful data processing tool that provides a characterization of complex signals over multiple time scales. Typically, the standard deviations of wavelet coefficients are computed depending on the resolution level and such quantities are used as measures for diagnosing different types of system behavior....

The spatio-temporal patterns of precipitation are of considerable relevance in the context of understanding the underlying mechanism of climate phenomena. The application of the complex network paradigm as a data-driven technique for the investigation of the climate system has contributed significantly to identifying the key regions influencing the...

Tropical cyclones (TCs) are one of the most destructive natural hazards that pose a serious threat to society around the globe, particularly to those in the coastal regions. In this work, we study the temporal evolution of the regional weather conditions in relation to the occurrence of TCs using climate networks. Climate networks encode the intera...

In actual network transmission, data loss due to network congestion and power shortage is unavoidable. However, this phenomenon has not been considered in Boolean networks (BNs) analysis so far. The loss of data are usually random, so BNs with missing data is modeled by introducing Bernoulli distribution sequences. A novel augmented system is const...

The IUTAM Symposium on Data-driven nonlinear and stochastic dynamics with the control will be held in Xi’an from 6 to 10 June 2022. The symposium focuses on data-driven problems combining complex systems science, machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern me...

Extended detrended fluctuation analysis (EDFA) is a recently proposed modification of the conventional method, which provides a characterization of complex time series with varying nonstationarity. It evaluates two scaling exponents for a better quantification of inhomogeneous datasets. Here, we study the effect of different types of nonstationarit...

In real systems, the unpredictable jump changes of the random environment can induce the critical transitions (CTs) between two non-adjacent states, which are more catastrophic. Taking an asymmetric Lévy-noise-induced tri-stable model with desirable, sub-desirable, and undesirable states as a prototype class of real systems, a prediction of the noi...

Music plays a more important role in our life than just being an entertainment. For example, it can be used as an anti-anxiety therapy of human and animals. However, the unsafe listening of loud music triggers hearing loss in millions of young people and professional musicians (rock, jazz and symphony orchestra) owing to exposure to damaging sound...

Self-organization is the spontaneous formation of spatial, temporal, or spatiotemporal patterns in complex systems far from equilibrium. During such self-organization, energy distributed in a broadband of frequencies gets condensed into a dominant mode, analogous to a condensation phenomenon. We call this phenomenon spectral condensation and study...

Music plays a more important role in our life than just being an entertainment. It is an even anti-anxiety therapy of human and animals. However, the unsafe listening of loud music triggers hearing loss in millions of young people and professional musicians (rock, jazz, and symphony orchestra) due to exposure to damaging levels of sound using perso...

We discuss the problem of revealing structural changes in rat electroencephalograms (EEG) caused by activation of the brain lymphatic drainage function due to a sound-induced stress. For this purpose, we apply the detrended fluctuation analysis (DFA) with its extended version to characterize long-range power-law correlations associated with the slo...

Detrended fluctuation analysis (DFA) is widely used to characterize long-range power-law correlations in complex signals. However, it has restrictions when nonstationarity is not limited only to slow variations in the mean value. To improve the characterization of inhomogeneous datasets, we have proposed the extended DFA (EDFA), which is a modifica...

Self-organization driven by feedback between subsystems is ubiquitous in turbulent fluid mechanical systems. This self-organization manifests as emergence of oscillatory instabilities and is often studied in different system-specific frameworks. We uncover the existence of a universal scaling behaviour during self-organization in turbulent flows le...

We study scaling features in the reactions of cereral blood vessel network to sudden “jumps” in peripheral arterial pressure in rats. Using laser speckle contrast imaging (LSCI) to measure the relative velocity of cerebral blood flow (CBF) and detrended fluctuation analysis (DFA) for processing experimental data, we investigate distinctions in the...

This seems to be the time to gain new knowledge about the meningeal lymphatic system and a deeper understanding of its anatomy and physiology. Although it is known that the meningeal lymphatics present in the layers of the brain, limited information is available about the role of this system in brain function. Here, for the first time we clearly de...

Synchronization and chimera are examples of collective behavior observed in an ensemble of coupled nonlinear oscillators. Recent studies have focused on their discovery in systems with least possible number of oscillators. Here we present an experimental study revealing the synchronization route to weak chimera via quenching, clustering, and chimer...

ABSTRACT Mean-field diffusive coupling was known to induce the phenomenon of quenching of oscillations even in identical systems, where the standard diffusive coupling (without mean-field) fails to do so [Phys. Rev. E 89, 052912 (2014)]. In particular, the mean-field diffusive coupling facilitates the transition from amplitude to oscillation death...

The influences of correlated spatially random perturbations (SRPs) on the first passage problem are studied in a linear-cubic potential with a time-changing external force driven by a Gaussian white noise. First, the escape rate in the absence of SRPs is obtained by Kramers' theory. For the random potential case, we simplify the escape rate by mult...

