Tag: pubmed

Chaos. 2022 Dec;32(12):121103. doi: 10.1063/5.0128743.

ABSTRACT

The role of topological heterogeneity in the origin of extreme events in a network is investigated here. The dynamics of the oscillators associated with the nodes are assumed to be identical and influenced by mean-field repulsive interactions. An interplay of topological heterogeneity and the repulsive interaction between the dynamical units of the network triggers extreme events in the nodes when each node succumbs to such events for discretely different ranges of repulsive coupling. A high degree node is vulnerable to weaker repulsive interactions, while a low degree node is susceptible to stronger interactions. As a result, the formation of extreme events changes position with increasing strength of repulsive interaction from high to low degree nodes. Extreme events at any node are identified with the appearance of occasional large-amplitude events (amplitude of the temporal dynamics) that are larger than a threshold height and rare in occurrence, which we confirm by estimating the probability distribution of all events. Extreme events appear at any oscillator near the boundary of transition from rotation to libration at a critical value of the repulsive coupling strength. To explore the phenomenon, a paradigmatic second-order phase model is used to represent the dynamics of the oscillator associated with each node. We make an annealed network approximation to reduce our original model and, thereby, confirm the dual role of the repulsive interaction and the degree of a node in the origin of extreme events in any oscillator associated with a node.

PMID:36587354 | DOI:10.1063/5.0128743

Chaos. 2022 Dec;32(12):122101. doi: 10.1063/5.0124274.

ABSTRACT

Sharp changes in state, such as transitions from survival to extinction, are hallmarks of evolutionary dynamics in biological systems. These transitions can be explored using the techniques of statistical physics and the physics of nonlinear and complex systems. For example, a survival-to-extinction transition can be characterized as a non-equilibrium phase transition to an absorbing state. Here, we review the literature on phase transitions in evolutionary dynamics. We discuss directed percolation transitions in cellular automata and evolutionary models, and models that diverge from the directed percolation universality class. We explore in detail an example of an absorbing phase transition in an agent-based model of evolutionary dynamics, including previously unpublished data demonstrating similarity to, but also divergence from, directed percolation, as well as evidence for phase transition behavior at multiple levels of the model system’s evolutionary structure. We discuss phase transition models of the error catastrophe in RNA virus dynamics and phase transition models for transition from chemistry to biochemistry, i.e., the origin of life. We conclude with a review of phase transition dynamics in models of natural selection, discuss the possible role of phase transitions in unraveling fundamental unresolved questions regarding multilevel selection and the major evolutionary transitions, and assess the future outlook for phase transitions in the investigation of evolutionary dynamics.

PMID:36587338 | DOI:10.1063/5.0124274

Chaos. 2022 Dec;32(12):123131. doi: 10.1063/5.0129066.

ABSTRACT

Noakes and Stoyanov [Mathematics 9, 2434 (2021)] introduced a method of recovering strictly convex planar obstacles from their set of traveling times. We provide an extension of this construction for obstacles on Riemannian surfaces under some general curvature conditions. It is required that no smooth geodesic intersects more than two obstacles.

PMID:36587331 | DOI:10.1063/5.0129066

Chaos. 2022 Dec;32(12):123136. doi: 10.1063/5.0097187.

ABSTRACT

White noise is a fundamental and fairly well understood stochastic process that conforms to the conceptual basis for many other processes, as well as for the modeling of time series. Here, we push a fresh perspective toward white noise that, grounded on combinatorial considerations, contributes to giving new interesting insights both for modeling and theoretical purposes. To this aim, we incorporate the ordinal pattern analysis approach, which allows us to abstract a time series as a sequence of patterns and their associated permutations, and introduce a simple functional over permutations that partitions them into classes encoding their level of asymmetry. We compute the exact probability mass function (p.m.f.) of this functional over the symmetric group of degree n, thus providing the description for the case of an infinite white noise realization. This p.m.f. can be conveniently approximated by a continuous probability density from an exponential family, the Gaussian, hence providing natural sufficient statistics that render a convenient and simple statistical analysis through ordinal patterns. Such analysis is exemplified on experimental data for the spatial increments from tracks of gold nanoparticles in 3D diffusion.

PMID:36587330 | DOI:10.1063/5.0097187

Chaos. 2022 Dec;32(12):123123. doi: 10.1063/5.0118404.

ABSTRACT

A fractional order susceptible-exposed-infected-quarantined-recovered model is established on the complex networks. We calculate a specific expression for the basic reproduction number R₀, prove the existence and uniqueness with respect to the solution, and prove the Ulam-Hyers stability of the model. Using the Latin hypercube sampling-partial rank correlation coefficient method, the influence of parameters on the R₀ is analyzed. Based on the results of the analysis, the optimal control of the model is investigated as the control variables with vaccination rate and quarantine rate applying Pontryagin’s minimum principle. The effects of α, degree of nodes, and network size on the model dynamics are simulated separately by the prediction correction method.

PMID:36587321 | DOI:10.1063/5.0118404

Chaos. 2022 Dec;32(12):123102. doi: 10.1063/5.0122184.

