Transient Dynamics Research Articles

Building functional networks for complex response analysis in systems of coupled nonlinear oscillators

Some aspects of engineering dynamics, such as nonlinearities and transient motion of many interconnected parts, remain difficult to handle today. To comply with increasing demands on resilience and safety, the dynamics of large machines need to be better understood. Complex network methods, already present in many scientific disciplines, provide a tool set complementary to conventional methods of system analysis. This work aims at providing a new, function-based view on mechanical systems by generating functional networks. To this end, a network algorithm is applied to sets of cyclically coupled Duffing oscillators as a common example of a complex nonlinear mechanical system. In the functional network, each node represents an oscillator while the direction of the network edges represents a functional coupling. Results show that the network method is capable of identifying dynamical transitions and synchronization between components, as well as determining the number of different states present within a system. Additionally, the time evolution of the component interactions, especially in response to a disturbance, is studied via a sliding-window approach. The results of this analysis might hopefully open new ways for a more efficient system analysis through optional sensor placement, and for effective countermeasures against unwanted dynamics through improved analysis of transient dynamics.

Coactivation pattern analysis reveals altered whole-brain functional transient dynamics in autism spectrum disorder.

Recent studies on autism spectrum disorder (ASD) have identified recurring states dominated by similar coactivation pattern (CAP) and revealed associations between dysfunction in seed-based large-scale brain networks and clinical symptoms. However, the presence of abnormalities in moment-to-moment whole-brain dynamics in ASD remains uncertain. In this study, we employed seed-free CAP analysis to identify transient brain activity configurations and investigate dynamic abnormalities in ASD. We utilized a substantial multisite resting-state fMRI dataset consisting of 354 individuals with ASD and 446 healthy controls (HCs, from HC groups and 2). CAP were generated from a subgroup of all HC subjects (HC group 1) through temporal K-means clustering, identifying four CAPs. These four CAPs exhibited either the activation or inhibition of the default mode network (DMN) and were grouped into two pairs with opposing spatial CAPs. CAPs for HC group 2 and ASD were identified by their spatial similarity to those for HC group 1. Compared with individuals in HC group 2, those with ASD spent more time in CAPs involving the ventral attention network but less time in CAPs related to executive control and the dorsal attention network. Support vector machine analysis demonstrated that the aberrant dynamic characteristics of CAPs achieved an accuracy of 74.87% in multisite classification. In addition, we used whole-brain dynamics to predict symptom severity in ASD. Our findings revealed whole-brain dynamic functional abnormalities in ASD from a single transient perspective, emphasizing the importance of the DMN in abnormal dynamic functional activity in ASD and suggesting that temporally dynamic techniques offer novel insights into time-varying neural processes.

Leaky RyR2 channels as pro-arrhythmic trigger in the PKP2-deficient atrial myocardium

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): American Heart Association National Institutes of Health Introduction Atrial arrhythmias, like atrial fibrillation, occur in 20–40% of patients with Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC). Atrial fibrillation in ARVC patients is often associated with an increased risk of sustained ventricular arrhythmias and inappropriate ICD shocks. However, the pathophysiology behind the development of atrial arrhythmias in ARVC is far from clear. A genome-wide association study, based on UK-biobank data, revealed a link between atrial fibrillation and variants in the desmosomal gene plakophilin-2 (PKP2). Previous studies show that PKP2 is necessary to maintain the transcription of genes that control intracellular calcium (Ca2+) cycling and that loss of PKP2 expression in adult mouse ventricular tissue leads to disruption of intracellular Ca2+ homeostasis. In this study, we test the hypothesis that loss of PKP2 expression leads to pro-arrhythmic changes in atrial myocytes. Methods Experiments were carried out using a cardiac-specific, tamoxifen (TAM)-activated PKP2 knockout murine model (PKP2-cKO). Cre-negative, flox-positive, TAM-injected littermates were used as controls. We used RNA sequencing, quantitative imaging modalities, as well as biochemical and electrophysiological methods to study the functional and structural properties of atrial PKP2cKO tissue. Studies were carried out 21 days post-tamoxifen injection, a time point at which an arrhythmogenic cardiomyopathy of right ventricular predominance is manifest. Results In contrast to the previously-reported observations in PKP2cKO ventricular myocytes, atrial PKP2cKO myocytes presented no significant differences in Ca2+ transient dynamics, SR load and action potential duration. However, PKP2cKO atrial myocytes showed an increased frequency and amplitude of Ca2+ sparks, in combination with increased diastolic Ca2+ levels as well as an increase in cellular ROS levels. RNAseq data showed an under-representation of mRNA for Integrinα7, a stabilizer of Ryr2 that reduces its phosphorylation. Separate studies showed that PKP2cKO atrial myocytes present impaired relaxation and enhanced sarcomere shortening, a finding consistent with a downregulation in the expression of Myosin Binding Protein C. Isoproterenol (ISO) exposure further increased the frequency of Ca2+ sparks and the levels of diastolic Ca2+, and these effects were reversed by acute (30 minute) in vivo treatment with Ryanodex (medical grade Dantrolene), a known RyR blocker. Conclusion Loss of PKP2 expression affects cellular Ca2+ handling and electrophysiology differently in the atrial versus ventricular myocardium. We speculate that an increased probability of opening of Ryr2 channels, caused by ROS-induced RyR2 oxidation and/or Integrinα7-induced RyR2 phosphorylation, serve as pro-arrhythmic trigger in the PKP2-deficient atrial myocardium, that these effects can be amplified by a catecholaminergic input and that RyR blockers can dampen these pro-arrhythmic effects.

