Spatiotemporal Instability Research Articles

Spatio-temporal instabilities of blood flow in a model capillary network

Spatio-temporal instabilities of blood flow in a model capillary network

Modeling the Causes of Urban Traffic Crashes: Accounting for Spatiotemporal Instability in Cities

Traffic crashes have become one of the key public health issues, triggering significant apprehension among citizens and urban authorities. However, prior studies have often been limited by their inability to fully capture the dynamic and complex nature of spatiotemporal instability in urban traffic crashes, typically focusing on static or purely spatial effects. Addressing this gap, our study employs a novel methodological framework that integrates an Integrated Nested Laplace Approximation (INLA)-based Stochastic Partial Differential Equation (SPDE) model with spatially adaptive graph structures, which enables the effective handling of vast and intricate geospatial data while accounting for spatiotemporal instability. This approach represents a significant advancement over conventional models, which often fail to account for the fluid interplay between time-varying weather conditions, geographical attributes, and crash severity. We applied this methodology to analyze traffic crashes across three major U.S. cities—New York, Los Angeles, and Houston—using comprehensive crash data from 2016 to 2019. Our findings reveal city-specific disparities in the factors influencing severe traffic crashes, which are defined as incidents resulting in at least one person sustaining serious injury or death. Despite some universal trends, such as the risk-enhancing effect of cold weather and pedestrian crossings, we find marked differences across cities in relation to factors like temperature, precipitation, and the presence of certain traffic facilities. Additionally, the adjustment observed in the spatiotemporal standard deviations, with values such as 0.85 for New York and 0.471 for Los Angeles, underscores the varying levels of annual temporal instability across cities, indicating that the fluctuation in crash severity factors over time differs markedly among cities. These results underscore the limitations of traditional modeling approaches, demonstrating the superiority of our spatiotemporal method in capturing the heterogeneity of urban traffic crashes. This work has important policy implications, suggesting a need for tailored, location-specific strategies to improve traffic safety, thereby aiding authorities in better resource allocation and strategic planning.

Spatiotemporal instability and optical filament formation in metamaterials

This study investigates the spatiotemporal instability in artificial metamaterials, with a focus on generating ultrashort pulses or light filaments. We identify the parametric regions where the metamaterial exhibits spatiotemporal instability, enabling the generation of ultrashort pulses. Our approach involves modeling nonlinear pulse propagation in the metamaterial using a (3+1)-dimensional nonlinear Schrödinger equation and performing a standard linear stability analysis to explore the spatiotemporal instability. Leveraging the engineering freedom to tailor the material parameters, we numerically demonstrate the generation of ultrashort pulses through spatiotemporal instability.

Spatiotemporal evolution and instability of the mixing layer in supersonic ejector based on large eddy simulation

Spatiotemporal evolution and instability of the mixing layer in supersonic ejector based on large eddy simulation

Influence of nonic nonlinearity on spatiotemporal modulational instabilities in PT-symmetric fiber Bragg grating structures

Influence of nonic nonlinearity on spatiotemporal modulational instabilities in PT-symmetric fiber Bragg grating structures

The influence of residue interaction on thermal stability of lipase based on dynamic graph embedding

Lipases with high thermal stability have greater application in industrial production. Focusing on wild-type lipase and their thermotolerant mutants, this study employs dynamic graph embedding to explore the change of spatiotemporal characteristics in residue-residue interactions, analyzing the relationship between residue mutations and the thermal stability of lipase. K-means clustering is used to analyze the synergistic relationships between residues, revealing that thermotolerant mutants achieve higher thermal stability by enhancing the synergistic interactions between secondary structures, resulting in a more balanced and tightly-knit internal structure. Critical residues are identified using anomaly node detection methods, showing that residues with spatiotemporal instability are mainly distributed on highly flexible loop regions. Specifically, mutations at Tyr89 and Asp132 restrict the motion range of the loops, making the lipase structure more stable. The study demonstrates that mutating highly flexible regions to increase structural rigidity can effectively enhance the thermal stability of lipases.

