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The precise identification of drug–protein inter action (DPI) can significantly speed up the drug discovery process. Bioassay methods are time-consuming and expensive to screen for each pair of drug proteins. Machine-learning-based methods cannot accurately predict a large number of DPIs. Compared with traditional computing methods, deep learning methods need less domain knowledge and have strong data learning ability. In this study, we construct a DPI prediction model based on dual channel neural networks with an efficient path attention mechanism, called DCA-DPI. The drug molecular graph and protein sequence are used as the data input of the model, and the residual graph neural network and the residual convolution network are used to learn the feature representation of the drug and protein, respectively, to obtain the feature vector of the drug and the hidden vector of protein. To get a more accurate protein feature vector, the weighted sum of the hidden vector of protein is applied using the neural attention mechanism. In the end, drug and protein vectors are concatenated and input into the full connection layer for classification. In order to evaluate the performance of DCA-DPI, three widely used public data, Human, C.elegans and DUD-E, are used in the experiment. The evaluation metrics values in the experiment are superior to other relevant methods. Experiments show that our model is efficient for DPI prediction. [ABSTRACT FROM AUTHOR]

The hypersonic local-correlation-based transition modeling (LCTM) and amplification factor transport (AFT) transition models are extended to crossflow-induced transitions and applied to three-dimensional hypersonic vehicles. A new crossflow Reynolds number correlation is proposed and implanted to an existing hypersonic LCTM to extend it to take account of the crossflow effect. In the hypersonic AFT model, a new transport equation is added to predict the transported crossflow amplification factor. The two improved transition models are first validated using the HIFiRE-5 configuration. The results demonstrate that both transition models predict the transition on HIFiRE-5 with reasonable accuracy. Next, the two models are applied to the X-51A forebody and the X-33 vehicle. The results show that both models are capable of predicting transition behaviors and aeroheating environments on hypersonic complex geometries. The two models also provide reasonable reflections of the effects of various factors that influence transition, including the freestream Reynolds number, turbulence level, and angle of attack. [ABSTRACT FROM AUTHOR]

To explore the rumor propagation dynamics in online social networks (OSNs) and propose the corresponding control strategies, a novel Ignorants-Spreaders-1-Spreaders-2-Removers (I2SR) rumor-spreading model with general incidence is first formulated in heterogeneous networks. This model covers the bilinear incidence and nonlinear incidence, and considers the time delay in the rumor-spreading process, which is universal and practical. We analytically derive the basic reproduction numbers, which determine the existence of rumor-spreading equilibria but also the global dynamics of the model. Moreover, the Lyapunov–LaSalle principle and the graph-theoretic approach prove the global asymptotic stability of the rumor-free/rumor-spreading equilibria in detail. Significantly, the effects of various strategies, including uniform control, targeted control, and acquaintance control, are implemented and compared. Finally, the developed theoretical results are tested via numerical simulations and a real case data of rumors, showing that the model can more accurately simulate rumor-spreading in OSNs. [ABSTRACT FROM AUTHOR]

The presence of information asymmetry can hinder the public's ability to make well-informed decisions, resulting in unwarranted suspicion and the widespread dissemination of rumors. Therefore, it is crucial to provide individuals with consistent and dependable scientific education. Regular popular science education is considered a periodic impulsive intervention to mitigate the impact of information asymmetry and promote a more informed and discerning public. Drawing on these findings, this paper proposes a susceptible-hesitant-infected-refuting-recovered (SHIDR) rumor-spreading model to explain the spread of rumors. The model incorporates elements such as time delay, nonlinear incidence, and refuting individuals. Firstly, by applying the comparison theorem of an impulsive differential equation, we calculate two thresholds for rumor propagation. Additionally, we analyze the conditions of global attractiveness of the rumor-free periodic solution. Furthermore, we consider the condition for the rumor's permanence. Finally, numerical simulations are conducted to validate the accuracy of our findings. The results suggest that increasing the proportion of impulsive vaccination, reducing the impulsive period, or prolonging the delay time can effectively suppress rumors. [ABSTRACT FROM AUTHOR]

