Notes

Blended term associated with aldehyde dehydrogenase 1A1 along with β-catenin is owned by lymph node metastasis along with inadequate tactical throughout breast cancer sufferers following cyclophosphamide therapy.
Second, the modulated envelope structures such as freak waves (FWs) are investigated in the framework of the Gardner equation by transforming this equation to the nonlinear Schrödinger equation (NLSE). Again, the ADM is used to solve the NLSE for studying FWs numerically. Furthermore, the effect of physical parameters of the plasma environment (e.g., Ar+-SF5 +-F--SF5 - plasma) on the characteristics of the nonlinear pulse profile is elaborated. These results help in a better understanding of the fundamental mechanisms of fluid physics governing the plasma processes.In this work, we have investigated the evolutionary dynamics of a generalist pathogen, e.g., a virus population, that evolves toward specialization in an environment with multiple host types. We have particularly explored under which conditions generalist viral strains may rise in frequency and coexist with specialist strains or even dominate the population. By means of a nonlinear mathematical model and bifurcation analysis, we have determined the theoretical conditions for stability of nine identified equilibria and provided biological interpretation in terms of the infection rates for the viral specialist and generalist strains. By means of a stability diagram, we identified stable fixed points and stable periodic orbits, as well as regions of bistability. For arbitrary biologically feasible initial population sizes, the probability of evolving toward stable solutions is obtained for each point of the analyzed parameter space. This probability map shows combinations of infection rates of the generalist and specialist strains that might lead to equal chances for each type becoming the dominant strategy. Furthermore, we have identified infection rates for which the model predicts the onset of chaotic dynamics. Several degenerate Bogdanov-Takens and zero-Hopf bifurcations are detected along with generalized Hopf and zero-Hopf bifurcations. This manuscript provides additional insights into the dynamical complexity of host-pathogen evolution toward different infection strategies.In many real-life systems, transient chaotic dynamics plays a major role. For instance, the chaotic spiral or scroll wave dynamics of electrical excitation waves during life-threatening cardiac arrhythmias can terminate by itself. Epileptic seizures have recently been related to the collapse of transient chimera states. Controlling chaotic transients, either by maintaining the chaotic dynamics or by terminating it as quickly as possible, is often desired and sometimes even vital (as in the case of cardiac arrhythmias). We discuss in this study that the difference of the underlying structures in state space between a chaotic attractor (persistent chaos) and a chaotic saddle (transient chaos) may have significant implications for efficient control strategies in real life systems. In particular, we demonstrate that in the latter case, chaotic dynamics in spatially extended systems can be terminated via a relatively low number of (spatially and temporally) localized perturbations. We demonstrate as a proof of principle that control and targeting of high-dimensional systems exhibiting transient chaos can be achieved with exceptionally small interactions with the system. This insight may impact future control strategies in real-life systems like cardiac arrhythmias.In this paper, a new meminductor model with sine function is presented. Based on this meminductor and a capacitor, a simple conservative chaotic system is designed. The proposed system has rich dynamic characteristics, including zero divergence, self-reproducing chaos, bursting oscillations, and symmetric Lyapunov exponent spectra. selleck compound The corresponding mechanisms of these dynamic behaviors are analyzed theoretically. Furthermore, Multisim simulations and experimental circuit are performed to verify the numerical results.Since 2012, the semiarid region of Northeast Brazil (NEB) has been experiencing a continuous dry condition imposing significant social impacts and economic losses. Characterizing the recent extreme drought events and uncovering the influence from the surrounding oceans remain to be big challenges. The physical mechanisms of extreme drought events in the NEB are due to varying interacting time scales from the surrounding tropical oceans (Pacific and Atlantic). From time series observations, we propose a three-step strategy to establish the episodic coupling directions on intraseasonal time scales from the ocean to the precipitation patterns in the NEB, focusing on the distinctive roles of the oceans during the recent extreme drought events of 2012-2013 and 2015-2016. Our algorithm involves the following (i) computing drought period length from daily precipitation anomalies to capture extreme drought events; (ii) characterizing the episodic coupling delays from the surrounding oceans to the precipitation by applying the Kullback-Leibler divergence (KLD) of complexity measure, which is based on ordinal partition transition network representation of time series; and (iii) calculating the ratio of high temperature in the ocean during the extreme drought events with proper time lags that are identified by KLD measures. From the viewpoint of climatology, our analysis provides data-based evidence of showing significant influence from the North Atlantic in 2012-2013 to the NEB, but in 2015-2016, the Pacific played a dominant role than that of the Atlantic. The episodic intraseasonal time scale properties are potential for monitoring and forecasting droughts in the NEB in order to propose strategies for drought impacts reduction.A novel general randomized method is proposed to investigate multifractal properties of long time series. Based on multifractal temporally weighted detrended fluctuation analysis (MFTWDFA), we obtain randomized multifractal temporally weighted detrended fluctuation analysis (RMFTWDFA). The innovation of this algorithm is applying a random idea in the process of dividing multiple intervals to find the local trend. To test the performance of the RMFTWDFA algorithm, we apply it, together with the MFTWDFA, to the artificially generated time series and real genomic sequences. For three types of artificially generated time series, consistency tests are performed on the estimated h(q), and all results indicate that there is no significant difference in the estimated h(q) of the two methods. Meanwhile, for different sequence lengths, the running time of RMFTWDFA is reduced by over ten times. We use prokaryote genomic sequences with large scales as real examples, the results obtained by RMFTWDFA demonstrate that these genomic sequences show fractal characteristics, and we leverage estimated exponents to study phylogenetic relationships between species.
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