Chaos最新文献 - Book学术

A compounded Burr probability distribution for fitting heavy-tailed data with applications to biological networks. 重尾数据拟合的复合Burr概率分布及其在生物网络中的应用。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0270403

Tanujit Chakraborty, Swarup Chattopadhyay, Suchismita Das, Shraddha M Naik, Chittaranjan Hens

{"title":"A compounded Burr probability distribution for fitting heavy-tailed data with applications to biological networks.","authors":"Tanujit Chakraborty, Swarup Chattopadhyay, Suchismita Das, Shraddha M Naik, Chittaranjan Hens","doi":"10.1063/5.0270403","DOIUrl":"https://doi.org/10.1063/5.0270403","url":null,"abstract":"Complex biological networks, encompassing metabolic pathways, gene regulatory systems, and protein-protein interaction networks, often exhibit scale-free structures characterized by heavy-tailed degree distributions. However, empirical studies reveal significant deviations from ideal power-law behavior, underscoring the need for more flexible and accurate probabilistic models. In this work, we propose the Compounded Burr (CBurr) distribution, a novel four-parameter family derived by compounding the Burr distribution with a discrete mixing process. This model is specifically designed to capture both the body and tail behavior of real-world network degree distributions with applications to biological networks. We rigorously derive its statistical properties, including moments, hazard and risk functions, and tail behavior, and develop an efficient maximum likelihood estimation framework. The CBurr model demonstrates broad applicability to networks with complex connectivity patterns, particularly in biological, social, and technological domains. Extensive experiments on large-scale biological network datasets show that CBurr consistently outperforms classical power-law, lognormal, and other heavy-tailed models across the full degree spectrum. By providing a statistically grounded and interpretable framework, the CBurr model enhances our ability to characterize the structural heterogeneity of biological networks.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144198331","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

Formation and suppression of hotspots in urban crime models with law enforcement. 形成和打击城市犯罪热点与执法模式。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0273298

Madi Yerlanov, Qi Wang, Nancy Rodríguez

引用次数: 0

A mathematical model of CAR-T cell therapy in combination with chemotherapy for malignant gliomas. CAR-T细胞联合化疗治疗恶性胶质瘤的数学模型。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0260252

Dmitry Sinelshchikov, Juan Belmonte-Beitia, Matteo Italia

{"title":"A mathematical model of CAR-T cell therapy in combination with chemotherapy for malignant gliomas.","authors":"Dmitry Sinelshchikov, Juan Belmonte-Beitia, Matteo Italia","doi":"10.1063/5.0260252","DOIUrl":"https://doi.org/10.1063/5.0260252","url":null,"abstract":"Malignant gliomas (MGs) are among the most aggressive primary brain tumors, characterized by a high degree of resistance to therapy and poor prognosis. In this work, we develop a mathematical model to investigate the dynamics of MG under the combined effects of chemotherapy and chimeric antigen receptor cell therapy. The proposed model is a five-dimensional dynamical system incorporating impulsive inputs that correspond to the clinical administration of chemotherapy and immunotherapy. We demonstrate the non-negativity of solutions for non-negative initial conditions, ensuring the biological relevance of the model. We show that if we apply both therapies only once, the trajectories are attracted to an invariant surface corresponding to the tumor carrying capacity. Conversely, under constant administration of both treatments, we identify parameter ranges in which tumor eradication is achievable. Furthermore, we numerically study various treatment combinations to determine optimal protocols at the population level. To this end, we generate a cohort of 104 virtual patients with model parameters sampled uniformly within clinically relevant ranges and carry out in silico trials. Our findings indicate that tumor growth rate, chemotherapy efficacy, and tumor-induced immunosuppression are the key determinants of survival outcomes. We believe that our results provide new theoretical insights into treatment optimization and offer a framework for refining the design of clinical trials for MG therapies.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144198332","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