Transient dynamics of an anisotropic plate on an elastic-inertial foundation with local supports

Transient dynamics of an anisotropic plate on an elastic-inertial foundation with local supports

Promotion of Probabilistic Bit Generation in Mott Devices by Embedded Metal Nanoparticles.

Considerable attention has been drawn to the use of volatile two-terminal devices relying on the Mott transition for the stochastic generation of probabilistic bits (p-bits) in emerging probabilistic computing. To improve randomness and endurance of bit streams provided by these devices, delicate control of the transient evolution of switchable domains is required to enhance stochastic p-bit generation. Herein, it is demonstrated that the randomness of p-bit streams generated via the consecutive pulse inputs of pump-probe protocols can be increased by the deliberate incorporation of metal nanoparticles (NPs), which influence the transient dynamics of the nanoscale metallic phase in VO2 Mott switches. Among the vertically stacked Pt-NP-containing VO2 threshold switches, those with higher Pt NP density show a considerably wider range of p-bit operation (e.g., up to ≈300% increase in ΔVprobe upon going from (Pt NP/VO2)0 to (Pt NP/VO2)11) and can therefore be operated under the conditions of high speed (400 kbit s-1), low power consumption (14 nJ per bit), and high stability (>105200 bits) for p-bit generation. Thus, the study presents a novel strategy that exploits nanoscale phase control to maximize the generation of nondeterministic information sources for energy-efficient probabilistic computing hardware.

Range and climate niche shifts in European and North American breedingbirds.

Species respond dynamically to climate change and exhibit time lags. Consequently, species may not occupy their full climatic niche during range shifting. Here, we assessed climate niche tracking during recent range shifts of European and UnitedStates (US) birds. Using data from two European bird atlases and from the North American Breeding Bird Survey betweenthe 1980s and 2010s, we analysed range overlap and climate niche overlap based on kernel density estimation. Phylogenetic multiple regression was used to assess the effect of species morphological, ecological and biogeographic traits on range and niche metrics. European birds shifted their ranges north and north-eastwards, US birds westwards. Range unfilling was lower than expected by null models, and niche expansion was more common than niche unfilling. Also, climate niche tracking was generally lower in US birds and poorly explained by species traits. Overall, our results suggest that dispersal limitations were minor in range shifting birds in Europe and theUSA while delayed extinctions from unfavourable areas seem more important. Regional differences could be related to differences in land use history and monitoring schemes. Comparative analyses of range and niche shifts provide a useful screening approach for identifying the importance of transient dynamics and time-lagged responses to climate change. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Self acceleration from spectral geometry in dissipative quantum-walk dynamics

The dynamic behavior of a physical system often originates from its spectral properties. In open systems, where the effective non-Hermitian description enables a wealth of spectral structures in the complex plane, the concomitant dynamics are significantly enriched, whereas the identification and comprehension of the underlying connections are challenging. Here we experimentally demonstrate the correspondence between the transient self-acceleration of local excitations and the non-Hermitian spectral topology using lossy photonic quantum walks. Focusing first on one-dimensional quantum walks, we show that the measured short-time acceleration of the wave function is proportional to the area enclosed by the eigenspectrum. We then reveal a similar correspondence in two-dimension quantum walks, where the self-acceleration is proportional to the volume enclosed by the eigenspectrum in the complex parameter space. In both dimensions, the transient self-acceleration crosses over to a long-time behavior dominated by a constant flow at the drift velocity. Our results unveil the universal correspondence between spectral topology and transient dynamics, and offer a sensitive probe for phenomena in non-Hermitian systems that originate from spectral geometry.