This work aims to achieve cluster synchronization of a complex network by some pinning control strategies. Firstly, the network not only is affected by the reaction–diffusion and the directed coupling phenomena, but also is disturbed by the stochastic noise and Markovian switching. Secondly, switched constant gain pinning, centralized and decentralized adaptive pinning are proposed respectively to realize the cluster synchronization of the considered network. In these adaptive pinning controllers, the control gain and coupling strength can been adjusted automatically while only a part of the nodes are controlled. Thirdly, the target state of cluster synchronization is taken as the average state related to the directed topology of all nodes in the same cluster, and does not need to be given separately as an isolated node. Finally, to verify the theoretical results, some simulations of directed coupled reaction–diffusion neural networks with stochastic noise and Markovian switching are given. [ABSTRACT FROM AUTHOR]

Considering the media coverage and age‐dependent education, a deterministic and a stochastic class‐age‐structured rumor propagation models are studied, respectively. First, the deterministic rumor propagation model is characterized by a coupled system of ordinary and partial differential equations. The positivity and boundness of solutions are proved, and the basic reproduction number is derived. Second, the stochastic rumor propagation model is formulated by stochastic differential equations. The existence of global positive solutions in model is discussed with the Itô's formula and stochastic Lyapunov function. Additionally, by utilizing comparison principle of stochastic differential equations and the strong law of large numbers, several sufficient conditions for extinction and persistence of the rumor are derived. Finally, numerical simulations are carried out for illustrating the results. [ABSTRACT FROM AUTHOR]

This article addresses the fixed-time (F-T) and predefined-time (P-T) cluster lag synchronization of stochastic multi-weighted complex networks (SMWCNs) via strictly intermittent quantized control (SIQC). Firstly, by exploiting mathematical induction and reduction to absurdity, a novel F-T stability lemma is proved and an accurate estimation of settling time (ST) is obtained. Subsequently, by virtue of the proposed F-T stability, some simple conditions that ensure the F-T cluster lag synchronization of SMWCNs are derived by developing a SIQC strategy. Furthermore, the P-T cluster lag synchronization is also explored based on a SIQC design, where the ST can be predefined by an adjustable constant of the controller. Note that the designed controllers here are simpler and more economical than the traditional design whose the linear part is still activated during the rest interval. Finally, two numerical examples are provided to verify the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

Due to the widespread presence of disturbances in practical engineering and widespread applications of high-order systems, this paper first pays attention to a class of high-order strict-feedback nonlinear systems subject to bounded disturbance and investigates the prescribed performance tracking control and anti-disturbance control problems. A novel composite control protocol using the technique of a disturbance observer—prescribed performance control—is designed using the back-stepping method. The disturbance observer is introduced for estimating and compensating for unknown disturbances in each step, and the prescribed performance specifications guarantee both transient and steady-state performance of the tracking error to improve the control performance and result in better disturbance rejection. Moreover, the technique of adding a power integrator is modified to tackle controller design problems for the high-order systems. The Lyapunov function method is utilized for rigorous stability analysis. It is revealed that while the control performance completely remains in the prescribed bound, all states in the closed-loop system are input-to-state stable, and the tracking error and the disturbances estimating error asymptotically converge to zero simultaneously. Then, the feasibility and effectiveness of the proposed control protocol are verified by a simulation result. [ABSTRACT FROM AUTHOR]