Physics-driven deep learning methods and numerically intractable "bad" Jaulent-Miodek equation. 物理驱动的深度学习方法和数值棘手的“坏”Jaulent-Miodek方程。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0264041

Jing-Jing Su, Gao-Liang Tao, Ran Li, Sheng Zhang

{"title":"Physics-driven deep learning methods and numerically intractable \"bad\" Jaulent-Miodek equation.","authors":"Jing-Jing Su, Gao-Liang Tao, Ran Li, Sheng Zhang","doi":"10.1063/5.0264041","DOIUrl":"https://doi.org/10.1063/5.0264041","url":null,"abstract":"The \"bad\" Jaulent-Miodek (JM) equation serves to describe the motion of non-viscous shallow water wave packets in a flat-bottomed domain subject to shear forces. The \"bad\" JM equation exhibits poor properties, characterized by the linear instability of nonlinear waves on the zero-plane background, rendering it challenging to solve through traditional analytical and numerical methods. In this paper, two classic physics-driven deep learning approaches, namely, Physics-Informed Neural Networks (PINN) and Physics and Equality-Constrained Artificial Neural Networks (PECANN), are combined into a two-stage \"PINN+PECANN\" neural network to address the nonlinear wave evolution on the zero-plane background for the \"bad\" JM equation. The two-stage \"PINN+PECANN\" neural network method employs PINN in the first stage to pre-train the neural network, followed by fine-tuning of the network parameters using PECANN in the second stage. This approach not only correctly obtains solutions to the \"bad\" JM equation but also enhances computational efficiency. Specifically, we present the evolutionary behavior of nonlinear waves for the common initial values of the \"bad\" JM equation: Gauss wave packets, sech wave packets, and rational wave packets. Furthermore, the nonlinear interactions between two Gauss, sech, rational wave packets are provided. The results in this paper validate the advantages of physics-driven deep learning methods in solving equations with poor properties and open up a new pathway for obtaining unstable solutions of nonlinear equations.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144198355","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

Blink it to sync it: Experimental evidence of synchronization of human brainwaves subjected to common photic forcing. 眨眼使其同步：在普通光强迫下，人类脑电波同步的实验证据。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0276609

Aarsh Chotalia, Sapna Yadav, Richa Phogat, P Parmananda

引用次数: 0

Fractional Bloch oscillations. 分数阶Bloch振荡。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0275519

Mario I Molina

引用次数: 0

On the nature of nonequilibrium phase transition in a complex system. 复杂系统中非平衡相变的性质。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0265336

Sivakumar Sudarsanan, Induja Pavithran, R I Sujith

{"title":"On the nature of nonequilibrium phase transition in a complex system.","authors":"Sivakumar Sudarsanan, Induja Pavithran, R I Sujith","doi":"10.1063/5.0265336","DOIUrl":"https://doi.org/10.1063/5.0265336","url":null,"abstract":"The transition from a chaotic to a periodic oscillatory state can be smooth or abrupt in real-world complex systems. We study smooth and abrupt transitions in a turbulent reactive flow system. The turbulent reactive flow system consists of the flame, the acoustic field, and the hydrodynamic field interacting nonlinearly. Generally, as the Reynolds number is increased, a laminar flow becomes turbulent, and the range of time scales associated with the flow broadens. Yet, as the Reynolds number is increased in a turbulent reactive flow system, a single dominant time scale emerges in the acoustic pressure oscillations. By varying the Reynolds number at different rates, we observe smooth and abrupt transitions from chaos to order. For such smooth and abrupt transitions, we study the evolution of correlated (conformists and contrarians) and uncorrelated (disordered) dynamics between the acoustic pressure and the heat release rate oscillations in the spatiotemporal domain of the turbulent reactive flow system. We discover that the spatial extent of the disordered dynamics plays a critical role in deciding the abruptness of the transition. During the smooth transition, we observe a significant presence of disordered dynamics in the spatial domain. In contrast, abrupt transitions are accompanied by the abrupt disappearance of disordered dynamics from the spatial domain.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144198354","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

