We examine the time-dependent behavior of a nonlinear system driven by a two-frequency forcing. By using a nonperturbative approach, we are able to derive an asymptotic expression, valid in the long-time limit, for the time average of the output variable which describes the response of the system. We identify several universal features of the asymptotic response of the system, which are independent of the details of the model. In particular, we determine an asymptotic expression for the width of the resonance observed by keeping one frequency fixed and varying the other one. We show that this width is smaller than the usually assumed Fourier width by a factor determined by the two driving frequencies, and independent of the model system parameters. Additional general features can also be identified depending on the specific symmetry properties of the system. Our results find direct application in the study of sub-Fourier signal processing with nonlinear systems.
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http://dx.doi.org/10.1103/PhysRevE.88.062919 | DOI Listing |
Cardiovasc Eng Technol
January 2025
Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA.
Purpose: This study explores the use of heart rate variability (HRV) analysis, a noninvasive technique for assessing the autonomic nervous system, by applying nonlinear dynamics and chaos theory to detect chaotic behavior in RR intervals and assess cardiovascular health.
Methods: Employing the "System Analysis of Heart Rate Dynamics" (SADR) program, this research combines chaos analysis with the short-time Fourier transform to assess nonlinear dynamic parameters in HRV. It includes constructing phase portraits in Takens space and calculating measures of chaos to identify deterministic chaos indicators.
Sci Rep
January 2025
Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, P.O. Box 2457, 11451, Riyadh, Saudi Arabia.
This study focuses on the use of machine learning (ML) models to predict the biodistribution of nanoparticles in various organs, using a dataset derived from research on nanoparticle behavior for cancer treatment. The dataset includes both categorical and numerical variables related to nanoparticle properties, with a focus on their distribution across organs such as the tumor, heart, liver, spleen, lung, and kidney tissues. In order to address the complex and non-linear nature of the data, three machine learning models were utilized: Bayesian Ridge Regression (BRR), Kernel Ridge Regression (KRR), and K-Nearest Neighbors (KNN).
View Article and Find Full Text PDFInt J Biol Macromol
January 2025
Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-products Processing, Ministry of Agriculture and Rural Affairs, Beijing 100193, China; Institute of Western Agriculture, Chinese Academy of Agricultural Sciences, Changji 831100, China. Electronic address:
This work prepared the soy protein isolate (SPI)-beeswax-based bigel loaded with β-carotene, and the effect of printing temperature (PT) on texture regulation was investigated. During printing, increasing PT weakened the rheological properties and printability of ink. However, the mechanical strength and deformation resistance at non-linear regions of products were strengthened after printing.
View Article and Find Full Text PDFChaos
January 2025
School of Public Health, Chongqing Medical University, Chongqing 400016, China.
The impact of resource allocation on the dynamics of epidemic spreading is an important topic. In real-life scenarios, individuals usually prioritize their own safety, and this self-protection consciousness will lead to delays in resource allocation. However, there is a lack of systematic research on the impact of resource allocation delay on epidemic spreading.
View Article and Find Full Text PDFData Brief
December 2024
Complex System Group & GISC, Universidad Rey Juan Carlos, Madrid, 28933, Spain.
Some real-world phenomena and human-made problems have been modeled as networks where the objects form pairwise interactions. However, this is a limited approach when the existence of high-order interactions is inherent in a system, such as the brain, social networks and ecosystems. The way in which these high-order interactions affect the collective behavior of a complex system is still an open question.
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