An improved photothermal technique for evaluating opaque coating thicknesses using a normalized DC component is proposed. The pump beam is modulated at a frequency that the generated thermal wave only exists in the coating layer and becomes invariant to the thickness changes. The DC component is normalized by the amplitude of the AC signal in order to eliminate the dependency on the pump intensity, surface absorptivity, and emissivity. Both theoretical analysis and experimental results demonstrate that the normalized DC component is linearly correlated to the coating thickness over a broad range. This method offers a significant advantage over existing photothermal methods by avoiding the tedious procedure of frequency trails for coatings of an unknown thickness. Also, the non-monotonic issue is successfully resolved. [ABSTRACT FROM AUTHOR]

Fixed-time stability (FXTS) and fixed-time control (FXTC) of dynamic systems are reconsidered in this article based on special functions from the view of improving the estimate accuracy of settling time (ST) and reducing the chattering caused by the sign function. First, by means of the idea of contradiction and variable transformations, some generic FXTS criteria are established and some upper bounds of ST are directly calculated and expressed by several special functions. It is further proved that these estimates are the most accurate compared with the existing results. Besides, to suppress the chattering caused by the sign function, some saturation functions are constructed to replace the sign function and the FXTS of the new system obtained by replacing is ensured by rigorous theoretical analysis. As applications, the problem of stabilization for chaotic systems in fixed or preassigned time is explored. Especially, an innovative saturation controller is developed to realize preassigned-time stabilization, where the convergence time is prescribed in advance according to actual requirement and the control gains are finite, the existing control methods with time-varying infinite gains are essentially improved. Lastly, three numerical examples are provided to verify the improved estimates of ST and the chattering reduction. [ABSTRACT FROM AUTHOR]

Objective To evaluate the efficacy and safety of the Jianpi Bushen Jiedu formula combined with apatinib and tegafur/gimeracil/oteracil (S-1) for patients with metastatic colorectal cancer (mCRC). Methods A single-arm, open-label clinical study was conducted. The patients were treated with the Jianpi Bushen Jiedu formula combined with a low dose of apatinib (250 mg, once per day) and S-l (20 mg, twice per day). The primary outcome was progression-free survival (PFS), and secondary outcomes included the objective remission rate (ORR), the disease control rate (DCR), overall survival (OS), and the MD Anderson Symptom Inventory for Traditional Chinese Medicine (MDASI-TCM) score. Results The median PFS and median OS of the treatment of the Jianpi Bushen Jiedu formula combined with apatinib and S-l were 4. 80 months and 12.73 months, respectively. The ORR was 7.32% (3/41) while the DCR was 68.29% (28/41). The score of the MDASI-TCM did not fall. The common adverse events were hypertension, proteinuria, thrombocytopenia, and bleeding, with incidences of 51.22%, 41.46%, 26.83%, and 19.51%, respectively. Conclusion Patients with mCRC, especially after the failure of the second or above lines of treatment or without treatment with previous bevacizumab may potentially benefit from the treatment with the Jianpi Bushen Jiedu formula combined with low dose apatinib and S-l. [ABSTRACT FROM AUTHOR]

This paper is devoted to investigating the impact of the recurrence of rumors and individual behaviors and control strategies related to rumor spreading in online social networks. To do this, a novel susceptible-hesitating-infected-latent-recovered (SHILR) rumor propagation model in heterogeneous networks is presented. Firstly, based on the relevant mean-field equations of the model, the threshold value is examined to demonstrate the existence and stability of rumor-free/spreading equilibrium with the help of the algebraic method. Secondly, the global stabilities of the equilibria are analyzed through applying Lyapunov stability theory and LaSalle's invariance principle. Next, the optimal control is proposed by taking advantage of Pontryagin's maximum principle for reducing the number of infected individuals with minimum cost. Moreover, some numerical examples are carried out to test the theoretical results. Finally, combined with practice, a model application is presented. [ABSTRACT FROM AUTHOR]