We study the problem of recognizing specific oscillatory patterns in multichannel electroencephalograms (EEGs) of untrained volunteers arising during various types of movements and mental intentions that are associated with motor functions. To distinguish between the related patterns, we perform a multiresolution analysis based on discrete wavelet...

Epileptic seizures are associated with excessively high synchronous activities of neocortex regions or other neural populations. Traub and Wong showed that synchronized bursts appear in epileptic seizures depend on the neural dynamics. Two suggested mechanisms responsible for the generation of partial epilepsy are the decrease of inhibition and inc...

Frequent and intense rainfall events demand innovative techniques to better predict the extreme rainfall dynamics. This task requires essentially the assessment of the basic types of atmospheric processes that trigger extreme rainfall, and then to examine the differences between those processes, which may help to identify key patterns to improve pr...

Figures and technical details

Currently, causes of the middle Pleistocene transition (MPT) – the onset of large-amplitude glacial variability with 100 kyr time scale instead of regular 41 kyr cycles before – are a challenging puzzle in Paleoclimatology. Here we show how a Bayesian data analysis based on machine learning approaches can help to reveal the main mechanisms underlyi...

Until now, cause of the Mid-Pleistocene Transition (MPT), when the dominant periodicity of climate cycles changed from 41,000 to 100,000 years in the absence of significant change in orbital forcing, are still an open question in Paleoclimatology. Here we show how a Bayesian data analysis and nonlinear dynamical reconstruction methods can help to r...

We study the impact of noise on the rate dependent transitions in a noisy bistable oscillator using a thermoacoustic system as an example. As the parameter—the heater power—is increased in a quasi-steady manner, beyond a critical value, the thermoacoustic system undergoes a subcritical Hopf bifurcation and exhibits periodic oscillations. We observe...

A new data-driven model for analysis and prediction of spatially distributed time series is proposed. The model is based on a linear dynamical mode (LDM) decomposition of the observed data which is derived from a recently developed nonlinear dimensionality reduction approach. The key point of this approach is its ability to take into account simple...

In our previous data we observed the presence of products of degraded blood (the iron/hemosiderin) in the meningeal lymphatics (ML) and in the deep cervical lymph node (dcLN) in patients who died after hemorrhagic events (brain trauma and stroke). Here we demonstrate novel data related to the brain clearance from the blood after hemorrhagic stroke...

Albeit synchronous behavior of some fireflies species is one of the paradigmatic examples of synchronization, there are not many efforts to model in a realistic way this astounding phenomenon. One of the most important features of fireflies synchronization is the cooperative behavior of many fireflies giving rise to the emergency of synchronization...

Climate change and variability have created widespread risks for farmers’ food and livelihood security in the Himalayas. However, the extent of impacts experienced and perceived by farmers varies, as there is substantial diversity in the demographic, social, and economic conditions. Therefore, it is essential to understand how farmers with differen...

The blood-brain barrier (BBB) poses a significant challenge for drug brain delivery. The limitation of our knowledge about the nature of BBB explains the slow progress in the therapy of brain diseases and absence of methods for drug brain delivery in the clinical practice. Here we show that BBB opens for low/high weight molecules and nanocarriers a...

Numerous studies have demonstrated the important role of noise in the dynamical behaviour of a complex system. The most probable trajectories of nonlinear systems under the influence of Gaussian noise have recently been studied already. However, there has been only a few works that examine how most probable trajectories in the two-dimensional syste...

The peripheral lymphatic system plays a crucial role in the recovery mechanisms after many pathological changes, such as infection, trauma, vascular, or metabolic diseases. The lymphatic clearance of different tissues from waste products, viruses, bacteria, and toxic proteins significantly contributes to the correspondent recovery processes. Howeve...

Irregularly sampled time series usually require data preprocessing before a desired time-series analysis can be applied. We propose an approach for distance measuring of pairs of data points which is directly applicable to irregularly sampled time series. In order to apply recurrence plot analysis to irregularly sampled time series, we use this app...

Thermoacoustic instability is a result of the positive feedback between the acoustic pressure and the unsteady heat release rate fluctuations in a combustor. We apply the framework of the synchronization theory to study the coupled behavior of these oscillations during the transition to thermoacoustic instability in a turbulent bluff-body stabilize...

In the last decade, there has been a growing body of literature addressing the utilization of complex network methods for the characterization of dynamical systems based on time series. While both nonlinear time series analysis and complex network theory are widely considered to be established fields of complex systems sciences with strong links to...

In recent years, complex network analysis facilitated the identification of universal and unexpected patterns in complex climate systems. However, the analysis and representation of a multiscale complex relationship that exists in the global climate system are limited. A logical first step in addressing this issue is to construct multiple networks...