Transient Propagation of the Invasion Front in the Homogeneous Landscape and in the Presence of a Road

Understanding the propagation of invasive plants at the beginning of invasive spread is important as it can help practitioners eradicate harmful species more efficiently. In our work the propagation regime of the invasive plant species is studied at the short-time scale before a travelling wave is established and advances into space at a constant speed. The integro-difference framework has been employed to deal with a stage-structured population, and a short-distance dispersal mode has been considered in the homogeneous environment and when a road presents in the landscape. It is explained in the paper how nonlinear spatio-temporal dynamics arise in a transient regime where the propagation speed depends on the detection threshold population density. Furthermore, we investigate the question of whether the transient dynamics become different when the homogeneous landscape is transformed into the heterogeneous one. It is shown in the paper how invasion slows down in a transient regime in the presence of a road.

A hybrid transmission model for Plasmodium vivax accounting for superinfection, immunity and the hypnozoite reservoir

Malaria is a vector-borne disease that exacts a grave toll in the Global South. The epidemiology of Plasmodium vivax, the most geographically expansive agent of human malaria, is characterised by the accrual of a reservoir of dormant parasites known as hypnozoites. Relapses, arising from hypnozoite activation events, comprise the majority of the blood-stage infection burden, with implications for the acquisition of immunity and the distribution of superinfection. Here, we construct a novel model for the transmission of P. vivax that concurrently accounts for the accrual of the hypnozoite reservoir, (blood-stage) superinfection and the acquisition of immunity. We begin by using an infinite-server queueing network model to characterise the within-host dynamics as a function of mosquito-to-human transmission intensity, extending our previous model to capture a discretised immunity level. To model transmission-blocking and antidisease immunity, we allow for geometric decay in the respective probabilities of successful human-to-mosquito transmission and symptomatic blood-stage infection as a function of this immunity level. Under a hybrid approximation—whereby probabilistic within-host distributions are cast as expected population-level proportions—we couple host and vector dynamics to recover a deterministic compartmental model in line with Ross-Macdonald theory. We then perform a steady-state analysis for this compartmental model, informed by the (analytic) distributions derived at the within-host level. To characterise transient dynamics, we derive a reduced system of integrodifferential equations, likewise informed by our within-host queueing network, allowing us to recover population-level distributions for various quantities of epidemiological interest. In capturing the interplay between hypnozoite accrual, superinfection and acquired immunity—and providing, to the best of our knowledge, the most complete population-level distributions for a range of epidemiological values—our model provides insights into important, but poorly understood, epidemiological features of P. vivax.

Quantum simulation of dissipation for Maxwell equations in dispersive media

The dissipative character of an electromagnetic medium breaks the unitary evolution structure that is present in lossless, dispersive optical media. In dispersive media, dissipation appears in the Schrödinger representation of classical Maxwell equations as a sparse diagonal operator occupying an r-dimensional subspace. A first order Suzuki-Trotter approximation for the evolution operator enables us to isolate the non-unitary operators (associated with dissipation) from the unitary operators (associated with lossless media). The unitary operators can be implemented through qubit lattice algorithm (QLA) on n qubits, based on the discretization and the dimensionality of the pertinent fields. However, the non-unitary-dissipative part poses a challenge both physically and computationally on how it should be implemented on a quantum computer. In this paper, two probabilistic dilation algorithms are considered for handling the dissipative operators. The first algorithm is based on treating the classical dissipation as a linear amplitude damping-type completely positive trace preserving (CPTP) quantum channel where an unspecified environment interacts with the system of interest and produces the non-unitary evolution. Therefore, the combined system-environment is now closed, and must undergo unitary evolution in the dilated space. The unspecified environment can be modeled by just one ancillary qubit, resulting in an implementation scaling of O(2n−1n2) elementary gates for the total system-environment unitary evolution operator. The second algorithm approximates the non-unitary operators by the Linear Combination of Unitaries (LCU). On exploiting the diagonal structure of the dissipation, we obtain an optimized representation of the non-unitary part, which requires O(2n) elementary gates. Applying the LCU method for a simple dielectric medium with homogeneous dissipation rate, the implementation scaling can be further reduced into O[poly(n)] basic gates. For the particular case of weak dissipation we show that our proposed post-selective dilation algorithms can efficiently delve into the transient evolution dynamics of dissipative systems by calculating the respective implementation circuit depth. A connection of our results with the non-linear-in-normalization-only (NINO) quantum channels is also presented.