This study sets out to solve the synchronization problem of complex-valued multi-layer coupled systems (CVMLCSs) under two asynchronous intermittent event-triggered mechanisms (IETMs). Unlike the existing works on IETM, two kinds of novel IETMs including static IETM and dynamic IETM are developed, where the asynchronous nature is mainly reflected in the fact that each node in each layer possesses its own control and rest intervals. Remarkably, under two control schemes, the choice of control time sequence is based on corresponding event-triggered condition rather than being preset artificially. Moreover, by utilizing graph theory and Lyapunov approach, two synchronization conditions for CVMLCSs are given, respectively. In the end, as an application, a complex-valued multi-layer neural network model is established and some numerical examples are provided to validate the feasibility of the theoretical results. • A new model of time-varying complex-valued multi-layer coupled systems is built. • Two novel asynchronous intermittent event-triggered mechanisms are proposed. • Two controllers remove the limitation on artificial selection of control time sequence. [ABSTRACT FROM AUTHOR]

This study addresses the fixed/preset-time bipartite synchronization (FTBS/PTBS) of memristor-based discontinuous multi-layer signed networks via quantized dynamic event-triggered control (ETC). Firstly, a memristor-based neural network model incorporating multi-layer coupling structures, signed networks and discontinuous activations is built. Subsequently, by designing two quantized dynamic ETC strategies without the linear feedback term, the FTBS and PTBS of the considered networks are discussed, and it is proved that Zeno behavior can be ruled out. In contrast to the previous static ETC mechanism, the introduced internal dynamic variable can significantly decrease the triggering times and further save communication resources. Lastly, three numerical examples are offered to verify the correctness and practicability of the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper investigates the exponential passivity of discrete-time switched neural networks (DSNNs) with transmission delays via an event-triggered sliding mode control (SMC). Firstly, a novel discrete-time switched SMC scheme is constructed on the basis of sliding mode control method and event-triggered mechanism. Next, a state observer with transmission delays is designed to estimate the system state. Moreover, some new weighted summation inequalities are further proposed to effectively evaluate the exponential passivity criteria for the closed-loop system. Finally, the effectiveness of theoretical results is showed through a simulative analysis on a multi-area power system. • Network communication is embedded into the DSNNs modeling, and the network-induced time delays are consiederd here. • Combined with sliding mode control and event-triggered mechanism, a discretetime switched SMC method is proposed to reduce the impact of network delays, and make the closed-loop system meet the performance index while ensuring its stability. • Some new weighted summation inequalities are further proposed to reduce the conservatism of exponential passivity criteria. • A practical example of a multi-area power system is utilized to demonstrate the validity ofproposed control approaches. [ABSTRACT FROM AUTHOR]

An Innocents-Spreaders-Calmness-Removes (ISCR) rumor propagation model is established with nonlinear incidence and time delay on complex networks in this paper. Based on the mean-field theory, the spreading dynamics of the ISCR model are discussed in detail. Firstly, the basic reproduction number R 0 is obtained by the next generation matrix method to ensure the existence of rumor-prevailing equilibrium. Secondly, by utilizing the Routh–Hurwitz criterion and LaSalle's invariance principle, the local stability and global stability of rumor equilibria are proved. Moreover, the optimal control is presented via Pontryagin's minimum principle, which is to effectively restrain rumor diffusion. Finally, the theoretical results are verified by numerical simulations. [ABSTRACT FROM AUTHOR]

