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Fits associated with depressive disposition among graduate-level allied wellbeing college students: An exploratory review looking at feature electricity along with tiredness.
The output of our method can be straightforwardly used to calculate concepts, such as basin stability and final state sensitivity.The objective of this paper is the study of the dynamical properties analysis of an original specification of the classical Cournot heterogeneous model with optimal response; specifically, a new approach that considers ordinal utility instead of cardinal monetary amounts is proposed where the classical decision of quantity is disentangled from the decision on imitation. The analysis is performed by means of bifurcation diagrams, the 0-1 test for chaos, power spectral density, histograms, and trajectory analysis. For this purpose, a new perturbation parameter ε of the initial condition is introduced, and together with the intensity of choice parameter β determining the share of responders vs imitators, the system is researched. Depending on ε and β, extreme reach dynamics, and coexisting attractors, periodic and chaotic trajectories are investigated through massive simulations. Those dynamics represent alternation between stability, cycles and chaos in the market. As the dynamics are completely endogenous, it means that swings in economy are intrinsic to the system and that they may persist unless controlled.A reservoir computer is a way of using a high dimensional dynamical system for computation. One way to construct a reservoir computer is by connecting a set of nonlinear nodes into a network. Because the network creates feedback between nodes, the reservoir computer has memory. If the reservoir computer is to respond to an input signal in a consistent way (a necessary condition for computation), the memory must be fading; that is, the influence of the initial conditions fades over time. How long this memory lasts is important for determining how well the reservoir computer can solve a particular problem. In this paper, I describe ways to vary the length of the fading memory in reservoir computers. Tuning the memory can be important to achieve optimal results in some problems; too much or too little memory degrades the accuracy of the computation.At present, network science can be considered one of the prosperous scientific fields. The multi-layered network approach is a recent development in this area and focuses on identifying the interactions of several interconnected networks. In this paper, we propose a new method for predicting redundant links for multiplex networks using the similarity criterion based on the hyperbolic distance of the node pairs. We retrieve lost links found on various attack strategies in multiplex networks by predicting redundant links in these networks using the proffered method. We applied the recommended algorithm to real-world multiplex networks, and the numerical simulations show its superiority over other advanced algorithms. During the studies and numerical simulations, the power of the hyperbolic geometry criterion over different standard and current methods based on link prediction used for network retrieval is evident, especially in the case of attacks based on the edge betweenness and random strategies illustrated in the results.Vertically vibrating a liquid bath can give rise to a self-propelled wave-particle entity on its free surface. The horizontal walking dynamics of this wave-particle entity can be described adequately by an integro-differential trajectory equation. By transforming this integro-differential equation of motion for a one-dimensional wave-particle entity into a system of ordinary differential equations (ODEs), we show the emergence of Lorenz-like dynamical systems for various spatial wave forms of the entity. Specifically, we present and give examples of Lorenz-like dynamical systems that emerge when the wave form gradient is (i) a solution of a linear homogeneous constant coefficient ODE, (ii) a polynomial, and (iii) a periodic function. Understanding the dynamics of the wave-particle entity in terms of Lorenz-like systems may prove to be useful in rationalizing emergent statistical behavior from underlying chaotic dynamics in hydrodynamic quantum analogs of walking droplets. Moreover, the results presented here provide an alternative physical interpretation of various Lorenz-like dynamical systems in terms of the walking dynamics of a wave-particle entity.Most previous studies focused on the giant component to explore the structural robustness of complex networks under malicious attacks. As an important failure mode, localized attacks (LA) can excellently describe the local failure diffusion mechanism of many real scenarios. However, the phase transition behavior of finite clusters, as important network components, has not been clearly understood yet under LA. Here, we develop a percolation framework to theoretically and simulatively study the phase transition behavior of functional nodes belonging to the finite clusters of size greater than or equal to s(s=2,3,…) under LA in this paper. The results reveal that random network exhibits second-order phase transition behavior, the critical threshold pc increases significantly with increasing s, and the network becomes vulnerable. In particular, we find a new general scaling relationship with the critical exponent δ=-2 between the fraction of finite clusters and s. Furthermore, we apply the theoretical framework to some real networks and predict the phase transition behavior of finite clusters in real networks after they face LA. The framework and results presented in this paper are helpful to promote the design of more critical infrastructures and inspire new insights into studying phase transition behaviors for finite clusters in the network.Liquid drops when subjected to external periodic perturbations can execute polygonal