Search

This is a call for papers that should contribute to the unification of behavioral sciences and team management, focusing on the biological origin of cooperation and swarm intelligence, moving from biology to psychology and from sociology to political science, with the help of the theoretical tools of complex networks. This issue should shed light into the origin of ergodicity breaking and contribute to establishing a connection, still lacking theoretical support, between complexity properties that are expected to be correlated. Examples are: non-Poisson renewal events and multi-fractality; complexity matching and chaos synchronization; criticality and extended criticality of small size systems. Although the emphasis is on systems of small size, and especially on the search of the size maximizing both information transport and cooperation emergence, special attention will be devoted to the interaction between small groups and their larger societies.

The purpose of this short paper is to present a new form of the so called early exercise premium for the American type derivatives. The decomposition we derived consists of the corresponding European derivative and a derivative with a stochastic maturity. In different particular cases we reach to the well known form for the American put option where the underlying asset is driven by a Brownian motion or a Levy process.

The Lie symmetry and invariants for a generalized Birkhoffian system on time scales are studied, which include exact invariants and adiabatic invariants. First, the generalized Pfaff-Birkhoff principle on time scales is established, and by using Dubois-Reymond lemma the generalized Birkhoff’s equations on time scale are derived. Secondly, the determining equations of Lie symmetry for the generalized Birkhoffian system on time scales are established. We prove that if the Lie symmetry satisfies the structural equation, it leads to a conserved quantity, which is an exact invariant of the system. Again, the perturbation of Lie symmetry under the action of small disturbance is considered, the determining equations and the structural equations of disturbed system are established, and the adiabatic invariants led by the Lie symmetry perturbation for the generalized Birkhoffian system on time scales are given. Because of the arbitrariness of selecting time scales and the generality of the generalized Birkhoffian system, the results of this paper are of universal significance. The results of this paper contain the corresponding results for Birkhoffian system on time scales and classical generalized Birkhoffian system as its special cases. At the end of the paper, an example is given to illustrate the validity of the method and the results.

In this paper, the author proposes a new stock financial market stochastic volatility and stock pricing model based on the Taylor formula, by embedding the strictly increasing harmonic steady-state process as a time variable into the Brownian motion with drift terms. The use of variance gamma and normal inverse high-lower distribution are special forms of NTS distribution, combined with principal component analysis (PCA) and artificial neural network (ANN) methods, for nonlinear and multi-scale complex financial time series in financial markets. The model is constructed and predicted, and the forecast and calculation of stock market index and foreign exchange rate are realized. Through calculation and research, the model can fill the blank of complex time series model research in financial market. The stock signal analysis based on fractional calculus equation proposed in the thesis is based on the idea of decomposition-reconstruction-integration, which can improve the prediction accuracy of the model for the time series combined financial model. The Shanghai and Shenzhen 300 Index and foreign exchange rates selected by the paper are taken from the market real data, and the skeleton prediction model is established. It can predict the short-term trend after the stock market closes, confirming the nonlinear, multi-scale and non-stationary the prediction accuracy of the sequential decomposition prediction method of financial time series is effectively improved, and the principal component and artificial neural network method are used to compress redundant data and shorten the prediction time.

In this paper, we study the existence and the numerical estimates of solutions for a specific types of fractional differential equations. The nonlinear part of the problem, however, presupposes certain hypotheses. Particularly, for exact localization of the parameter, the existence of a non-zero solution is established, which requires the sublinearity of the nonlinear part at the origin and infinity. We also take into consideration several theoretical and numerical examples. One of the main novelties of this paper is to use the variational method to investigate the properties of solutions of boundary values problems involving Atangana–Baleanu fractional derivative for the first time.

The complexities of nature have pushed humankind to construct complex mathematical formula that can be used to capture such natural occurrence. Very recently the concept differential and integral operators with fractional order and fractal dimension were introduced. The concept has opened new doors for investigations. In this paper, we present a step forward, where the constant fractal dimension is replaced by variable dimension. We present in detail some properties of this new operators, we suggested a new numerical approach that can be used to solve differential and integral equations associate to this operators. We presented some examples and simulations are presented to underpin the strength of the new operators. We strongly believe that this paper will open many new doors of investigation toward modeling real world problems.

Chatter between devices becomes a primary concern in actual engineering problems since it may cause the reduction of efficiency. Due to random factors and non-smooth properties, difficulties rest in deriving the analytical results and such systems are generally investigated with simplified approximate methods. In this context, the present paper pioneers the response analysis of three-dimensional hydraulic relief valve impact systems under stochastic excitations. In order to retain the non-smooth characteristics of the systems under consideration, no non-smooth transformation is imposed on the original system. A procedure in which the stochastic trajectories start from the contact surface and return to the contact surface for the next time is constructed. Probability density functions (PDFs) of the random trajectories returning to the contact surface at any time can be obtained, and the proposed procedure is proved accurate and efficient using Monte Carlo (MC) simulations in this paper. Moreover, we find that the flow rate of the systems can lead to the stochastic P-bifurcation on the contact surface. Further discussion indicates that the proposed procedure can substantially reflect the complicated dynamic behaviors of the high-dimensional vibro-impact systems.

This paper describes the design of a regional observer-based controller for the locally Lipchitz nonlinear systems, which can be employed successfully to attain both monitoring and control of a wide range of systems. An observer-based control approach has been employed to attain advantages of the traditional state feedback along with the state estimation through an observer. A lot of work has been accomplished for the globally Lipchitz nonlinear systems. However, a less conservative continuity, called the generalized ellipsoidal Lipchitz condition, has been applied in this paper to consider the locally Lipchitz systems. This condition is then incorporated to attain convex routines for computing the local controller and observer gains. The focus of the present study is to investigate conditions for simultaneous design of observer and controller under locally Lipchitz nonlinearities for systems with norm-bounded disturbances that not only guarantees the stabilization and true state estimation but also robustness against external perturbations. Furthermore, the decoupling of the observer and controller design conditions has been worked out for obtainment of a simple design method. Since the resultant control approach applies to a general class of systems, it can be straightforwardly employed to the globally Lipschitz nonlinear systems as a specific case. The approach is tested via a chaotic system and simulation results are provided to validate the effectiveness of resultant control schemes for the locally Lipschitz systems.