Background: Children with early-onset scoliosis living in high-altitude areas have severe deformities and poor nutritional status. However, no reports on early-onset scoliosis treatment using traditional growing rods in such children exist. Thus, we analyzed the outcomes of traditional growing rods treatment in such patients and the effect of altitude on therapy. Methods: Between September 2007 and December 2017, 59 consecutive patients with EOS underwent systematic surgical correction using traditional growing rods. They were divided into the high-altitude and low-altitude groups, and differences in surgical efficacy and complications between the groups were analyzed pre- and postoperatively. Radiographic measurements, including the Cobb angle, thoracic kyphosis, lumbar lordosis, T1–S1 and T1–T12 heights, sagittal and coronal balance, distance between C7PL and sagittal vertical axis, pelvic incidence, sacral slope, and pelvic tilt were assessed preoperatively, postoperatively, and at the last follow-up. Continuous data were analyzed using paired or independent Student's t tests, and they were compared preoperatively, postoperatively, and at the last follow-up using a repeated measures analysis of variance. Enumerated data were analyzed using the χ2 test. Results: The mean patient age at the initial surgery and mean follow-up duration were 8.9 ± 2.4(5–14) years and 51.91 ± 25.23 months, respectively. Altogether, 234 operations were conducted for all patients with an average interval between operations of 11.4 ± 3.0 months. The average Cobb angle was similar in both groups preoperatively and at the last follow-up, it was significantly different postoperatively. TK was significantly different in all three periods. T1–S1 and T1–T12 heights were significantly different only during the preoperative period. The overall rates of complications and implant-related complications did not differ significantly between the groups. Conclusions: Deformity in patients with EOS in high-altitude areas was more severe, and treatment using TGRs yielded a satisfactory therapeutic effect. [ABSTRACT FROM AUTHOR]

In this article, we considered the fixed‐time stability (FXT) of a type of discontinuous dynamical system. First, we introduced some new FXT stability results via variable substitutions and using inequality techniques, which are more accurately estimate the upper bound of settling time (ST). Then, based on the established results and using the differential inclusion theory, we investigated the FXT synchronization of a type of general neural networks (NNs) with state‐dependent switching coefficients and discontinuous neuron activation functions via introducing a type of discontinuous controller which is more simple compared to existing results. In addition, the estimated upper bound of ST shown to be independent to the initial values of considered drive‐response networks, and it is much smaller and nearer to the real synchronization time than those given in the previously published works. Lastly, two numerical examples are given to demonstrate the feasibility of our derived theoretical results. We believe that the results of this article can give some new insights for the FXT stabilization and FXT synchronization analysis of state‐dependent switching dynamics with or without discontinuous right‐hand sides. [ABSTRACT FROM AUTHOR]

This paper is concerned with the synchronization of fractional-order competitive neural networks with reaction–diffusion terms and time delays. A novel method that combines the fractional-order Lyapunov theorem with M-matrix theory is utilized to cope with synchronization for the addressed networks. Based on such approach and developing two different controllers, some sufficient criteria are derived to guarantee global synchronization by employing the properties about Mittag–Leffler and trigonometric functions, comparison principle as well as the method of contradiction. Finally, a numerical example is provided to show the effectiveness of the established result. [ABSTRACT FROM AUTHOR]

In this paper, the fixed-time and preassigned-time synchronization issues of fully quaternion-valued fuzzy memristive neural networks are studied based on the dynamic event-triggered control mechanism. Initially, the fuzzy rules are defined within the quaternion domain and the relevant properties are established through rigorous analysis. Subsequently, to conserve resources and enhance the efficiency of the controller, a kind of dynamic event-triggered control mechanism is introduced for the fuzzy memristive neural networks. Based on the non-separation analysis, fixed-time and preassigned-time synchronization criteria are presented and the Zeno phenomenon under the event-triggered mechanism is excluded successfully. Finally, the effectiveness of the theoretical results is verified through numerical simulations. [ABSTRACT FROM AUTHOR]

This paper studies the finite-time synchronization issue of stochastic complex networks (SCNs) with random coupling delay and nonlinear coupling function. Internal delay, perturbation delay are also considered into this model. Meanwhile, a quantized aperiodically intermittent control strategy is proposed to realize finite-time synchronization of SCNs. By means of Lyapunov stability theory and graph theory, two types of sufficient conditions are derived to ensure finite-time synchronization of SCNs. The obtained results are closely related to the maximum proportion of rest width and the topological structure of considered networks. Moreover, the theoretical results is applied to study finite-time synchronization of stochastic coupled oscillators. Finally, a numerical example is presented to demonstrate the effectiveness and feasibility of the obtained results. [ABSTRACT FROM AUTHOR]

