IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0234904

Silvio L T de Souza, Antonio M Batista, Rene O Medrano-T, Iberê L Caldas

引用次数: 0

Chaotic property in general fractional calculus. 一般分数阶微积分中的混沌性质。

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0243475

Anatoly N Kochubei

引用次数: 0

Finding bifurcations in mathematical epidemiology via reaction network methods. 通过反应网络方法寻找数学流行病学中的分岔。

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0221082

N Vassena, F Avram, R Adenane

引用次数: 0

Fast-slow analysis and bifurcations in the generation of the early afterdepolarization phenomenon in a realistic mathematical human ventricular myocyte model. 一个真实的人心室肌细胞数学模型中早期后去极化现象产生的快慢分析和分支。

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0230834

Hiroyuki Kitajima, Toru Yazawa, Roberto Barrio

引用次数: 0

Introduction to Focus Issue: Chimera states: From theory and experiments to technology and living systems. 焦点问题导论：奇美拉状态：从理论和实验到技术和生命系统。

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0249682

Jörn Davidsen, Yuri Maistrenko, Kenneth Showalter

引用次数: 0

Brownian non-Gaussian polymer diffusion in non-static media. 非静态介质中的布朗非高斯聚合物扩散。

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0232075

Xiao Zhang, Heng Wang, Weihua Deng

{"title":"Brownian non-Gaussian polymer diffusion in non-static media.","authors":"Xiao Zhang, Heng Wang, Weihua Deng","doi":"10.1063/5.0232075","DOIUrl":"https://doi.org/10.1063/5.0232075","url":null,"abstract":"In nature, essentially, almost all the particles move irregularly in non-static media. With the advance of observation techniques, various kinds of new dynamical phenomena are detected, e.g., Brownian non-Gaussian diffusion. This paper focuses on the dynamical behavior of the center of mass (CM) of a polymer in non-static media and investigates the effect of polymer size fluctuations on the diffusion behavior. First, we establish a diffusing diffusivity model for polymer size fluctuations, linking the polymer size variation to the birth and death process, and introduce co-moving and physical coordinate systems to characterize the position of the CM for a polymer in non-static media. Next, the important statistical quantities for the CM diffusing diffusivity model in non-static media, such as mean square displacement (MSD) and kurtosis, are obtained by adopting the subordinate process approach, and the long-time asymptotic behavior of the MSD in the media of different types is specifically analyzed. Finally, the bivariate Fokker-Planck equation and the Feynman-Kac equation corresponding to the diffusing diffusivity model are detailedly derived and solved through the deep backward stochastic differential equation (BSDE) method to confirm the correctness of the derived equations.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"34 12","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142821972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic patterns in herding predator-prey system: Analyzing the impact of inertial delays and harvesting. 放牧捕食-猎物系统的动态模式：惯性延迟和收获的影响分析。

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0239612

Santanu Bhattacharya, Santu Ghorai, Nandadulal Bairagi

{"title":"Dynamic patterns in herding predator-prey system: Analyzing the impact of inertial delays and harvesting.","authors":"Santanu Bhattacharya, Santu Ghorai, Nandadulal Bairagi","doi":"10.1063/5.0239612","DOIUrl":"https://doi.org/10.1063/5.0239612","url":null,"abstract":"This study expands traditional reaction-diffusion models by incorporating hyperbolic dynamics to explore the effects of inertial delays on pattern formation. The kinetic system considers a harvested predator-prey model where predator and prey populations gather in herds. Diffusion and inertial effects are subsequently introduced. Theoretical frameworks establish conditions for stability, revealing that inertial delay notably alters diffusion-induced instabilities and Hopf bifurcations. The inclusion of inertial effects narrows the stability region of the kinetic system by wave instability, which cannot arise in a two-variable spatiotemporal system without inertia. Computational simulations demonstrate that Turing and wave instabilities lead to diverse spatial and spatiotemporal patterns. This study highlights that initial conditions influence wave instability, generating distinct patterns based on different initial values, while other instabilities remain unaffected. Additionally, patterns, such as hot spots, cold spots, and stripes, are observed within the Turing region. The impact of harvesting on spatiotemporal system stability is also examined, showing that increased harvesting efforts can shift systems between unstable and uniform states. The findings provide practical implications for ecological modeling, offering insights into how inertial delays and harvesting practices affect pattern formation in natural populations.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"34 12","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142881335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Synchronization transitions in adaptive simplicial complexes with cooperative and competitive dynamics. 具有合作和竞争动态的自适应简单复合物中的同步转换。

