We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.
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http://dx.doi.org/10.1103/PhysRevE.93.032209 | DOI Listing |
Sci Rep
January 2025
Department of Medicine, Surgery and Dentistry, Center for Neurodegenerative Diseases (CEMAND), University of Salerno, Fisciano, Italy.
Subtle gait and cognitive dysfunction are common in Parkinson's disease (PD), even before most evident clinical manifestations. Such alterations can be assumed as hypothetical phenotypical and prognostic/progression markers. To compare spatiotemporal gait parameters in PD patients with three cognitive status: cognitively intact (PD-noCI), with subjective cognitive impairment (PD-SCI) and with mild cognitive impairment (PD-MCI) in order to detect subclinical gait differences.
View Article and Find Full Text PDFNeural Netw
January 2025
Defense Innovation Institute, Chinese Academy of Military Science, Beijing 100071, China; Intelligent Game and Decision Laboratory, China.
The Physics-informed Neural Network (PINN) has been a popular method for solving partial differential equations (PDEs) due to its flexibility. However, PINN still faces challenges in characterizing spatio-temporal correlations when solving parametric PDEs due to network limitations. To address this issue, we propose a Physics-Informed Neural Implicit Flow (PINIF) framework, which enables a meshless low-rank representation of the parametric spatio-temporal field based on the expressiveness of the Neural Implicit Flow (NIF), enabling a meshless low-rank representation.
View Article and Find Full Text PDFBioengineering (Basel)
January 2025
Biomechanics Laboratory, Division of Sport and Exercise, School of Health and Life Sciences, University of the West of Scotland, Paisley PA1 2BE, UK.
Golfers must modify their motor patterns when the demands of a putting task change. The objective was to compare joint angles and putter kinematics during putting at two distances and inclines. Recreational golfers ( = 14) completed putts over four conditions: 3-foot putts on flat and incline surfaces, and 7-foot putts on flat and incline surfaces.
View Article and Find Full Text PDFMagn Reson Med
January 2025
Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Purpose: To develop a deep subspace learning network that can function across different pulse sequences.
Methods: A contrast-invariant component-by-component (CBC) network structure was developed and compared against previously reported spatiotemporal multicomponent (MC) structure for reconstructing MR Multitasking images. A total of 130, 167, and 16 subjects were imaged using T, T-T, and T-T- -fat fraction (FF) mapping sequences, respectively.
Med Sci Monit
January 2025
Department of Physical Education, Pusan National University, Busan, South Korea.
BACKGROUND The VICON Toolkit enables three-dimensional (3D) motion capture for gait analysis. Statistical parametric mapping (SPM) is a voxel-based neuroimaging approach used to identify region-specific effects. This study aimed to apply SPM to analyze the joint angles of the hip, knee, and ankle during gait in 20 post-stroke patients using the VICON motion capture system.
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