The study investigates bipartite synchronization of inertial coupled delayed neural networks (ICDNNs) with signed digraph by non-reduced order method and pinning control. The second-order CDNNs will not be converted into a first-order differential system by introducing variable substitution. Instead, a novel Lyapunov–Krasovskii functional is proposed which depends on the topology of the ICDNNs. Some sufficient conditions for linear matrix inequalities (LMI) are derived to realize bipartite synchronization, which is based on matrix decomposition theory and Barbalat Lemma in strongly connected signed networks. And then, M-matrix theory is utilized to generalize the results to networks containing directed spanning trees. Finally, two examples are used to verify the validity of the derived theoretical results. [ABSTRACT FROM AUTHOR]

A neural network model upon differential inclusion is designed for solving the complex-variables convex programming, and the chain rule for real-valued function with the complex-variables is established in this paper. The model does not need to choose penalty parameters when applied to practical problems, which makes it easier to design. The result is obtained that its state reaches the feasible region in finite time. Furthermore, the convergence for its state to an optimal solution is proved. Some typical examples are shown for the effectiveness of the designed model. [ABSTRACT FROM AUTHOR]

This paper considers the prescribed-time event-triggered consensus for a class of nonholonomic multi-agent systems (MASs) with external disturbances. Firstly, the nonholonomic chained MASs are divided into two subsystems, and a switching control scheme is introduced. Secondly, a distributed prescribed-time continuous protocol is proposed to ensure that all agents reach average consensus within a prescribed finite-time. Moreover, to reduce the communication costs, an event-triggered consensus protocol is further established and some related theorems are given. In addition, the Zeno behaviour can be excluded by choosing parameters appropriately. Finally, two numerical examples are presented to demonstrate the effectiveness of the proposed protocols. [ABSTRACT FROM AUTHOR]

In this paper, without transforming the quaternion-valued neural networks into two equivalent complex-valued systems or four equivalent real-valued systems, a novel class of fractional-order quaternion-valued neural networks with leakage and discrete delays is investigated. To this end, two novel inequalities are established with the aid of properties of quaternion and Caputo fractional derivative. By exploiting Lyapunov method, our established inequalities, fractional-order Razumikhin theorem and some analysis techniques, some criteria ensuring the global asymptotical synchronization and the global Mittag-Leffler synchronization of the considered networks are obtained through designing suitable controllers. Finally, two numerical examples are utilized to show the derived theoretical results. [ABSTRACT FROM AUTHOR]

Projective synchronization (PS) is a type of chaos synchronization where the states of slave system are scaled replicas of the states of master system. This paper studies the asymptotic projective synchronization (APS) between master–slave chaotic neural networks (NNs) with mixed time-delays and unmatched coefficients. Based on useful inequality techniques and constructing a suitable Lyapunov functional, some simple criteria are derived to ensure the APS of considered networks via designing a novel adaptive feedback controller. In addition, a numerical example and its MATLAB simulations are provided to check the feasibility of the obtained results. The main innovation of our work is that we dealt with the APS problem between two different chaotic NNs, while most of the existing works only concerned with the PS of chaotic systems with the same topologies. In addition, compared with the controllers introduced in the existing papers, the designed controller in this paper does not require any knowledge about the activation functions, which can be seen as another novelty of the paper. [ABSTRACT FROM AUTHOR]