Research findings have shown that evolution equations containing non-integer order derivatives can lead to some useful dynamical systems which can be used to describe important physical scenarios. This paper deals with numerical simulations of multicomponent symbiosis systems, such as the parasitic predator-prey model, the commensalism system, and the mutualism case. In such models, we replace the classical time derivative with either the Caputo fractional derivative or the Atangana-Baleanu fractional derivative in the sense of Caputo. To guide in the correct choice of parameters, we report the models linear stability analysis. Numerical examples and results obtained for different instances of fractional power α are provided for non-spatial models as well as the spatial case in one and two dimensions in other to justify our theoretical findings which include the chaotic phenomena, spatiotemporal and oscillatory patterns, multiple steady states and other spatial pattern processes. This paper further suggest an alternative approach to incessant killing of wildlife animals for pattern generation and decorative purposes.

An epidemic is a typical public health emergency that refers to the occurrence and rapid spread of disease. A good epidemic transmission model plays a crucial role in preventing an epidemic. The epidemic transmission model is largely similar to the model of sentiment analysis and transmission on social media. Therefore, this paper intend to use the method of deep learning to explore the key issues of theme and sentiment analysis from the perspective of public opinion analysis. In order to fully extract the features automatically, we combine the following methods: multi-channel inputs, multi-granularity convolution kernels, direct connection with high-speed channels, and this paper proposes the multi-channel and multi-kernel (MCMK) model. Furthermore, we leverage generative adversarial nets to combine several single tasks, called Joint-MCMK model, which achieves information sharing and improves the training speed and model accuracy. To verify the validity of our proposed models, this paper experimented with the short text topic classification dataset TREC [1] and the sentiment analysis dataset IMDB [2] . Results achieved 98.6% and 92.6% respectively, which are superior to the highest existing industry benchmark (96.1% and 92.58%). In addition, this paper compared the training spread differences between the joint-MCMK model and MCMK model, which shows that the joint-MCMK model has better performance at training speed. Finally, the control variable method was used to analyze the multiple effects of the different factors. The optimal value of some relevant parameters in our models were verified by several experiments.

One of the important classes of coupled systems of algebraic, differential and fractional differential equations (CSADFDEs) is fractional differential algebraic equations (FDAEs). The main difference of such systems with other class of CSADFDEs is that their singularity remains constant in an interval. However, complete classifying and analyzing of these systems relay mainly to the concept of the index which we introduce in this paper. For a system of linear differential algebraic equations (DAEs) with constant coefficients, we observe that the solvability depends on the regularity of the corresponding pencils. However, we show that in general, similar properties of DAEs do not hold for FDAEs. In this paper, we introduce some practical applications of systems of FDAEs in physics such as a simple pendulum in a Newtonian fluid and electrical circuit containing a new practical element namely fractors. We obtain the index of introduced systems and discuss the solvability of these systems. We numerically solve the FDAEs of a pendulum in a fluid with three different fractional derivatives (Liouville–Caputo’s definition, Caputo–Fabrizio’s definition and with a definition with Mittag–Leffler kernel) and compare the effect of different fractional derivatives in this modeling. Finally, we solved some existing examples in research and showed the effectiveness and efficiency of the proposed numerical method.

In this paper, we suggest a new algorithm for description of complex beatings. Under the complex beating we understand a signal, which contains the high-frequency (HF) component that is located between two low-frequency (LF) envelopes having random origin. These beatings are associated with the so-called blow-like signals (BLS) and a typical example of the BLS can be associated with the registered earthquakes signals. For description of these signals, it becomes possible to separate two envelopes from the HF-component located between them and find their amplitude-frequency response (AFR) based on the non-orthogonal amplitude-frequency analysis of the smoothed signals (NAFASS) approach that was suggested earlier by one of the authors (RRN) in paper [1] . It was successfully applied for description of economic data having also multi-frequency structure. In order to separate these envelopes from the HF component one can notice that the most signals of such kind have a fractal (self-similar) structure. It means that under reasonable compression/scaling of these signals they keep approximately their initial structure. This scaling property can be tested on many types of the different signals. In the results of application of the NAFASS approach one can describe quantitatively the desired envelopes and obtain their AFRs. As an example, we considered the randomly taken data that were recorded from EQs station located in Kyrgyzstan. We deliberately chose the different types of the EQs signals in order to demonstrate the flexibility and wide applicability of the proposed algorithm. We expect that this algorithm can find a wide application for description of many BLS that are met frequently in many natural phenomena and engineering applications.

This paper is inspired by the stratified-rewards adopted by rural organizers. Since this method has been used for many years, this paper attempts to explore the feasibility of it. We take into account of individuals’ self-assessment of face, asynchronous decision-making and individuals’ expectations for their neighbors, take available funds and standard deviation as the main indicators and then use agent-based model to simulate the effects of stratified-rewards. Our results show that cooperation can be maintained or promoted slightly if the total number of individuals who can gain rewards is not large. If organizers want to gain more available funds, they need to expand the scope of reward. But they should control the number of individuals who can receive higher rewards this time. Otherwise, the available funds may less than the initial value, though all individuals choose to cooperate. Of course, controlling costs is also important. In general, organizers can get more available funds at low cost if they do it properly.