Investigating the impact of temporal instability in smart roadway retrofitting on terrain-related crash injury severity

The advancement of intelligent road systems in developing countries poses unique challenges in identifying risk factors and implementing safety strategies. The variability of factors affecting crash injury severity leads to different risks across levels of roadway smartness, especially in hazardous terrains, complicating the adaptation of smart technologies. Therefore, this study investigates the temporal instability of factors affecting injury severities in crashes across various terrains, with a focus on the evolution of road smartness. Crash data from selected complex terrain regions in Shaanxi Province during smart road adaptation were used, and categorized into periods before, during, and after smart road implementations. A series of mixed logit models were employed to account for unobserved heterogeneity in mean and variance, and likelihood ratio tests were conducted to assess the spatio-temporal instability of model parameters across different topographic settings and smart processes. Moreover, a comparison between partially constrained and unconstrained temporal modeling approaches was made. The findings reveal significant differences in injury severity determinants across terrain conditions as roadway intelligence progressed. On the other hand, certain factors like pavement damage, truck and pedestrian involvement were identified that had relatively stable effects on crash injury severities. Out-of-sample predictions further emphasize the need for modeling across terrain and roadway development stages. These insights are crucial for developing tailored safety measures for smart road retrofitting in different terrain conditions, thereby supporting the transition towards smarter road systems in developing regions.

Spatiotemporal flow-induced instability of predator-prey model with Crowley-Martin functional response and prey harvesting.

Ecological systems can generate striking large-scale spatial patterns through local interactions and migration. In the presence of diffusion and advection, this work examines the formation of flow-induced patterns in a predator-prey system with a Crowley-Martin functional response and prey harvesting, where the advection reflects the unidirectional flow of each species migration (or flow). Primarily, the impact of diffusion and advection rates on the stability and the associated Turing and flow-induced patterns are investigated. The theoretical implication of flow-induced instability caused by population migration, mainly the relative migrations between prey and predator, is examined, and it also shows that Turing instability is the particular condition of flow-induced instability. The influence of the relative flow of both species and prey-harvesting effort on the emerging pattern is reported. Advection impacts a wide range of spatiotemporal patterns, including bands, spots, and a mixture of bands and spots in both harvested and unharvested dynamics. We also observe the diagonally bend-type banded patterns and straight-type banded patterns due to positive and negative relative flows, respectively. Here, the increasing relative flow increases the band length. The growing harvesting effort also decreases the band length, producing a thin band and a mixture of spots and bands due to the negative and positive relative flows, respectively. One exciting result observed here is that harvesting effort drives the flow-Turing and flow-Turing-Hopf instability into pure-flow instability.

Spatiotemporal instability analysis in single-vehicle crash severity on different roadway classifications

ABSTRACT The severity of crashes on national/provincial roads, urban roads, and rural roads was analyzed. Random parameters logit models with heterogeneity in means and variances under different time periods of the day and roadway classifications were employed. Analysis of factors influencing injury severity of single-vehicle crashes in the driver, vehicle, road, and environment to explore correlation and difference between influencing factors and crash severity. The results showed that the effect of factors that determine injury severity varied significantly across different roadway classifications. Specifically, driver age (<30) and summer were only significantly associated with single-vehicle crashes on urban roads. Dawn/dusk was only significant in single-vehicle crashes on rural roads. Meanwhile, overall spatiotemporal instability was observed in the study. While several indicators were also reported to show relative spatial or temporal stability such as male, driver age (>55), motorcycle, traffic control, and visibility (<100 m).

Spatiotemporal dynamics of modulation instability in Kerr nonlinear media with pure-quartic dispersion

We present the analytical and numerical analysis on spatiotemporal dynamics of modulation instability (MI) in Kerr nonlinear media with pure-quartic dispersion. We apply a linear stability method to arrive at a universal expression for pure-quartic instability gain, which can simultaneously describe the temporal, spatial, and spatiotemporal cases. The results show that the condition of such three fundamental instability occurrence in pure-quartic dispersion media (PDM) is the same as that in conventional quadratic dispersion media (QDM). Another interesting observation is that the maximum gain is also the same in both cases. For temporal instability, there exists a critical power below which the instability bandwidth becomes wider than the corresponding case in QDM or otherwise. For spatiotemporal instability, the instability region depending on critical frequencies is found to show some remarkable difference when compared with the latter case. The analytical prediction resulting from linear stability analysis is confirmed by the numerical method.