This work investigates the H ∞ output synchronization (HOS) of the directed coupled reaction–diffusion (R–D) neural networks (NNs) with mixed delays. Firstly, a model of the directed state coupled R–D NNs is introduced, which not only contains some discrete and distributed time delays, but also obeys a mixed Dirichlet–Neumann boundary condition. Secondly, a spacial sampled-data controller is proposed to achieve the HOS of the considered networks. This type of controller can reduce the update rate in the process of control by measuring the state of networks at some fixed sampling points in the space region. Moreover, some criteria for the HOS are established by designing an appropriate Lyapunov functional, and some quantitative relations between diffusion coefficients, mixed delays, coupling strength and control parameters are given accurately by these criteria. Thirdly, the case of directed spatial diffusion coupled networks is also studied and, the following finding is obtained: the spatial diffusion coupling can suppress the HOS while the state coupling can promote it. Finally, one example is simulated as the verification of the theoretical results. • H ∞ output synchronization for the directed coupled R–D NNs is defined. • A spacial sampled-data controller is proposed to lower spatial update rate. • Obtained conditions depend on diffusion, delay, and control parameters. • Both the directed state and spatial diffusion coupled R–D NNs are considered. • Synchronization can be suppressed by diffusion and promoted by state couple. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the problem of pinning synchronization for delayed complex directed networks via generalized intermittent adaptive control strategy is considered. First, a dynamical mode of delayed network is investigated. Second, a generalized intermittent adaptive control strategy which unified the traditional periodic intermittent control and the aperiodic case is introduced. Additionally, by constructing a piecewise Lyapunov auxiliary function and making use of piecewise analysis technique, some effective and novel criteria to ensure the global synchronization of delayed complex networks based on the designed control protocols are obtained. Finally, an example with numerical simulations is provided to demonstrate the validness of the theoretical results proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, the observer-based leader-following consensus problem for multi-agent systems with input saturation is studied under fixed and switching topology. Firstly, based on the measurable output information of systems, we construct an auxiliary observation system to estimate the real state information of systems. At the same time, the centralized event-triggered control is considered in the fixed and switching topology, and the Lyapunov function and Cauchy's convergence criterion are used to prove that the consensus of systems can be achieved. Secondly, the sufficient conditions of the event-triggered function are given, and it is proved that the constructed centralized event-triggered function can exclude the Zeno behavior. Then, the group case is considered in the fixed topology, and it is emphasized that the group event-triggered mechanism has the idea of event-triggered and decentralized control. Finally, the validity and feasibility of the theoretical results are illustrated by numerical examples. [ABSTRACT FROM AUTHOR]

In this paper, an I2S2R rumor spreading model in complex networks is established and analyzed. Firstly, the threshold value is acquired to identify the existence and stability of rumor-free equilibria state and rumor equilibria state by using the next generation matrix method. Secondly, based on Routh–Hurwitz judgment, Lyapunov stability theory and LaSalle's invariance principle, the local and global stability of rumor-free/rumor equilibrium points are discussed. Thirdly, the sensitivity analysis about the threshold value is given to analyze the impact of model parameters on rumor propagation. Finally, some numerical simulations are presented to illustrate the validity and feasibility of corresponding results. [ABSTRACT FROM AUTHOR]

In this paper, we have made an effort to investigate the general decay projective synchronization (GDPS) problem of a type of delayed memristor-based BAM neural networks. First, we introduced a type of novel nonlinear controller. Then, we derived some sufficient conditions ensuring the GDPS of considered networks by employing differential inclusion theory and using well-known Lyapunov functional method. Lastly, an example is given to show the correctness of obtained results. To the authors' knowledge, the results derived in this paper are the only available ones on the projective synchronization of BAM neural networks, combining the three main factors, i.e., memristor, general decay and time-varying delays. [ABSTRACT FROM AUTHOR]