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0226199

S Nirmala Jenifer, Dibakar Ghosh, Paulsamy Muruganandam

{"title":"Synchronization transitions in adaptive simplicial complexes with cooperative and competitive dynamics.","authors":"S Nirmala Jenifer, Dibakar Ghosh, Paulsamy Muruganandam","doi":"10.1063/5.0226199","DOIUrl":"https://doi.org/10.1063/5.0226199","url":null,"abstract":"Adaptive network is a powerful presentation to describe different real-world phenomena. However, current models often neglect higher-order interactions (beyond pairwise interactions) and diverse adaptation types (cooperative and competitive) commonly observed in systems such as the human brain and social networks. This work addresses this gap by incorporating these factors into a model that explores their impact on collective properties such as synchronization. Through simplified network representations, we investigate how the simultaneous presence of cooperative and competitive adaptations influences phase transitions. Our findings reveal a transition from first-order to second-order synchronization as the strength of higher-order interactions increases under competitive adaptation. We also demonstrate the possibility of synchronization even without pairwise interactions, provided there is strong enough higher-order coupling. When only competitive adaptations are present, the system exhibits second-order-like phase transitions and clustering. Conversely, with a combination of cooperative and competitive adaptations, the system undergoes a first-order-like phase transition, characterized by a sharp transition to the synchronized state without reverting to an incoherent state during backward transitions. The specific nature of these second-order-like transitions varies depending on the coupling strengths and mean degrees. With our model, we can control not only when the system synchronizes but also the way the system goes to synchronization.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"34 12","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142845836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detection of Parkinson's disease using nocturnal breathing signals based on multifractal detrended fluctuation analysis. 基于多重分形去趋势波动分析的夜间呼吸信号检测帕金森病。

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0237878

Zhong Dai, Shutang Liu, Changan Liu

{"title":"Detection of Parkinson's disease using nocturnal breathing signals based on multifractal detrended fluctuation analysis.","authors":"Zhong Dai, Shutang Liu, Changan Liu","doi":"10.1063/5.0237878","DOIUrl":"https://doi.org/10.1063/5.0237878","url":null,"abstract":"Parkinson's disease (PD) is a highly prevalent neurodegenerative disorder that poses a significant challenge in terms of accurate and cost-effective diagnosis. This study focuses on the use of fractal features derived from nocturnal breathing signals to diagnose PD. Our study includes 49 individuals with Parkinson's disease (PD group), 49 relatively healthy individuals without PD (HC group), 49 individuals without PD but with other diseases (NoPD group), as well as 12 additional PD patients and 200 healthy individuals for testing. Using multifractal detrended fluctuation analysis, we extracted fractal features from nocturnal breathing signals, with logistic regression models applied to diagnose PD, as demonstrated in receiver operating characteristic curves. Eight fractal features show significant diagnostic potential for PD, including generalized Hurst exponents for the Airflow, Thorax, and Abdomen signals and the multifractal spectrum width of the SaO2 signal. Finally, the area under the receiver operating characteristic curve (AUC) of the training data set of the PD and HC groups for all four signals is 0.911, and the AUC of the testing data set is 0.929. These results demonstrate the potential of this work to enhance the accuracy of PD diagnosis in clinical settings.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"34 12","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142821974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Resilience of the Atlantic meridional overturning circulation. 大西洋经向翻转环流的恢复力。

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0226410

Valérian Jacques-Dumas, Henk A Dijkstra, Christian Kuehn

引用次数: 0

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