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Objectives: To investigate the clinical characteristics and molecular epidemiology of CRKP infection in neonatal patients in a children’s hospital in China from 2017 to 2021. Methods: Species identification and antibiotic susceptibilities were tested with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and VITEK 2 systems. The clinical data were collected from medical records. Carbapenem-resistant Klebsiella pneumoniae(CRKP) isolates were investigated by antimicrobial susceptibility testing, carbapenemase genes and multilocus sequence typing. Results: Six kinds of resistant genes and 23 STs were detected. BlaNDM-1(n=83, 55.3%) was the predominant carbapenemase gene, followed by blaKPC-2(n=45, 30.0%), blaNDM-5(n=7, 4.7%), blaIMP-38(n=6, 4.0%). BlaNDM-1was predominant in 2017 and 2018, whereas blaKPC-2increased in 2019 and became the predominant gene from 2020 to 2021. ST11 accounted for most infections (n=35, 23.3%), followed by ST278 (n=23, 15.3%), ST17 (n=17, 11. 3%) and ST2735 (n=16, 10.7%). ST278 and ST17 were predominant in 2017 and 2018, whereas ST11 increased in 2019 and became the predominant sequence type from 2020 to 2021. Compared with blaNDM-1, the CRKP strains producing blaKPC-2were characterized by high resistance to gentamicin, amikacin and levofloxacin and the change trend of drug resistance rate before and after COVID-19 was consistent with that of blaNDM-1and blaKPC-2. Conclusions: The main sequence type of CRKP infection changed dynamically from ST278-NDM-1 to ST11-KPC-2 during the years 2017–2021 in the newborns. Antibiotic exposure and the prevalence of COVID-19 since 2020 may have led to changes in hospital population and lead to the changes.

This paper concerns ultimately bounded output-feedback control problems for networked systems with unknown nonlinear dynamics. Sensor-to-observer signal transmission is facilitated over networks that has communication constraints. These transmissions are carried out over an unreliable communication channel. In order to enhance the utilization rate of measurement data, a buffer-aided strategy is novelly employed to store historical measurements when communication networks are inaccessible. Using the neural network technique, a novel observer-based controller is introduced to address effects of signal transmission behaviors and unknown nonlinear dynamics. Through the application of stochastic analysis and Lyapunov stability, a joint framework is constructed for analyzing resultant system performance under the introduced controller. Subsequently, existence conditions for the desired output-feedback controller are delineated. The required parameters for the observer-based controller are then determined by resolving some specific matrix inequalities. Finally, a simulation example is showcased to confirm method efficacy.

This paper focuses on the quadratic nonfragile filtering problem for linear non-Gaussian systems under multiplicative noises, multiple missing measurements as well as the dynamic event-triggered transmission scheme. The multiple missing measurements are characterized through random variables that obey some given probability distributions, and thresholds of the dynamic event-triggered scheme can be adjusted dynamically via an auxiliary variable. Our attention is concentrated on designing a dynamic event-triggered quadratic nonfragile filter in the well-known minimum-variance sense. To this end, the original system is first augmented by stacking its state/measurement vectors together with second-order Kronecker powers, thus the original design issue is reformulated as that of the augmented system. Subsequently, we analyze statistical properties of augmented noises as well as high-order moments of certain random parameters. With the aid of two well-defined matrix difference equations, we not only obtain upper bounds on filtering error covariances, but also minimize those bounds via carefully designing gain parameters. Finally, an example is presented to explain the effectiveness of this newly established quadratic filtering algorithm.

This technical paper investigates the cluster synchronization of finite-field networks (FFNs) based on the algebraic state space representation. By resorting to the semi-tensor product of matrices, the cluster synchronization of an FFN can be completely converted into the set stability of state trajectory. Then, a necessary and sufficient condition for the cluster synchronization of FFNs is obtained based on the invariant subset and one-step transition matrix. In particular, the obtained results are applicable to check the leader–follower synchronization and group consensus of FFNs. Finally, a numerical example is given to illustrate the feasibility of the obtained results.