Highlights • A compartmental mathematical model has been proposed in this paper incorporating all possible non-pharmaceutical intervention policies. • Short-term projection results have been illustrated for Bangladesh and India. • All necessary graphical simulations have been performed with the help of Caputo-Fabrizio fractional derivatives. • Optimal control problem for fractional system has been designed and the existence of unique solution has also been showed by using Picard-Lindelof technique., When the entire world is eagerly waiting for a safe, effective and widely available COVID-19 vaccine, unprecedented spikes of new cases are evident in numerous countries. To gain a deeper understanding about the future dynamics of COVID-19, a compartmental mathematical model has been proposed in this paper incorporating all possible non-pharmaceutical intervention strategies. Model parameters have been calibrated using sophisticated trust-region-reflective algorithm and short-term projection results have been illustrated for Bangladesh and India. Control reproduction numbers (Rc) have been calculated in order to get insights about the current epidemic scenario in the above-mentioned countries. Forecasting results depict that the aforesaid countries are having downward trends in daily COVID-19 cases. Nevertheless, as the pandemic is not over in any country, it is highly recommended to use efficacious face coverings and maintain strict physical distancing in public gatherings. All necessary graphical simulations have been performed with the help of Caputo-Fabrizio fractional derivatives. In addition, optimal control strategies for fractional system have been designed and the existence of unique solution has also been showed using Picard-Lindelof technique. Finally, unconditional stability of the fractional numerical technique has been proved.

Most of the widely populated countries across the globe have been observing vicious spread and detrimental effects of pandemic COVID-19 since its inception on December 19. Therefore to restrict the spreading of pandemic COVID-19, various researches are going on in both medical and administrative sectors. The focus has been given in this research keeping an administrative point of view in mind. In this paper a dynamic model of infected population due to spreading of pandemic COVID-19 considering both intra and inter zone mobilization factors with rate of detection has been proposed. Few factors related to intra zone mobilization; inter zone mobilization and rate of detection are the key points in the proposed model. Various remedial steps are taken into consideration in the form of operating procedures. Further such operating procedures are applied over the model in standalone or hybridized mode and responses are reported in this paper in a case-studies manner. Further zone-wise increase in infected population due to the spreading of pandemic COVID-19 has been studied and reported in this paper. Also the proposed model has been applied over the real world data considering three states of India and the predicted responses are compared with real data and reported with bar chart representation in this paper.

In this paper, we are working on a pandemic of novel coronavirus (COVID-19). COVID-19 is an infectious disease, it creates severe damage in the lungs. COVID-19 causes illness in humans and has killed many people in the entire world. However, this virus is reported as a pandemic by the World Health Organization (WHO) and all countries are trying to control and lockdown all places. The main objective of this work is to solve the five different tasks such as I) Predicting the spread of coronavirus across regions. II) Analyzing the growth rates and the types of mitigation across countries. III) Predicting how the epidemic will end. IV) Analyzing the transmission rate of the virus. V) Correlating the coronavirus and weather conditions. The advantage of doing these tasks to minimize the virus spread by various mitigation, how well the mitigations are working, how many cases have been prevented by this mitigations, an idea about the number of patients that will recover from the infection with old medication, understand how much time will it take to for this pandemic to end, we will be able to understand and analyze how fast or slow the virus is spreading among regions and the infected patient to reduce the spread based clear understanding of the correlation between the spread and weather conditions. In this paper, we propose a novel Support Vector Regression method to analysis five different tasks related to novel coronavirus. In this work, instead of simple regression line we use the supported vectors also to get better classification accuracy. Our approach is evaluated and compared with other well-known regression models on standard available datasets. The promising results demonstrate its superiority in both efficiency and accuracy.

Highlights • Reviewed on various information related to application of Machine Learning and Artificial Intelligent for tackling Covid-19 pandemic. • Challenges on computational system with real world problem discusses suggestions conveying researchers on model design, medical experts, and policymakers for tackling the Covid-19 pandemic and ahead. • Targeting on treatment, medication, screening, prediction, forecasting, contact tracing, and drug/vaccination process for the Covid-19 pandemic., Background and objective During the recent global urgency, scientists, clinicians, and healthcare experts around the globe keep on searching for a new technology to support in tackling the Covid-19 pandemic. The evidence of Machine Learning (ML) and Artificial Intelligence (AI) application on the previous epidemic encourage researchers by giving a new angle to fight against the novel Coronavirus outbreak. This paper aims to comprehensively review the role of AI and ML as one significant method in the arena of screening, predicting, forecasting, contact tracing, and drug development for SARS-CoV-2 and its related epidemic. Method A selective assessment of information on the research article was executed on the databases related to the application of ML and AI technology on Covid-19. Rapid and critical analysis of the three crucial parameters, i.e., abstract, methodology, and the conclusion was done to relate to the model's possibilities for tackling the SARS-CoV-2 epidemic. Result This paper addresses on recent studies that apply ML and AI technology towards augmenting the researchers on multiple angles. It also addresses a few errors and challenges while using such algorithms in real-world problems. The paper also discusses suggestions conveying researchers on model design, medical experts, and policymakers in the current situation while tackling the Covid-19 pandemic and ahead. Conclusion The ongoing development in AI and ML has significantly improved treatment, medication, screening, prediction, forecasting, contact tracing, and drug/vaccine development process for the Covid-19 pandemic and reduce the human intervention in medical practice. However, most of the models are not deployed enough to show their real-world operation, but they are still up to the mark to tackle the SARS-CoV-2 epidemic.