oscillations. In this work, a simple model is presented that demonstrates these oscillations and their characteristic properties. The model consists of a spring-mass network such that masses are analogous to liquid molecules and the springs correspond to intermolecular links. Neo-Hookean springs are considered to represent these intermolecular links. The restoring force of a neo-Hookean spring depends nonlinearly on its length such that the force of a compressed spring is much higher than the force of the spring elongated by the same amount. This is analogous to the incompressibility of liquids, making these springs suitable to simulate the polygonal oscillations. It is shown that this spring-mass network can imitate most of the characteristic features of experimentally reported polygonal oscillations. Additionally, it is shown that the network can execute certain dynamics, which so far have not been observed in a perturbed liquid drop. The characteristics of dynamics that are observed in the perturbed network are polygonal oscillations, rotation of network, numerical relations (rational and irrational) between the frequencies of polygonal oscillations and the forcing signal, and that the shape of the polygons depends on the parameters of perturbation.We have found a way for penetrating the space of the dynamical systems toward systems of arbitrary dimension exhibiting the nonlinear mixing of a large number of oscillation modes through which extraordinarily complex time evolutions may arise. The system design is based on assuring the occurrence of a number of Hopf bifurcations in a set of fixed points of a relatively generic system of ordinary differential equations, in which the main peculiarity is that the nonlinearities appear through functions of a linear combination of the system variables. The paper outlines the design procedure and presents a selection of numerical simulations with a variety of designed systems whose dynamical behaviors are really rich and full of unknown features. For concreteness, the presentation is focused on illustrating the oscillatory mixing effects on the periodic orbits, through which the harmonic oscillation born in a Hopf bifurcation becomes successively enriched with the intermittent incorporation of other oscillation modes of higher frequencies while the orbit remains periodic and without the necessity of bifurcating instabilities. Even in the absence of a proper mathematical theory covering the nonlinear mixing mechanisms, we find enough evidence to expect that the oscillatory scenario be truly scalable concerning the phase-space dimension, the multiplicity of involved fixed points, and the range of time scales so that extremely complex but ordered dynamical behaviors could be sustained through it.Astute variations in the geometry of mathematical billiard tables have been and continue to be a source of understanding their wide range of dynamical behaviors, from regular to chaotic. Viewing standard specular billiards in the broader setting of no-slip (or rough) collisions, we show that an equally rich spectrum of dynamics can be called forth by varying the mass distribution of the colliding particle. We look at three two-parameter families of billiards varying both the geometry of the table and the particle, including as special cases examples of standard billiards demonstrating dynamics from integrable to chaotic, and show that markedly divergent dynamics may arise by changing only the mass distribution. Furthermore, for certain parameters, billiards emerge, which display unusual dynamics, including examples of full measure periodic billiards, conjectured to be nonexistent for the standard billiards in Euclidean domains.The lipid-coated mesoporous silica nanoparticles (LMSNs) that can synergistically harness the advantages and mitigate the disadvantages of the liposomes and MSNs are considered potential drug carriers. So far, several methods have been developed to prepare LMSNs, including vesicle fusion, thin-film hydration, and solvent exchange. Despite their wide application in LMSN preparation, these methods are short of detailed elaboration and comparison, which hinders their further development. In this review, for the first time, the three methods are systematically summarized, including their mechanisms, influence factors, advantages, and limitations. Although these methods are all based on lipid self-assembly, there is still a difference between them. In order to efficiently prepare LMSNs, we proposed that a suitable method should be selected based on the actual situation. It is conceivable that the elaboration and comparison in this review will make these methods easy to be understood and provide guidance for the design of LMSNs as drug carriers.In ionic-liquid (IL)-based electrolytes, relevant for current energy storage applications, ion transport is limited by strong ion-ion correlations, generally yielding inverse Haven ratios (ionicities) of below 1. In particular, Li is transported in anionic clusters into the wrong direction of the electric field, requiring compensation by diffusive anion fluxes. Here, we present a concept to exploit ion-ion correlations in concentrated IL electrolytes beneficially by designing organic cations with a Li-coordinating chain. 1H NMR and Raman spectra show that IL cations with seven or more ether oxygens in the side chain induce Li coordination to organic cations. An unusual behavior of an inverse Haven ratio of >1 is found, suggesting an ionicity larger than that of an ideal electrolyte with uncorrelated ion motion. This superionic behavior is consistently demonstrated in both NMR transport/conductivity measurements and molecular dynamics (MD) simulations. Key to this achievement is the formation of long-lived Li-IL cation complexes, which invert the Li drift direction, yielding positive Li+ ion mobilities for the first time in a single IL-solvent-based electrolyte.
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