ABSTRACT

Key features of biological activity can often be captured by transitions between a finite number of semi-stable states that correspond to behaviors or decisions. We present here a broad class of dynamical systems that are ideal for modeling such activity. The models we propose are chaotic heteroclinic networks with nontrivial intersections of stable and unstable manifolds. Due to the sensitive dependence on initial conditions, transitions between states are seemingly random. Dwell times, exit distributions, and other transition statistics can be built into the model through geometric design and can be controlled by tunable parameters. To test our model’s ability to simulate realistic biological phenomena, we turned to one of the most studied organisms, C. elegans, well known for its limited behavioral states. We reconstructed experimental data from two laboratories, demonstrating the model’s ability to quantitatively reproduce dwell times and transition statistics under a variety of conditions. Stochastic switching between dominant states in complex dynamical systems has been extensively studied and is often modeled as Markov chains. As an alternative, we propose here a new paradigm, namely, chaotic heteroclinic networks generated by deterministic rules (without the necessity for noise). Chaotic heteroclinic networks can be used to model systems with arbitrary architecture and size without a commensurate increase in phase dimension. They are highly flexible and able to capture a wide range of transition characteristics that can be adjusted through control parameters.

PMID:36587320 | DOI:10.1063/5.0122184

Chaos. 2022 Dec;32(12):123124. doi: 10.1063/5.0125949.

ABSTRACT

While it is well known that the probability density for conventional stochastic differential equations can be obtained by numerically solving the corresponding Fokker-Planck equations, no feasible approaches have been reported to compute the probability density for stochastic differential equations with time delays. Lacking efficient algorithms to compute the probability density has greatly restricted the application of stochastic differential equations with time delays. A numerical method is developed in this paper to compute the probability density for stochastic differential equations with multiple time delays. It is shown that the proposed numerical method is of first order convergence with respect to time step. Numerical examples are presented to verify and illustrate the proposed method.

PMID:36587317 | DOI:10.1063/5.0125949

Chaos. 2022 Dec;32(12):123135. doi: 10.1063/5.0131433.

ABSTRACT

This paper focuses on the averaging principle of Caputo fractional stochastic differential equations (SDEs) with multiplicative fractional Brownian motion (fBm), where Hurst parameter 1/2<H<1 and the integral of fBm as a generalized Riemann-Stieltjes integral. Under suitable assumptions, the averaging principle on Hölder continuous space is established by giving the estimate of Hölder norm. Specifically, we show that the solution of the original fractional SDEs converges to the solution of the proposed averaged fractional SDEs in the mean square sense and gives an example to illustrate our result.

PMID:36587315 | DOI:10.1063/5.0131433

Acad Emerg Med. 2023 Jan 1. doi: 10.1111/acem.14651. Online ahead of print.

ABSTRACT

BACKGROUND: Reported risk of bleeding complications after central catheter access in patients with thrombocytopenia is highly variable. Current guidelines recommend routine prophylactic platelet transfusion before central venous catheter placement in patients with severe thrombocytopenia. Nevertheless, strength of such recommendations is weak and supported by observational studies including few patients with very low platelet counts (PLT < 20×10⁹ /L). This study aims to assess the risk of bleeding complications related to using or not using prophylactic platelet transfusion before ultrasound-guided central venous access in patients with very low platelet counts.

METHODS: This was a retrospective cohort study of patients with very low PLT counts (PLT< 20×10⁹ /L) subjected to ultrasound-guided central venous catheterization between January 2011 and November 2019 in a university hospital. Bleeding complications were graded according to the Common Terminology Criteria for Adverse Events. A multivariate logistic regression was conducted to assess the risk of major and minor bleeding complications comparing patients who did or did not receive prophylactic platelet transfusion for the procedure. Multiple imputation by chained equations was used to handle missing data. A 2-tailed P < .05 was considered statistically significant.

RESULTS: Among 221 patients with very low platelets, 72 received prophylactic platelet transfusions while 149 did not. Baseline characteristics were similar between transfused and non-transfused patients. No major bleeding events were identified, while minor bleeding events were recognized in 35.7% of patients. Multivariate logistic regression analysis showed no significant differences in bleeding complications between patients who received prophylactic platelet transfusions and those who did not (OR 0.83, 95% CI 0.45-1.55, p= 0.567). Additional complete case and sensitivity analyses yielded similar results to the main analysis.

CONCLUSIONS: In this single center retrospective cohort study of ultrasound-guided central venous access in patients with very low platelet counts, no major bleeding was identified, and prophylactic platelet transfusions did not significantly decrease minor bleeding events.

PMID:36587310 | DOI:10.1111/acem.14651

Cephalalgia. 2023 Jan;43(1):3331024221131331. doi: 10.1177/03331024221131331.

ABSTRACT

OBJECTIVE: To compare clinical features in youth with continuous headache from migraine, persistent post-traumatic headache, and new daily persistent headache to determine if they are similar, contrary to their distinction in the International Classification of Headache Disorders.

METHODS: We pursued a single center age- and sex-matched observational study comparing the clinical characteristics of 150 youth (11 – 17 years old) with continuous headache from migraine, persistent post-traumatic headache, and new daily persistent headache. A diagnostic algorithm based on international classification of headache disorders criteria was used to identify those with migraine (headache features of migraine with gradual onset), and persistent post-traumatic headache and new daily persistent headache (based on the circumstances of headache onset regardless of headache features). Fifty participants each with migraine, persistent post-traumatic headache, and new daily persistent headache were matched by age and sex. Participant survey responses on headache characteristics were compared.

RESULTS: Median usual headache severity was 6.0 [95%CI 6.0, 6.0] and was not different across diagnostic groups (H statistic = 1.2, p = 0.55). Headache exacerbation frequency, disability, associated symptoms, and most triggers were not significantly different across groups. The majority of persistent post-traumatic headache and new daily persistent headache had headache features consistent with a diagnose of migraine (72% and 62%, respectively).

CONCLUSION: Our findings suggest that most persistent post-traumatic headache and new daily persistent headache may represent abrupt onset of migraine.

PMID:36587297 | DOI:10.1177/03331024221131331