Biological computations: Limitations of attractor-based formalisms and the need for transients

Living systems, from single cells to higher vertebrates, receive a continuous stream of non-stationary inputs that they sense, for e.g. via cell surface receptors or sensory organs. By integrating these time-varying, multi-sensory, and often noisy information with memory using complex molecular or neuronal networks, they generate a variety of responses beyond simple stimulus-response association, including avoidance behavior, life-long-learning or social interactions. In a broad sense, these processes can be understood as a type of biological computation. Taking as a basis generic features of biological computations, such as real-time responsiveness or robustness and flexibility of the computation, we highlight the limitations of the current attractor-based framework for understanding computations in biological systems. We argue that frameworks based on transient dynamics away from attractors are better suited for the description of computations performed by neuronal and signaling networks. In particular, we discuss how quasi-stable transient dynamics from ghost states that emerge at criticality have a promising potential for developing an integrated framework of computations, that can help us understand how living system actively process information and learn from their continuously changing environment.

Ultrafast Dynamics of Strong Near‐Field Coupled Localized and Delocalized Surface Plasmons

AbstractThis paper reports transient dynamics of strong near‐field coupling behavior of plasmons in a multilayer metal nanostructure that enables ultrahigh‐efficient optical switching. Particle plasmon on the top array units couples with localized/delocalized plasmons on the bottom Au film to produce dipolar and high‐order hybrid modes with nearly suppressed reflection. The mode coupling can be tuned from near‐field to far‐field regime readily mediated by the spacer thickness. The dipolar mode inherits the high dispersive property of the delocalized plasmon, but the higher‐order one shows limited dispersion. Transient spectroscopy illustrates both hybrid modes have a picosecond timescale redshift under on‐ and off‐resonance excitation. However, the higher‐order mode exhibits a longer decay lifetime than the dipolar one because of resonance characteristics and cavity properties. An ultrafast optical switching effect with a response time of τ = 3.2 ps and an ultrahigh efficiency of 5100 mOD mJ−1 cm2 is achieved under an extremely low pump fluence.

A thermodynamic motivated RCCM damage interface model in an explicit transient dynamics framework

A thermodynamic motivated RCCM damage interface model in an explicit transient dynamics framework

Instantaneous thermometry imaging using two-photon laser-induced fluorescence.

Measuring temperature in complex two-phase flows is crucial for understanding the dynamics of heat and mass transfer. In this Letter, we introduce a novel, to the best of our knowledge, optical approach based on the combination of two-photon laser-induced fluorescence (2p-LIF) imaging and two-color laser-induced fluorescence (2CLIF) for instantaneous temperature mapping of complex liquid media. Using Kiton Red (KR) and Rhodamine 560 (R560), a temperature sensitivity of 1.54%/∘C has been achieved over a range of 17-60°C. The monitoring of two-dimensional transient temperature dynamics in the heating and degassing of water shows the efficiency of the 2p-2CLIF. This new approach contributes to the toolkit of optical temperature measurement techniques, providing a robust solution for studying transient scattering media and high-speed two-phase flows.

Imaging biomacromolecules in action with liquid-phase electron microscopy

Imaging biomacromolecules in action in a liquid environment poses a challenge to single-molecule experiments. Liquid-phase electron microscopy (LP-EM) has demonstrated its unique ability to reveal previously unseen transient dynamics and intermediate states of delicate biomacromolecular systems (protein, DNA/RNA) with deep-learning methods and careful evaluation of electron beam effects.