The present paper shows the dynamics of Hepatitis E with optimal control. The paper is analyzed by two different aspects: first, we explore the dynamics of Hepatitis E model and then applying the optimal control analysis. Secondly, we use the most appropriate and recent fractional order derivative called the Atangana–Baleanu derivative for the dynamical analysis of Hepatitis E model. The proposed model considered is locally asymptotically stable when the threshold quantity less than one. Further, we explore the stability analysis of the model when R 0 > 1 . Then, we choose some appropriate control to formulate the optimality system. The results associated to the optimal control are obtained and discussed with different strategies. Moreover, we apply Atangana–Baleanu derivative to the proposed model and obtain the required results necessary for the fractional order model. Numerical results for the optimal control problem and Atangana–Baleanu derivative are obtained and discussed in detail. The results suggest that control variables chosen should be properly applied to get rid of the infection of Hepatitis E. The Atangana–Baleanu derivative results suggest that at any time t we can check the disease status and make a useful strategy for the early elimination of Hepatitis E from the community.

In this paper, we present and analyze a prey-predator system, in which prey species can be infected with some disease. The model presented in this paper is motivated from D. Mukherjee’s model in which he has considered an SI model for the prey species. There are substantial evidences that infected individuals have the ability to recover from the disease if vaccinated/ treated properly. In this regard, Mukherjee’s model is modified by considering SIS model for prey species. Theoretical and numerical simulations show that the recovery of infected prey species plays a crucial role in eliminating the limit cycle oscillations and thus making the interior equilibrium point stable. The possibility of Hopf bifurcation around non zero equilibrium point using the recovery rate as a bifurcation parameter, is discussed. Further, the model is extended by incorporating the harvesting of predator population. A monitory agency has been introduced which monitors the exploitation of resources by implementing certain taxes for each unit biomass of the predator population. The main purpose of the present research is to explore the effect of recovery rate of prey on the dynamics of the system and to optimize the total economical net profits from harvesting of predator species, taking taxation as control parameter.

This paper develops the analytical conditions for the existence of periodic solutions of a second-order,time-delayed, discontinuous dynamical system. A sample model consists of two linear delayed sub-systems with a switching boundary. The defined G-functions for the delayed, discontinuous systems are introduced, and sufficient and necessary conditions for a flow crossing, sliding and grazing along the switch boundary are developed for such a delayed, discontinuous system. Furthermore, nine (9) regular basic mappings in phase plane and thirty-three (33) delay-related mappings for the second-order, time-delayed, discontinuous systems are classified. Constraint equations are predicted analytically for two periodic orbits with initial functions provided posteriorly. Finally, three numerical examples are illustrated to verify the existence of generalized slowly oscillating periodic orbits without and with sliding portions. This paper improves and extends motion switchability conditions at the boundary in discontinuous dynamical systems without delay.

A three factor variance model introduced by Gatheral in 2008, called the double mean reverting (DMR) model, is well-known to reflect the empirical dynamics of the variance and prices of options on both SPX and VIX consistently with the market. One drawback of the DMR model is that calibration may not be easy as no closed form solution for European options exists, not like the Heston model. In this paper, we still use the double mean reverting nature to extend the Heston model and study the pricing of variance swaps given by simple returns in discrete sampling times. The constant mean level of Heston’s stochastic volatility is extended to a slowly varying process which is specified in two different ways in terms of the Ornstein-Uhlenbeck (OU) and Cox-Ingersoll-Ross (CIR) processes. So, two types of double mean reversion are considered and the corresponding models are called the double mean reverting Heston-OU model and the double mean reverting Heston-CIR models. We solve Riccati type nonlinear equations and derive closed form exact solutions or closed form approximations of the fair strike prices of the variance swaps depending on the correlation structure of the three factors. We verify the accuracy of our analytic solutions by comparing with values computed by Monte Carlo simulation. The impact of the double mean reverting formulation on the fair strike prices of the variance swaps are also scrutinized in the paper.

In the recent past, coronal mass ejection (CME) has received much research attention for its geo-effectiveness. In this paper, an investigation has been made to identify the scaling pattern of the CME linear speed time series data (February 1999 to December 2007 of solar cycle 23) collected from the Solar and Heliospheric Observatory (SOHO) using Multi-Fractal Detrended Fluctuation Analysis (MFDFA) and Multi-Fractal Detrended Moving Average (MFDMA) method. The scaling exponent, generalized Hurst exponent, singularity strength and also the singularity spectrum have been computed to quantify the multifractality and to identify the singularities of the time series data. An effort has also been made to find out the possible sources which are responsible for the multifractality in the signal by studying the scaling patterns of the shuffled and surrogate version of the original data. It has been revealed in this paper that CME linear speed signal exhibit multifractal behaviour with long-term persistence. Both the long-range temporal correlation and the broad probability density function (pdf) are found to be the primary source of multifractality in the signal. The singularities or abruptness present in the signal are found to vary with time, and this fluctuation follows an AR (2) model.

This paper presents a scientific collaboration hypernetwork evolution model with adjustable clustering coefficient in which the authors are regarded as nodes and the hyperedges are the cooperative articles. Firstly, we build the scientific cooperation hypernetwork through the real paper data which comes from the database of arxive. The empirical results show that the node's hyperdegree follows the power law distribution, but the hyperedge's node-degree has the exponent distribution. In addition, we establish the scientific collaboration clustering hypernetwork evolution model by employing the Poisson process theory and the continuous method for studying the agglomeration phenomenon of scientific cooperation system. The theoretical analysis shows that the node's hyperdegree distribution has scale-free characteristics. The power index of our model is independent of the clustering coefficient, and the theoretical analyses agree with the conducted numerical simulations. Moreover, our model not only describes the scale-free property, but also depicts the phenomenon of agglomeration. Both the properties are usually coexist in the scientific cooperation, our model is more actual.