Summary: This study is mainly concerned with the general decay synchronization (GDS) problem of a class of inertial neural networks (INNs) with time‐varying delay. First, unlike the methods used in previous relevant literature where both of the master and slave systems were transferred into the first‐order differential equations, only error dynamical system is transferred into the reduced‐order differential equation. Then, by designing a novel nonlinear output feedback controller and constructing suitable Lyapunov functionals, some simple and useful sufficient conditions ensuring the GDS of considered INNs are established via employing useful analysis techniques and linear matrix inequality approach. In addition, two examples are presented to show the effectiveness of the established theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, the edge-based and node-based adaptive algorithms are established, respectively, to solve the distribution convex optimization problem. The algorithms are based on multiagent systems with general linear dynamics; each agent uses only local information and cooperatively reaches the minimizer. Compared with existing results, a damping term in the adaptive law is introduced for the adaptive algorithms, which makes the algorithms more robust. Under some sufficient conditions, all agents asymptotically converge to the consensus value which minimizes the cost function. An example is provided for the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

This paper concerns a class of coupled competitive neural networks, subject to disturbance and discontinuous activation functions. To realize the fixed-time quasi-bipartite synchronization, an aperiodic intermittent controller is initially designed. Subsequently, by combining the fixed-time stability theory and nonsmooth analysis, several criteria are established to ensure the bipartite synchronization in fixed time. Moreover, synchronization error bounds and settling time estimates are provided. Finally, numerical simulations are presented to verify the main results. [ABSTRACT FROM AUTHOR]

This article concerns the fixed-time (FET) and prescribed-time (PET) synchronization of quaternion-valued fuzzy BAM neural networks via aperiodic intermittent pinning control. First of all, two improved inequalities for FET and PET stability are proposed to reduce the conservatism of existing results in theoretical analysis. Subsequently, by excluding the control input of the rest interval in previous semi-intermittent design, two novel quaternion-valued aperiodic intermittent pinning controllers are developed. Furthermore, regarding the original quaternion-valued networks as an entirety instead of decomposing it into four real-valued subnetworks, several sufficient criteria that ensure the FET and PET synchronization of quaternion-valued fuzzy BAM neural networks are obtained by means of the improved stability inequalities and the designed controllers. Finally, the validity of the theoretical results is verified by three numerical examples. [ABSTRACT FROM AUTHOR]

This article aims to address the exponential bipartite synchronization (EBS) issue of multilayer signed stochastic coupled neural networks under the fully aperiodic intermittent pinning control (FAIPC) strategy. At first, a network model incorporating stochastic perturbations, multilayer signed graphs and multiple time-varying delays is built. Subsequently, instead of the maximum rest rate condition, by means of the average control rate of aperiodically intermittent control, an improved differential inequality is established to reduce the conservatism of existing results. Furthermore, by employing the presented differential inequality and stochastic analysis technique, some sufficient conditions for ensuring mean square EBS are obtained based on FAIPC with constant control gains and FAIPC with adaptive control gains, respectively. Finally, the availability of the theoretical results is verified by some numerical simulations. [ABSTRACT FROM AUTHOR]

Summary: The dissipativity of discrete‐time switched memristive neural networks with actuator saturation is considered in this paper. By constructing a quasi‐time‐dependent Lyapunov function, sufficient conditions are obtained to guarantee the exponential stability and exponential dissipativity for the closed‐loop system with mode‐dependent average dwell time switching. Furthermore, the exponential H∞ performance of discrete‐time switched memristive neural networks is also analyzed, while the quasi‐time‐dependent controller and observer gains of the desired exponential dissipative and H∞ performance can be calculated from linear matrix inequalities. Finally, the effectiveness of theoretical results is illustrated through the numerical examples. [ABSTRACT FROM AUTHOR]

In this paper, the guaranteed cost consensus problem for second-order multi-agent systems with directed topology is considered, in which each agent has a heterogeneous inertia and control gain. The distributed control protocols with the absolute and relative velocity dampings are proposed, respectively. In each kind of protocol, both the communications with and without the input time delay are also considered. By introducing the auxiliary variables and using Lyapunov stability theory, some sufficient conditions are given to achieve the consensus. Moreover, the upper bounds of the guaranteed cost functions are obtained. Finally, some simulation examples are presented to show the effectiveness of the proposed approaches. [ABSTRACT FROM AUTHOR]