In this article, observable stochastic graphs and detetectable stochastic graphs are, respectively, defined with the detailed implementation for the observability and detectability of stochastic discrete-time and discrete-state dynamic systems. More specifically, they are generally two classes of vertex-colored and edge-labeled graphs rendering a walking agent therein to determine his initial and current positions, respectively, in probability one by measuring the color sequence of his traversed vertices. In the part of analysis, we follow the aforementioned two definitions and establish the corresponding polynomial-time verifying algorithms. Notably, the implicit formulas are also established to calculate the observability and detectability probability for any pairwise vertex pair. In the synthesis part, the minimal number of colors dyeing the vertices to make the considered graph stochastically observable and detectable is investigated, respectively. Our results indicate that the minimal coloring problem is NP-hard for observability in the stochastic situations but is solvable in polynomial time for detectability in the deterministic cases. The observability and detectability of stochastic finite-valued systems, assembling with the finite-cardinal state spaces, are validated as a compelling application of these two types of directed graphs, whereas the minimal sensors placement problems subject to observability and detectability problems are accordingly interpreted by the minimum set cover algorithm.

This article covers the identification of the feedback nonlinear systems. The parameterized nonlinear identification model involves products of system nonlinear part parameters and system linear part parameters. To deal with these product terms, the hierarchical identification based on maximum likelihood is used to decompose the system into two subsystems. The Levenberg–Marquardt and particle swarm optimization methods are applied for identifying the two subsystems, respectively. For the purpose of enhancing the optimization capability of the basic particle swarm optimization method, some improvement strategies are constructed. Thus, the improved particle swarm optimization algorithm which combines the adaptive feedback, the linearly decreasing method and the mutational operator is applied to adaptively adjust the search strategy and improve the ergodicity. The simulation indicates that the derived estimation is effective because it can obtain high identification accuracy and fast convergence speed when identifying the feedback systems. Besides, the case study demonstrates that the proposed method can be well used to identify the electro-hydraulic-servo position system.

In this article, the distributed model predictive control (MPC)-based noncooperative game problem is dealt with for the discrete-time multiplayer systems (MPSs) with an undirected graph. To reflect the reality, the state and input constraints are considered along with the matched disturbances and unmatched disturbances. The disturbance-observer-based composite MPC strategy is put forward which optimizes a given cost function over the receding horizon while eliminating the matched disturbances. An iterative algorithm is developed such that the model predictive dynamic game (MPDG) converges to the so-called $\varepsilon $ -Nash equilibrium in a distributed manner. Sufficient conditions are established to guarantee the convergence of the proposed algorithm. In addition, easy-to-check conditions are also provided to ensure the uniform boundedness of the studied MPSs. Finally, a numerical example of a group of spacecrafts is provided to verify the effectiveness of the proposed methodology.

This paper is concerned with the problem of finite-horizon energy-to-peak state estimation for a class of networked linear time-varying systems. Due to the inherent vulnerability of network-based communication, the measurement signals transmitted over a communication network might be intercepted by potential eavesdroppers. To avoid information leakage, by resorting to an artificial-noise-assisted method, we develop a novel encryption-decryption scheme to ensure that the transmitted signal is composed of the raw measurement and an artificial-noise term. A special evaluation index named secrecy capacity is employed to assess the information security of signal transmissions under the developed encryption-decryption scheme. The purpose of the addressed problem is to design an encryption-decryption scheme and a state estimator such that: 1) the desired secrecy capacity is ensured; and 2) the required finite-horizon $l_{2}-l_{\infty}$ performance is achieved. Sufficient conditions are established on the existence of the encryption-decryption mechanism and the finite-horizon state estimator. Finally, simulation results are proposed to show the effectiveness of our proposed encryption-decryption-based state estimation scheme.

As one of the most induced genes in activated macrophages, immune-responsive gene 1(IRG1) encodes a mitochondrial metabolic enzyme catalysing the production of itaconic acid (ITA). Although ITA has an anti-inflammatory property, the underlying mechanisms are not fully understood. Here we show that ITA is a potent inhibitor of the TET-family DNA dioxygenases. ITA binds to the same site on TET2 as the co-substrate α-ketoglutarate, inhibiting TET2 catalytic activity. Lipopolysaccharide treatment, which induces Irg1 expression and ITA accumulation, inhibits Tet activity in macrophages. Transcriptome analysis reveals that TET2 is a major target of ITA in suppressing lipopolysaccharide-induced genes, including those regulated by the NF-κB and STAT signalling pathways. In vivo, ITA decreases the levels of 5-hydroxymethylcytosine, reduces lipopolysaccharide-induced acute pulmonary oedema as well as lung and liver injury, and protects mice against lethal endotoxaemia, depending on the catalytic activity of Tet2. Our study thus identifies ITA as an immune modulatory metabolite that selectively inhibits TET enzymes to dampen the inflammatory responses.