Recently fractional differential operators with non-index law properties have being recognized to have brought new weapons to accurately model real world problems particularly those with non-Markovian processes. This present paper has two double aims, the first was to prove the inadequacy and failure of index law fractional calculus and secondly to show the application of fractional differential operators with no index law properties to statistic and dynamical systems. To achieve this, we presented the historical construction of the concept of fractional differential operators from Leibniz to date. Using a matrix based on the fractional differential operators, we proved that, fractional operators obeying index law cannot model real world problems taking place in two states, more precisely they cannot describe phenomena taking place beyond their boundaries, as they are scaling invariant, more precisely our results show that, mathematical models based on these differential operators are not able to describe the inverse memory, meaning the full history of a physical problem cannot be described accurately using these derivatives with index law properties. On the other hand, we proved that, differential operators with no index-law properties are scaling variant, thus can describe situations taking place in different states and are able to localize the frontiers between two states. We present the renewal process properties included in differential equation build out of the Atangana–Baleanu fractional derivative and counting process, which is connected to its inter-arrival time distribution Mittag–Leffler distribution which is the kernel of these derivatives. We presented the connection of each derivative to a statistical family, for instance Riemann–Liouville–Caputo derivatives are connected to the Pareto statistic, which has no well-defined average when alpha is less than 1 corresponding to the interval where fractional operators mostly defined. We established new properties and theorem for the Atangana–Baleanu derivative of an analytic function, in particular we proved that, they are convolution of the Mittag–Leffler function with the Riemann–Liouville–Caputo derivatives. To see the accuracy of the non-index law derivative to in modeling real chaotic problems, 4 examples were considered, including the nine-term 3-D novel chaotic system, King Cobra chaotic system, the Ikeda delay system and chaotic chameleon system. The numerical simulations show very interesting and novel attractors. The king cobra system with the Atangana–Baleanu presented a very novel attractor where at the earlier time we observed a random walk and latter time we observed the real sharp of the cobra. The Ikeda model with Atangana–Baleanu presented different attractors for each value of fractional order, in particular we obtain a square and circular explosions. The results obtained in this paper show that, the future of modeling real world problem relies on fractional differential operators with non-index law property. Our numerical results showed that, to not model physical problems with fractional differential operators with non-singular kernel and imposing index law in fractional calculus is rightfully living with closed eyes without ever taking a risk to open them.

In the previous paper [Yamada, Chaos, Solitons $\&$ Fractals, {\bf 109},99(2018)], we investigated localization properties of one-dimensional disordered electronic system with long-range correlation generated by modified Bernoulli (MB) map. In the present paper, we report localization properties of phonon in disordered harmonic chains generated by the MB map. Here we show that Lyapunov exponent becomes positive definite for almost all frequencies $\omega$ except $\omega=0$, and the $B-$dependence changes to exponential decrease for $B > 2 $, where $B$ is a correlation parameter of the MB map. The distribution of the Lyapunov exponent of the phonon amplitude has a slow convergence, different from that of uncorrelated disordered systems obeying a normal central-limit theorem. Moreover, we calculate the phonon dynamics in the MB chains. We show that the time-dependence of spread in the phonon amplitude and energy wave packet changes from that in the disordered chain to that in the periodic one, as the correlation parameter $B$ increases., Comment: 10 pages, 11 figures

For non-invasively investigating the interaction between insulin and glucose, mathematical modeling is very helpful. In this paper, we propose a new model for insulin-glucose regulatory system based on the well-known prey and predator models. The results of previous researches demonstrate that chaos is a common feature in complex biological systems. Our results are in accordance with previous studies and indicate that glucose-insulin regulatory system has various dynamics in different conditions. One interesting feature of this new model is having hidden attractor for some set of parameters. The result of this paper might be helpful for better understanding of regulatory system that contains glucose, insulin, and diseases such as diabetes, hypoglycemia, and hyperinsulinemia.

It has been shown that natural interval extensions (NIE) can be used to calculate the largest positive Lyapunov exponent (LLE). However, the elaboration of NIE are not always possible for some dynamical systems, such as those modelled by simple equations or by Simulink-type blocks. In this paper, we use rounding mode of floating-point numbers to compute the LLE. We have exhibited how to produce two pseudo-orbits by means of different rounding modes; these pseudo-orbits are used to calculate the Lower Bound Error (LBE). The LLE is the slope of the line gotten from the logarithm of the LBE, which is estimated by means of a recursive least square algorithm (RLS). The main contribution of this paper is to develop a procedure to compute the LLE based on the LBE without using the NIE. Additionally, with the aid of RLS the number of required points has been decreased. Eight numerical examples are given to show the effectiveness of the proposed technique.

In this paper, we investigate a (2+1)-dimensional coupled nonlinear Schrodinger system, which describes the transverse effects in an optical fiber, time-independent copropagation and field of optical soliton. Bilinear forms, dark one- and two-soliton solutions are derived by virtue of the Hirota method. Propagation and interaction properties of the dark solitons are discussed: (i) Amplitudes and velocities of the dark solitons are affected by the values of the wave numbers μ, λ and θ. (ii) Head-on and overtaking interactions between the two parallel dark solitons are discussed, where the amplitudes of the dark solitons remain unchanged after each interaction, implying that the interactions are elastic. (iii) Stationary dark solitons are depicted in this paper. (iv) Through the asymptotic analysis, elastic interaction between the two solitons is discussed analytically.

Cyclic dominance is observed in predator-prey interactions, the mating strategy of side-blotched lizards, the overgrowth of marine sessile organisms and competition in microbial populations and many other natural systems. Rock-Paper-Scissor(RPS) is a popular game which demonstrates cyclic dominance. In this paper, we investigate replicator dynamics of RPS-game under logistic growth functions with Allee effect. The results obtained are compared with the case of no Allee effect. Due to Allee effect the number of stable attractors increases in a certain parameter region. The obtained result can be interpreted biologically that diversity of an ecological system increases due to Allee effect.