Analysis of Flow Instability and Mechanical Energy Loss of Fluid Field in Fluid Momentum Wheel

A new type of anti-rolling device denoted as a fluid momentum wheel (FMW) is proposed to address the limitations of traditional gyrostabilizers in reducing the roll responses of floating platforms in waves. The proposed device is based on the same gyroscope theorem, which differs from a rigid gyrostabilizer in that the internal fluid generates secondary flow in the cross-section under the combined effects of inertial centrifugal force and a radial pressure gradient, and the streamwise velocity exhibits a non-uniform distribution. These instability phenomena may cause mechanical energy loss in the flow field, which is critical for selecting the driving device and the anti-roll control performance of offshore platforms. In the study, different turbulence models are compared with the results of a Direct Numerical Simulation (DNS) and experiments to ensure the accuracy of the numerical method, and the spatiotemporal distribution characteristics of the flow field in FMW are analyzed. Therein, the SST k-ω model accurately verifies the flow instability phenomenon of the FMW observed in the Particle Image Velocimetry (PIV) experiment. Next, this paper proposes corresponding evaluation parameters to assess the impact of typical parameters on the flow field instability. The results show that the flow instability increases with an increase in the typical parameters of FMWs (such as the pipe diameter, curvature radius, and velocity). Furthermore, the paper discusses the relationship between dimensionless mechanical factors (Reynolds number, curvature ratio) and the spatiotemporal instability of the flow field, revealing the essential effects of the curvature ratio and Reynolds number on the loss coefficient.

Dual-track spatio-temporal learning for urban flow prediction with adaptive normalization

Robust urban flow prediction is crucial for transportation planning and management in urban areas. Although recent advances in modeling spatio-temporal correlations have shown potential, most models fail to adequately consider the complex spatio-temporal semantic information present in real-world scenarios. We summarize the following three primary limitations in existing models: a) The majority of existing models project overall time periods into the same latent space, neglecting the diverse temporal semantics between different time intervals. b) Existing models tend to capture spatial dependencies from a locale perspective such as surroundings but do not pay attention to the global influence factors. c) Beyond the spatio-temporal properties, the dynamics and instability of the data sequences introduce perturbations to the prediction results, potentially leading to model degradation. To address these issues, we propose a dual-track spatial-temporal learning module named DualST for accurate urban flow inference. To more effectively differentiate semantic information in the time dimension, we assign the overall time scales into closeness and periodicity. The dual-track module, which includes temporal causality inference and temporal contextual inference, simultaneously exploits the dynamic evolutionary trends and periodic traffic patterns, respectively. The proposed DualST captures global spatial features in a self-supervised manner which not only enriches the spatial semantics but also avoids introducing additional prior knowledge. To eliminate the instability caused by dynamics, we first adopt spatio-temporal adaptive normalization to learn appropriate data sequence normalization. We evaluate the proposed DualST on two typical urban flow datasets. The experiment results show that our model not only exhibits a consistent superiority over various state-of-the-art baselines but also has remarkable generalization capability.

Electrographic flow mapping of persistent atrial fibrillation: intra- and inter-procedure reproducibility in the absence of 'ground truth'.

Validating mapping systems that identify atrial fibrillation (AF) sources (focal/rotational activity) is confounded by the absence of ground truth. A key concern of prior mapping technologies is spatiotemporal instability, manifesting as poor map reproducibility. Electrographic flow (EGF) employs a novel algorithm that visualizes atrial electrical wavefront propagation to identify putative AF sources. We analysed both intra- (3 min) and inter- (>3 months) procedure EGF map reproducibility. In 23 persistent AF patients, after pulmonary vein isolation (PVI), EGF maps were generated from 3 serial 1 min recordings using a 64-electrode basket mapping catheter (triplets) at right and left atrial locations. Source prevalence from map triplets was compared between recordings. Per protocol, 12 patients returned for 3-month remapping (1 non-inducible): index procedure post-PVI EGF maps were compared with initial EGF remapping at 3-month redo. Intra-procedure reproducibility: analysing 224 map triplets (111 right atrium, 113 left atrium) revealed a high degree of map consistency with minimal min-to-min shifts: 97 triplets (43%), exact match of leading sources on all 3 maps; 95 triplets (42%), leading source within 1 electrode space on 2 of 3 maps; and 32 triplets (14%), chaotic leading source pattern. Average deviation in source prevalence over 60 s was low (6.4%). Inter-procedure reproducibility: spatiotemporal stability of EGF mapping >3 months was seen in 16 of 18 (89%) sources mapped in 12 patients with (re)inducible AF. Electrographic flow mapping generates reproducible intra- and inter-procedural maps, providing rationale for randomized clinical trials targeting these putative AF sources.