Chaotic dynamics and control in a discrete predation model with Holling II and prey refuge effects. 具有Holling II和猎物庇护效应的离散捕食模型的混沌动力学与控制。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0260237

Rabia Mehdi, Ranchao Wu, Zakia Hammouch

{"title":"Chaotic dynamics and control in a discrete predation model with Holling II and prey refuge effects.","authors":"Rabia Mehdi, Ranchao Wu, Zakia Hammouch","doi":"10.1063/5.0260237","DOIUrl":"https://doi.org/10.1063/5.0260237","url":null,"abstract":"Understanding predator-prey interactions is crucial for modeling ecological systems. This study investigates a discrete-time predator-prey system with a Holling type II functional response and prey refuge. Linear stability analysis establishes existence conditions and stability criteria for equilibrium points, while bifurcation analysis reveals critical transitions through period-doubling and Neimark-Sacker bifurcations. The center manifold theorem facilitates dimensionality reduction, enabling precise characterization of local dynamics near bifurcation points. Comprehensive numerical simulations-including bifurcation diagrams, phase portraits, maximum Lyapunov exponents, and time series-validate theoretical predictions and uncover complex behavioral regimes. A state feedback control strategy, derived from triangular stability regions, effectively suppresses chaotic fluctuations and stabilizes the system. These results advance fundamental understanding of ecological dynamics while offering practical stabilization techniques, bridging mathematical theory with applied ecological management. The interdisciplinary framework provides actionable insights for maintaining balance in complex ecological systems.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144246717","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

Two types of elliptic dark soliton solutions for the Hirota equation. Hirota方程的两类椭圆型暗孤子解。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0268266

Qiaofeng Huang, Xuan Sun

引用次数: 0

Empirical study and model of warfare dynamics: Willingness to risk. 战争动力学的实证研究与模型：冒险意愿。

IF 2.7 2区数学

Chaos Pub Date : 2025-06-01 DOI: 10.1063/5.0277615

Boris Podobnik, Luka Medvidovic, Dorian Wild, Stefano Boccaletti

{"title":"Empirical study and model of warfare dynamics: Willingness to risk.","authors":"Boris Podobnik, Luka Medvidovic, Dorian Wild, Stefano Boccaletti","doi":"10.1063/5.0277615","DOIUrl":"https://doi.org/10.1063/5.0277615","url":null,"abstract":"Economists often highlight a gross domestic product (GDP) as a key metric in determining war outcomes, despite historical exceptions, such as the Taliban's victories over the Soviet and U.S. armies in Afghanistan-nations with vastly superior GDPs. Two critical factors that remain underexplored are the soldier's willingness to sacrifice for their country and a country's willingness to risk nuclear war. To address this gap, we conducted a worldwide survey to assess the maximum acceptable level of losses respondents would tolerate in their own country for varying levels of enemy losses. The findings were surprising: respondents, on average, considered 23% casualties (with a median of 10%) as an acceptable loss if it meant 100% destruction of the enemy. To determine which nuclear power might be more inclined to initiate a nuclear war, we introduce the willingness to risk ratio, defined as the ratio between the GDP that can be destroyed in enemy countries and the GDP that could be destroyed by the enemy in one's own country. Recognizing that conventional wars can serve as a pretext for a nuclear conflict between two nuclear powers, S and S', we developed a network model where bravery is defined at the micro level of individual soldiers, whereas defeatism can spread contagiously throughout the network. If due to increasing aid of the nuclear power S' to a weaker country W, the opposing nuclear power S suffers heavier casualties, the probability of the nuclear catastrophe P surges, prompting S and S' to start weighing between a nuclear-war scenario and continuation of the proxy war. In this case, the increase of P ramps up the chance that the power S', geographically farther to the spot of conflict, stops supporting W since it is less willing to risk nuclear war and in economic terms, S' may lose more than S if the war escalates.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"35 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144265388","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