Studying attack strategy of complex networks is the basis of investigating network characteristics such as robustness, invulnerability, and network security. Knowing means of attack can help us take more effective measures to ensure network security. Presently, most research conclusions focus on a single vertex being attacked, and the choice of a set of attack nodes is also limited to a complete understanding of network information. In this paper, considering the effect of cascading failure, we focus on the multi-node attack strategy. Our results showed that the distance between attack targets has a great effect on the attacking effect. Taking both the average avalanche scale and maximum destruction size into account, when the distance between attack targets was 2, the network suffered the most serious damage. If the information about the network was unclear, we presented 3 kinds of conditional attack strategies. Under the condition of different tolerance coefficients and different degrees of known information, each strategy had its own unique advantages. In conclusion, the research in this paper supports the easy and quick selection of attack targets under the condition of incomplete information.

In this paper, we replace the classical differential operators with the fractal-fractional differential operators corresponding to the power law, exponential decay, and the generalized Mittag-Leffler kernels. These operators have two parameters created: the first is a fractal dimension and the second is a fractional order. The numerical schemes are combination of the Lagrange interpolating polynomial and theory of fractional calculus. In the case of δ = k = 1 the numerical solutions for the proposed models are found to be in an excellent agreement with the finite difference methods. We investigate the effects of the fractal-fractional order on the oscillations in the Fractal-Fractional Brusselator Chemical Reaction (FFBCR). All calculations in this paper were done using the mathematica package.

This paper addresses the problem of tracking control and disturbance rejection for nonlinear fractional order systems. To this end, based on Takagi-Sugeno (T-S) fuzzy modeling approach and a fractional order modified repetitive controller, an output feedback strategy is constructed for a class of nonlinear fractional order systems. T-S fuzzy model represents an accurate model of nonlinear fractional order systems and simplifies the procedure of control system design. By introducing a novel Fuzzy Lyapunov Function (FLF), sufficient conditions are established in the framework of Linear Matrix Inequalities (LMIs) to ensure the stability of the closed-loop system. Based on the achieved conditions, it is shown that the external disturbance is attenuated and the output of the system tracks the periodic reference input with an ignorable error. Lastly, three examples including fractional order Chua’s circuit, Lorenz-like and Chen systems are performed to show the efficiency of the method proposed in this paper.

This paper focuses on the role of feedback mechanism on message propagation. In this paper, we study the effect of feedback on message propagation in terms of both the motivation of the communicator to propagate the message and the trust of the message recipient in the communicator, and we design a decay mechanism of motivation based on Newton's cooling law. Based on these considerations, we propose a model of message propagation based on the feedback mechanism. We verify the effect of feedback on message propagation by performing numerical simulations in the Watts-Strogatz (WS) and Barabasi-Albert (BA) networks. The simulation results show that the feedback mechanism leads to faster and more persistent message propagation and that the degree of influence on message propagation varies across different network structures. The simulation also results show that the feedback mechanism changes the structure of the social network and makes the nodes between the networks more closely connected.

The rotary blood pump is one of the latest generations of left ventricular assist devices (LVAD), helping patients to deal with shortage of cardiac output. The main challenge of the LVAD controller is to finely regulate the pump speed in a variety of physical activities from sleep (50 beats/min) till running (180 beats/min). If the pump speed exceeds the low/high extremes, the blood will inversely move (backflow), or the heart muscle will collapse (suction state). This paper shows that the LVAD behaves like a limit cycle and optimizing the amplitude of this limit cycle leads to improve the performance of the LVAD. Therefore, in this paper, a nonlinear controller is proposed based on extremum-seeking theorem in order to regulate the heart performance. The controller objective is to provide the maximum pump flow, while the suction phenomenon is prevented. This goal can be achieved by the proposed controller since it can assure reaching the extremum, taking into account the constraints for preventing suction. The control strategy is applied to an in-silico model, and the results declare that the proposed controller can maintain proper cardiac response, while the mean arterial pressure remains within the demanding range, preventing the suction. The controller's robustness is investigated under different levels of external noise, and the results are compared to the state-of-the-art approaches. The comparison results imply the superiority of the proposed approach to the counterparts.

Barrier-lookback option stands for a class of exotic options involving both high risky and high payback properties that are popular for many investors, which expresses that the lookback option comes into effect or becomes invalid depending on whether the underlying asset reaches the predetermined barrier level. This paper aims at investigating the pricing formulas for barrier-lookback option in uncertain financial markets, including up-and-in lookback call option, down-and-in lookback put option, up-and-out lookback put option, and down-and-out lookback call option. Assume the stock price follows the uncertain stock model, the explicit pricing formulas for the above four kinds of barrier-lookback option are obtained. Besides, the corresponding numerical examples are discussed in this paper.

The present work is devoted to giving new insights into the extended Malkus-Robbins (EMR) dynamo. Firstly, based on differential geometry method, i.e. Kosambi-Cartan-Chern (KCC) theory, the paper investigates the Jacobi stability of the equilibrium and periodic orbit by the eigenvalues of the deviation curvature tensor. The deviation vector is applied to analyze the trajectory behaviors near the equilibrium and periodic orbit. Secondly, the zero-zero-Hopf bifurcation is investigated. The paper obtains the conditions that two periodic solutions appear at the bifurcation point and discusses their stability. Finally, on the global dynamics, the ultimate bound sets of the system are estimated. Numerical simulations are given to verify and visualize the corresponding theoretical results.

Randomness is a common phenomenon in nonlinear systems. And conditions to reach synchronization are more complex and difficult when chaotic systems have random parameters. So in this paper, an adaptive scheme for synchronization of chaotic system with random parameters by using the fuzzy impulsive method and combining the properties of Wiener process and Ito differential is investigated. The main concepts of this paper are applying fuzzy method to approximate the nonlinear part of system, then using Ito differential to study the Wiener process of random parameters of chaotic system, and realizing synchronization under fuzzy impulsive method. The stability is analyzed by Lyapunov stability theorem. At the end of the paper, numerical simulation is presented to illustrate the effectiveness of the results obtained in this paper.