Unravelling diverse spatiotemporal orders in chlorine dioxide-iodine-malonic acid reaction-diffusion system through circularly polarized electric field and photo-illumination.

Designing and predicting self-organized pattern formation in out-of-equilibrium chemical and biochemical reactions holds fundamental significance. External perturbations like light and electric fields exert a crucial influence on reaction-diffusion systems involving ionic species. While the separate impacts of light and electric fields have been extensively studied, comprehending their combined effects on spatiotemporal dynamics is paramount for designing versatile spatial orders. Here, we theoretically investigate the spatiotemporal dynamics of chlorine dioxide-iodine-malonic acid reaction-diffusion system under photo-illumination and circularly polarized electric field (CPEF). By applying CPEF at varying intensities and frequencies, we observe the predominant emergence of oscillating hexagonal spot-like patterns from homogeneous stable steady states. Furthermore, our study unveils a spectrum of intriguing spatiotemporal instabilities, encompassing stripe-like patterns, oscillating dumbbell-shaped patterns, spot-like instabilities with square-based symmetry, and irregular chaotic patterns. However, when we introduce periodic photo-illumination to the hexagonal spot-like instabilities induced by CPEF in homogeneous steady states, we observe periodic size fluctuations. Additionally, the stripe-like instabilities undergo alternating transitions between hexagonal spots and stripes. Notably, within the Turing region, the interplay between these two external influences leads to the emergence of distinct superlattice patterns characterized by hexagonal-and square-based symmetry. These patterns include parallel lines of spots, target-like formations, black-eye patterns, and other captivating structures. Remarkably, the simple perturbation of the system through the application of these two external fields offers a versatile tool for generating a wide range of pattern-forming instabilities, thereby opening up exciting possibilities for future experimental validation.

A novel bearing-time record estimation method based on α-stabledistribution modeling

Bearing-time record (BTR) is widely used in the field of passive sonar information processing for target tracking. Most existing BTR estimation methods of ship radiated noise are generally based on energy-varying under the assumption of Gaussian modeling in the time domain. However, some weak trajectories may exist in BTR for the decentralized energy distribution and unstable goodness of fit with Gaussian modeling caused by the spatiotemporal instability of the marine environment. In this paper, a novel ship trajectory enhancement method which is based on α-stable distribution modeling theory is presented. In order to make the statistical characteristic of ship radiated noise better reflected, the proposed method utilizes the α-stable distribution modeling in the real part of ship radiated noise Discrete Fourier Transform (DFT) coefficient instead of the Gaussian modeling in the time domain. The scale parameter γ of α-stable distribution is substituted for variance and enhanced BTR is achieved. According to the experimental results, the real part of the DFT coefficient of ship radiated noise could be fitted by α-stable distribution at the significant level of 0.05. Compared with traditional BTR estimation method, the proposed method could gain 3.1dB enhancement on peak signal-to-noise ratio (PSNR).

Spatio-temporal instabilities in viscoelastic channel flows: The centre mode

We study in this work the spatio-temporal characteristics of the centre-mode linear instability in viscoelastic channel flows of Oldroyd-B and FENE-P fluids. The linear complex Ginzburg–Landau equation derived using an amplitude expansion method is adopted to determine whether the flow is convectively unstable or absolutely unstable. Comparison of the obtained results with those from the conventional saddle-point searching method shows a favourable agreement. This demonstrates the good predictability of the linear complex Ginzburg–Landau equation which is more suitable for a parametric study in a large space than the conventional method. We found that the centre-mode instability in the viscoelastic channel flow is of a convective nature, i.e., the trailing edge of the wavepacket travels downstream. This could be attributed to the relatively high phase speed, low spreading rate and low growth rate of the instability, collectively preventing a disturbance from travelling upstream. Our results show that stronger polymer elasticity (a greater elastic number or larger polymer concentration) marginally affects the trailing-edge velocity of the centre mode. Decreasing the maximum polymer extensibility in the FENE-P model reduces the spreading rate of the wavepacket and makes the centre-mode disturbance more convective. Theoretical derivations at asymptotically high Reynolds numbers confirm the convective nature of the instabilities from numerical observations. Our results may be conducive to a better understanding of the spatio-temporal instability in viscoelastic experiments.