The peripheral lymphatic system plays a crucial role in the recovery mechanisms after many pathological changes, such as infection, trauma, vascular, or metabolic diseases. The lymphatic clearance of different tissues from waste products, viruses, bacteria and toxic proteins significantly contributes to the correspondent recovery processes. However...

In practical turbulent combustors, thermoacoustic instability is one of the major challenges, which results in large amplitude ruinous limit cycle oscillations. The occurrence of such large amplitude oscillations in the acoustic field of the combustor causes enhanced heat transfer to the walls and can lead to structural damage of the engine. Thermo...

Reinforcement learning in multi-agent systems has been studied in the fields of economic game theory, artificial intelligence and statistical physics by developing an analytical understanding of the learning dynamics (often in relation to the replicator dynamics of evolutionary game theory). However, the majority of these analytical studies focuses...

A nonlinear decomposition method is applied to the analysis of global sea surface temperature (SST) time series in different epochs related to the Pacific Decadal Oscillation (PDO) since the end of 19th century to present time. This method allows one to extract an optimal (small) number of global nonlinear teleconnection patterns associated with di...

We propose a novel technique to analyze multistable, non-linear dynamical systems. It enables one to characterize the evolution of a time-dependent stability margin along stable periodic orbits. By that, we are able to indicate the moments along the trajectory when the stability surplus is minimal, and even relatively small perturbation can lead to...

In this work, we apply the spatial recurrence quantification analysis (RQA) to identify chaotic burst phase synchronisation in networks. We consider one neural network with small-world topology and another one composed of small-world subnetworks. The neuron dynamics is described by the Rulkov map, which is a two-dimensional map that has been used t...

We investigate the basin of attraction properties and its boundaries for chimera states in a circulant network of Hénon maps. It is known that coexisting basins of attraction lead to a hysteretic behaviour in the diagrams of the density of states as a function of a varying parameter. Chimera states, for which coherent and incoherent domains occur s...

Constructing a reliable and stable emotion recognition system is a critical but challenging issue for realizing an intelligent human-machine interaction. In this study, we contribute a novel channel-frequency convolutional neural network (CFCNN), combined with recurrence quantification analysis (RQA), for the robust recognition of electroencephalog...

We investigate the basin of attraction properties and its boundaries for chimera states in a circulant network of H\'enon maps. Chimera states, for which coherent and incoherent domains coexist, emerge as a consequence of the coexistence of basin of attractions for each state. It is known that the coexisting basins of attraction lead to a hystereti...

In this paper, we aim to develop the averaging principle for a slow-fast system of stochastic reaction-diffusion equations driven by Poisson random measures. The coefficients of the equation are assumed to be functions of time, and some of them are periodic or almost periodic. So, the Poisson term needs to be processed, and a new method to define t...

We focus on the asymptotic behavior of two-time-scale delay systems driven by L\'evy processes. There are several difficulties in these problems, such as ${\left( {{x^\varepsilon }\left( t \right),{\xi ^\varepsilon }\left( t \right)} \right)^\prime }$ being not Markov, the state-dependence of the noises and the dispose of the infinitesimal operator...

Reconciling the paths of extreme rainfall with those of typhoons remains difficult despite advanced forecasting techniques. We use complex networks defined by a nonlinear synchronization measure termed event synchronization to track extreme rainfall over the Japanese islands. Directed networks objectively record patterns of heavy rain brought by fr...

In the last decade, the southeast region of Brazil has been suffering severe water shortages. Here, we propose to compute the expected drought period length to characterize the drought events in the region of São Paulo. We report the unique properties of the exceptional drought event during the austral summer 2014 by showing the differences and sim...

The climate of South America exhibits pronounced differences between rainy and dry seasons, associated with specific synoptic features such as the establishment of the South Atlantic convergence zone. Here, we analyze the spatiotemporal correlation structure and in particular teleconnections of daily rainfall associated with these features by means...

We investigate a quantitative bistable two-dimensional model (MeKS network) of gene expression dynamics describing the competence development in the Bacillus subtilis under the influence of Lévy as well as Brownian motions. To analyze the transitions between the vegetative and the competence regions therein, two dimensionless deterministic quantiti...

We use complex network theory to investigate the dynamical transition from stable operation to thermoacoustic instability via intermittency in a turbulent combustor with a bluff body stabilized flame. A spatial network is constructed, representing each of these three dynamical regimes of combustor operation, based on the correlation between time se...

We consider a network topology according to the cortico-cortical connec- tion network of the human brain, where each cortical area is composed of a random network of adaptive exponential integrate-and-fire neurons. Depending on the parameters, this neuron model can exhibit spike or burst patterns. As a diagnostic tool to identify spike and burst pa...

Optimizing economic welfare in environmental governance has been criticized for delivering short-term gains at the expense of long-term environmental degradation. Different from economic optimization, the concepts of sustainability and the more recent safe operating space have been used to derive policies in environmental governance. However, a for...