The effect of resource usage on economic growth has been investigated in many papers and the generic effect of resource usage efficacy by improving technical skills has been discussed. However, the impact of environmental pollution and the effect of memory property of the economic variables on economic growth have not been studied in detail. In this paper, a new resource depletion model, in which fractional derivative describes the memory property of economic variables, is built. Firstly, the influence of the environmental pollution on economic growth is analyzed. The results show the model is extreme sensitive to some parameters with considering the impact of environmental pollution. The small change of the parameters can lead a collapse of the economy in a short time. Meanwhile, new equilibrium region of economic growth can be obtained with considering the effect of the memory property of economic variables. Secondly, the effect of externally stochastic perturbation on the average of capital is studied, and the result shows random excitation can not only impede but also promote the development of the economy.

In this paper we compute topological entropy with prescribed accuracy for different economic models, showing the existence of a topologically chaotic regime for them. In order to make the paper self-contained, a general overview on the topological entropy of continuous interval maps is given. More precisely, we focus on piecewise monotone maps which often appear as dynamical models in economy, but also in population growth and physics. Our main aim is to show that when topological entropy can be approximated up to a given error, it is a useful tool which helps to analyze the chaotic dynamics in one dimensional models.

A periodic predator-prey model has been introduced in [5] to study the effect of water level on persistence or extinction of fish populations living in an artificial lake. By using the continuation theorem of Mawhin’s coincidence degree theory, the authors give sufficient conditions for the existence of at least one positive periodic solution. In this paper we study the problem in the general case. We begin by analyzing the invariance, permanence, non-persistence and the globally asymptotic stability for the system. Most interestingly, under additional conditions, we find that the periodic solution obtained in [5] is unique. Finally, in order to make the model system more realistic, we consider the special case when the periodicity in [5] is replaced by almost periodicity. We obtain conditions for existence, uniqueness and stability of a positive almost periodic solution. The methods used in this paper will be comparison theorems and Lyapunov functions. An example is employed to illustrate our result.

In this paper, an electromechanical energy harvesting system exhibiting the fractional properties and subjected to the harmonic excitation is investigated. The main objective of this paper is to discuss the system performance with parametric coupling and fractional derivative. The dynamic of the system is presented, plotting bifurcation diagram, poincare map, power spectral density and phase portrait. These results are confirmed by using 0 − 1 test. The harmonic balance method is used with the goal to provide the analytical response of the electromechanical system. The numerical simulation validates the results obtained by this analytical technique. In addition, replacing the harmonic by the random excitation, the impact of noise intensity, the fractional order derivatives κ and the amplitude of the parametric coupling γ is investigated in detail. It points out from these results that for the best choice of D, κ and γ, the output power can be improved.

This paper surveys the latest advances of the first author's group on the three new methodologies of fractional and fractal derivatives modeling to meet the increasing and challenging demands in scientific and engineering communities. Firstly, the structural fractal was proposed as a generalization of the Euclidean distance. Using the structural metric, the structural derivative approach was derived as a significant extension of the global fractional calculus and the local fractional derivative approaches to tackle the perplexing modeling problems. The classical derivative describes the change rate of a certain physical variable with respect to time or space, which rarely takes into account the significant influence of mesoscopic time-space metric of a complex system on its physical behaviors. The structural function plays a central role in this new strategy as a kernel transform of underlying time-space structural metric of physical systems. Secondly, we employed the fundamental solution or probability density function of statistical distribution which can describe the problem of interest to construct the implicit calculus governing equation. The ‘implicit’ suggests that the explicit calculus expression of this governing equation is difficult to derive and not required. The fundamental solution or potential function of calculus governing equation and corresponding boundary conditions are sufficient to do numerical simulation. We call this strategy the implicit calculus equation modeling. Thirdly, based on the implicit calculus equation modeling approach, we introduced the concept of fundamental solution on fractal and consequently defined the fractal differential operator to describe various mechanical behaviors of fractal materials. Fractal calculus operator significantly extends the application scope of the classical calculus modeling approach under the framework of continuum mechanics. This is also a step-forward advance of the fractal derivative proposed earlier by the first author. To demonstrate the structural derivative application, we applied the inverse Mittag-Leffler function as the structural function to model ultraslow diffusion of a random system of two interacting particles. On the other hand, this paper uses the fractional Riesz potential as the fundamental solution to establish the implicit calculus equation of fractional Laplacian modeling the power law behaviors of steady heat conduction in multiple phase material. Finally, by using the singular boundary method, we made numerical simulation of the fractal Laplacian equation for phenomenological modeling potential problems in fractal media. Numerical experiments show that all the three new methodologies are feasible mathematical tools to describe complex physical behaviors.

This paper presents a new chaotic system that exhibits a two wing (2W) chaotic attractor in its integer order dynamics, three-wing (3W) and four-wing (4W) chaotic attractors in its fractional-order (FO) dynamics, and an eight-wing (8W) attractor in its nonautonomous fractional dynamics. An interesting feature of the proposed system is that two distinct periodic orbits coexist with a strange attractor that gradually evolves into a 4W attractor. The asymmetry, dissimilarity and topological structure of this proposed system with respect to those available in literature, manifest increased irregularity, which in turn indicate more chaos. Besides, the authors have drawn its comparison with various well-known fractional-order chaotic systems (FOCS)s to prove its enhanced features in terms of higher Lyapunov Exponent, fractional order orbital velocities, bandwidth, density, range of dynamical behaviour, etc. A control scheme is proposed to enable switching hybrid synchronisation between the 8W nonautonomous FOCS and the 4W autonomous FOCS, using the former as master and the latter as slave. This work throws light on the potential practical applicability of the proposed system by designing a circuit using minimum circuit components possible, thus signifying the objectives of the paper are finally achieved.