Modeling injury severities of single and multi-vehicle freeway crashes considering spatiotemporal instability and unobserved heterogeneity

ABSTRACT Single and multi-vehicle (SMV) crashes remain a significant issue, causing serious safety and economic concerns, and therefore deserve more attention. Using crash data in the Beijing-Shanghai and Changchun-Shenzhen freeways over the five years (2015–2019), this paper explored the transferability and heterogeneity for crash type (single-vehicle versus multi-vehicle crashes) and spatiotemporal stability of determinants affecting the injury severity. The random parameters logit approach with heterogeneity in means and variances was used to model three possible crash injury severity outcomes (measured by the most severely injured individual in the crash) of no injury, minor injury, and severe injury and identify the determinants in terms of driver, vehicle, roadway, environment, temporal, spatial, traffic, and crash characteristics. Remarkable differences were observed in the SMV crashes, and the contributing factors also reported considerable temporal and (or) spatial instabilities. The insights of this study should be valuable to help freeway designers and decision-makers understand the contributing mechanism of the factors and develop the proper management strategies and enforcement countermeasures.

Analysing spatiotemporal instabilities in magneto-optical traps with the tools of turbulence theory

A large cloud of 87Rb atoms confined in a magneto-optical trap exhibits, in a certain regime of parameters, spatiotemporal instabilities with a dynamics resembling that of a turbulent fluid. We apply the methods of turbulence theory based on structure function analysis to extract scaling exponents which are compared to known turbulent regimes. This analysis also allows us to make a clear distinction between different instability regimes.

Scaling laws and spatial effects of Brazilian health regions: a research protocol

The literature has already consolidated the importance of health regions for Brazilian public health. Complexity properties strongly mark such regions. In this context, there are abundant indications that health regions should be analyzed with approaches linked to the sciences of complexity. One of these approaches, the estimation of scaling laws, can describe important properties of socio-spatial elements. However, no studies estimate the scaling laws of Brazilian health regions. This research protocol can remedy this limitation, proposing the estimation of scaling laws of the previously mentioned regions, mainly considering variables relevant to Brazilian public health. Still, this paper can substantially mitigate other relevant limitations of usual research that estimate scaling laws of socio-spatial elements. These mitigations, which provide advances in the literature on estimating scaling laws, are given by the proposal of modeling (if necessary) spatial effects and estimating scaling laws for the entire population of the socio-spatial elements. According to the theory, the expected results are non-linear scaling laws, which will likely vary with space and time and coexist with relevant spatial effects. From such laws and effects, it will be possible to accurately characterize the performance of each health region through Spatial and Scale Adjusted Metropolitan Indicators and unravel spatio-temporal properties, stabilities, and instabilities of sets composed of health regions. The expected findings of this paper can help rearrange health regions and improve the quality of information used in Brazilian public health planning.

Deciphering electric field induced spatial pattern formation in the photosensitive chlorine-dioxide iodine malonic acid reaction and the Brusselator reaction-diffusion systems.

Reaction-diffusion systems involving ionic species are susceptible to an externally applied electric field. Depending on the charges on the ionic species and the intensity of the applied electric field, diverse spatiotemporal patterns can emerge. We here considered two prototypical reaction-diffusion systems that follow activator-inhibitor kinetics: the photosensitive chlorine dioxide-iodine-malonic acid (CDIMA) reaction and the Brusselator model. By theoretical investigation and numerical simulations, we unravel how and to what extent an externally applied electric field can induce and modify the dynamics of these two systems. Our results show that both the uni- and bi-directional electric fields may induce Turing-like stationary patterns from a homogeneous uniform state resulting in horizontal, vertical, or bent stripe-like inhomogeneity in the photosensitive CDIMA system. In contrast, in the Brusselator model, for the activator and the inhibitor species having the same positive or negative charges, the externally applied electric field cannot develop any spatiotemporal instability when the diffusion coefficients are identical. However, various spatiotemporal patterns emerge for the same opposite charges of the interacting species, including moving spots and stripe-like structures, and a phenomenon of wave-splitting is observed. Moreover, the same signand different magnitudes of the ionic charges can give rise to Turing-like stationary patterns from a homogeneous, stable, steady state depending upon the intensity of the applied electric field in the case of the Brusselator model. Our findings open the possibilities for future experiments to verify the predictions of electric field-induced various spatiotemporal instabilities in experimental reaction-diffusion systems.