Simulation Analysis of the Transient Absorption Spectroscopic Dynamics of Charge Recombination in a Semiconductor Attached with a Gold Nanoparticle Using Initially Variable Coordinates

Simulation Analysis of the Transient Absorption Spectroscopic Dynamics of Charge Recombination in a Semiconductor Attached with a Gold Nanoparticle Using Initially Variable Coordinates

Dividing active and passive particles in nonuniform nutrient environments

To explore the coupling between a growing population of microorganisms such as E. coli and a nonuniform nutrient distribution, we formulate a minimalistic model. It consists of active Brownian particles that divide and grow at a nutrient-dependent rate following the Monod equation. The nutrient concentration obeys a diffusion equation with a consumption term and a point source. In this setting the heterogeneity in the nutrient distribution can be tuned by the diffusion coefficient. In particle-based simulations, we demonstrate that passive and weakly active particles form proliferation-induced clusters when the nutrient is localized, without relying on further mechanisms such as chemotaxis or adhesion. In contrast, strongly active particles disperse in the whole system during their lifetime and no clustering is present. The steady population is unaffected by activity or nonuniform nutrient distribution and only determined by the ratio of nutrient influx and bacterial death. However, the transient dynamics strongly depends on the nutrient distribution and activity. Passive particles in almost uniform nutrient profiles display a strong population overshoot, with clusters forming all over the system. In contrast, when slowly diffusing nutrients remain centred around the source, the bacterial population quickly approaches the steady state due to its strong coupling to the nutrient. Conversely, the population overshoot of highly active particles becomes stronger when the nutrient localisation increases. We successfully map the transient population dynamics onto a uniform model where the effect of the nonuniform nutrient and bacterial distributions are rationalized by two effective areas.

Genetic predictors of population resilience: A case study of native Brook Trout in headwater streams

AbstractObjectivePopulations of eastern Brook Trout Salvelinus fontinalis face threats from several sources, such as habitat fragmentation, climate change, and competition with introduced salmonids. As a native species, understanding how these populations will respond to disturbances is paramount to their management and effective conservation. A population's ability to respond to disturbance, its resilience, is influenced by several factors. One such group of factors is population genetics.MethodsWe calculated population resilience metrics based on transient dynamics using population projection matrix models. Long‐term demographic data from 23 headwater stream Brook Trout populations were used to parameterize models. Genetic data were collected, and genetic indices were calculated. Partial redundancy analysis was then used to evaluate relationships between resilience metrics and genetic indices.ResultInbreeding coefficient, rarefied allelic richness, pairwise genetic differentiation (FST), and effective population size were all found to be important variables in predicting resilience.ConclusionOur results suggest that genetic isolation may increase the demographic resilience in Brook Trout through faster generation times and higher juvenile survival, but this likely comes at the cost of increased extinction risk and truncated size structures. Genetic indices can provide insight into gene flow between populations, thus the relationship between population connectivity and resilience. Given the importance of connectivity to population resilience, restoring and maintaining movement corridors could affect resilience in headwater Brook Trout populations.

Transient vegetation dynamics in a tropical coastal wetland: Sea‐level rise, glycophyte retreat, and incipient loss in plant diversity

Transient vegetation dynamics in a tropical coastal wetland: Sea‐level rise, glycophyte retreat, and incipient loss in plant diversity

A high-accuracy intelligent fault diagnosis method for aero-engine bearings with limited samples

As a crucial component supporting aero-engine functionality, effective fault diagnosis of bearings is essential to ensure the engine's reliability and sustained airworthiness. However, practical limitations prevail due to the scarcity of aero-engine bearing fault data, hampering the implementation of intelligent diagnosis techniques. This paper presents a specialized method for aero-engine bearing fault diagnosis under conditions of limited sample availability. Initially, the proposed method employs the refined composite multiscale phase entropy (RCMPhE) to extract entropy features capable of characterizing the transient signal dynamics of aero-engine bearings. Based on the signal amplitude information, the composite multiscale decomposition sequence is formulated, followed by the creation of scatter diagrams for each sub-sequence. These diagrams are partitioned into segments, enabling individualized probability distribution computation within each sector, culminating in refined entropy value operations. Thus, the RCMPhE addresses issues prevalent in existing entropy theories such as deviation and instability. Subsequently, the bonobo optimization support vector machine is introduced to establish a mapping correlation between entropy domain features and fault types, enhancing its fault identification capabilities in aero-engine bearings. Experimental validation conducted on drivetrain system bearing data, actual aero-engine bearing data, and actual aerospace bearing data demonstrate remarkable fault diagnosis accuracy rates of 99.83%, 100%, and 100%, respectively, with merely 5 training samples per state. Additionally, when compared to the existing eight fault diagnosis methods, the proposed method demonstrates an enhanced recognition accuracy by up to 28.97%. This substantiates its effectiveness and potential in addressing small sample limitations in aero-engine bearing fault diagnosis.