This paper presents a synopsis of fractional calculus tools for characterising respiratory mechanics. A discussion on power law impedance, viscoelasticity and tissue heterogeneity is made based on morphological and structural properties of lungs. Although targeted towards respiratory system applications, these tools can serve as a basis for modelling other biological structures as well. The paper underlines the importance of characterising the viscoelastic properties of the respiratory tissue and its time-varying properties as a function of disease progress. Perspectives are suggested for developing models able to mimic disease progression and understand treatment effects for better therapeutic management.

In this paper, we study the effect of stochastic noise on the virus infection model with nonlytic immune response. Firstly, the mathematical model describing the virus infection with nonlytic immune response is presented. The basic reproduction number is derived and the stability of disease-free state E0 and disease state E1 are analysed. Then the threshold conditions for extinction and persistence of the virus are derived by the rigorous theoretical proofs. It is found that when the noise is large enough, the virus will die out without constraint. When the noise is small, the virus will become extinct under the condition R 0 * 1 and persistence under R 0 * * > 1 . Besides, the upper bound and lower bound for persistence have been given. At last, some numerical simulations are carried out to support our results. The conclusion of this paper could help provide the theoretical basis for the further study of the virus infection.

In this paper, we propose a new method to improve the safety of secure communication. This method uses the generalized dislocated lag projective synchronization and function projective synchronization to form a new generalized dislocated lag function projective synchronization. Moreover, this paper takes the examples of fractional order Chen system and Lu system with uncertain parameters as illustration. As the parameters of the two systems are uncertain, the nonlinear controller and parameter update algorithms are designed based on the fractional stability theory and adaptive control method. Moreover, this synchronization form and method of control are applied to secure communication via chaotic masking modulation. Many information signals can be recovered and validated. Finally, simulations are used to show the validity and feasibility of the proposed scheme.

This paper presents the influence of two kinds of variable growth hypernetworks on the scaling law of hypernetworks. Our model can be degenerated to the original evolving model. On one hand, we establish the variable growth of hyperedges evolving hypernetworks model and obtain the stationary average hyperdegree distribution of the model by employing the Poisson process theory and the continuous method. The theoretical analyses in this paper agree with the conducted numerical simulations. The results show that the transient average hyperdegree distribution of the hypernetwork follows the scale-free law. However, the stationary average hyperdegree distribution does not, which indicates that the number of hyperedges at each time step affects the scaling law of hypernetworks. On the other hand, we establish the new nodes variable growth hypernetworks model and obtain analytical solutions of the transient average hyperdegree distribution. We simulate to compare the different node growth rate effect on the hyperdegree distribution characteristics. The results show that the growth rate does not affect the scaling law properties of the hypernetworks. Only when λ = 1 can we obtain analytical solutions of stationary average hyperdegree distribution of the hypernetwork which is not scale-free law.

This paper focuses on the finite-time synchronization for a class of delayed drive-response complex-valued neural networks. By using inequality techniques and designing two kind of different exponential controllers of time variable, two criteria to assure the finite-time synchronization for the discussed drive-response delayed complex-valued neural networks are obtained. Since in the practice, it is reasonable to introduce the time variable t into the controllers designed, hence, our controllers designed related to the time variable and errors perform better than ones in the existing papers. Since some inequalities are used in our paper, our results on the finite-time synchronization are novel.

Yilmaz et al. (Fluct. Noise Lett. 17, 1830002, 2018) investigated the stochastic phenomenological bifurcations of a generalized Chua circuit driven by Skew-Gaussian distributed noise. They proved it is possible to decrease the number of scrolls by properly choosing the stochastic excitation, manipulating the skewness and noise intensity parameters. Based on the latter, this paper proposes an extension of skew-gaussian noise based on the family of Scale Mixtures of Skew-normal (SMSN) distributions, which includes the skew- t , the skew-gaussian, and the gaussian noises as particular cases. The Lorenz, Generalized Lorenz, Proto–Lorenzand Rossler attractors driven by skew- t distributed noise are considered. Results show that the chaotic regime’s behavior is influenced by the freedom parameter degrees of skew- t noise, increasing the noise variance. This paper concludes that noise intensity increases by rescaling the skew- t distribution at zero mean, rather than by increasing the asymmetry parameter.

Urban spatial system is a pre-fractal system, which has a sensitive reaction zone similar to the self-organized critical state (SOC) of complex systems on different spatial scales. In this paper, theoretical analysis includes the interpretation of multifractal dimension spectrum (f(a)-a(q) fitted curve) and its parameters. According to q-value distribution area, the fitted curve is divided into interval A (typical multifractal system distribution), interval B (atypical multifractal system distribution) and interval C (mediocre distribution). Furthermore, this paper launches a case study of the four-year period of construction land in Zhengzhou since the reform and opening up to reveal the spatial-temporal evolution features and operational mechanism of this region from a broader dimension. Analysis shows that Zhengzhou's development has long been in a spatial development trend dominated by chaos (interval B) and mediocrity (interval C), and the influence of q-level with spatial multifractal feature (interval A) on each spatial scale is relatively weak. Until the 2010s, multifractal feature tends to be strengthened, and there is a tendency to dominate regional spatial evolution. The significance of this study is that the combination and evolution of three intervals of the f(a)-a(q) fitting curve can be used to reflect the trend and regularity of regional spatial multifractal system and spatial-temporal succession relationship between them, so as to deeply understand the inherent and complete development and evolution of the geographical objects.