Herein, we describe pH-responsive Pickering emulsions stabilized by a sodium carboxylate-derived selenium surfactant (C10-Se-C10·(COONa)2) in combination with positively charged alumina nanoparticles. Unlike other bola-type carboxylate surfactants (e.g., disodium eicosanoate), C10-Se-C10·(COONa)2is soluble in water with a low Krafft temperature (36.1 °C). The emulsions are sensitive to pH variations, and efficient demulsification can be achieved by a pH trigger. The carboxylic sodium group in the C10-Se-C10·(COONa)2structure can be reversibly cycled between its anionic and nonionic states (carboxylic acid), resulting in a pH-controlled electrostatic attraction between the surfactant and alumina. The Pickering emulsion can be reversibly switched between “on” (stable) and “off” (unstable) states by pH at least four times. Compared with the emulsions stabilized by specially synthesized stimuli-responsive particles or surfactants, the method reported here is much easier to implement and requires very low concentrations of the surfactant and nanoparticles, with potential applications in the fields of biomedicine, drug delivery, and cosmetics.

This paper addresses the problem of consensus-based state estimation for interval type-2 Takagi–Sugeno (T–S) fuzzy time-delay systems over a wireless sensor network under deception attacks, partial information exchange and switching sensor-network topologies. The switching-topology-dependent estimators are constructed using interval type-2 fuzzy models considering the cases where the premise variables are available and unavailable. By means of the mode-dependent dwell time approach, sufficient conditions are established such that the estimation error system is exponentially and ultimately bounded. In addition, a fuzzy Lyapunov functional is utilized to derive the existence conditions of estimators for the case that the premise variable are unavailable. Two illustrative examples are provided to verify the effectiveness of the proposed method.

The studies on synthesis of organosilicons viaradical strategies since 2016 are reviewed, in which there are five main categories for the initiation of these radical silylations.

This article investigates the set stabilization of impulsive Boolean control networks (IBCNs) by sampled-data state feedback control based on a hybrid index model. It is worth mentioning that the 2-D index model has the ability to characterize the instantaneousness of ideal impulses and describe complicated impulsive behaviors. To avoid Zeno phenomenon, the judging conditions for forward completeness are derived. Subsequently, an algorithm is designed to obtain the largest sampled point control invariant set (SPCIS) of a given set in the hybrid domain, and its validity is further authenticated. Accordingly, a necessary and sufficient condition is derived for the set stabilization of IBCNs in the hybrid domain, and all time-optimal sampled-data state feedback controllers are designed. The similar results are also obtained for IBCNs in the time domain. Compared with set stabilization in the time domain, set stabilization in the hybrid domain not only focuses on the dynamics at each time instant but also concerns every jumping state. It results in that every SPCIS in the hybrid domain is a subset of a certain SPCIS in the time domain. Eventually, the $\lambda$ switch with impulsive disturbances is modeled as a reduced IBCN, which is presented to demonstrate the obtained results.

In this paper, the dissipative synchronization control problem for Markovian jump memristive neural networks (MNNs) is addressed with fully considering the time-varying delays and the fragility problem in the process of implementing the gain-scheduled controller. A Markov jump model is introduced to describe the stochastic changing among the connection of MNNs and it makes the networks under consideration suitable for some actual circumstances. By utilizing some improved integral inequalities and constructing a proper Lyapunov–Krasovskii functional, several delay-dependent synchronization criteria with less conservatism are established to ensure the dynamic error system is strictly stochastically dissipative. Based on these criteria, the procedure of designing the desired nonfragile gain-scheduled controller is established, which can well handle the fragility problem in the process of implementing the controller. Finally, an illustrated example is employed to explain that the developed method is efficient and available.

One of the fundamental problems in pinning control of complex networks is selecting appropriate pinning nodes, such that the whole system is controlled. This is particularly useful for complex networks with huge numbers of nodes. Recent research has yielded several pinning node selection strategies, which may be efficient. However, selecting a set of pinning nodes and identifying the nodes that should be selected first remain challenging problems. In this paper, we present a network control strategy based on left Perron vector. For directed networks where nodes have the same in- and out-degrees, there has so far been no effective pinning node selection strategy, but our method can find suitable nodes. Likewise, our method also performs well for undirected networks where the nodes have the same degree. In addition, we can derive the minimum set of pinning nodes and the order in which they should be selected for given coupling strengths. Our proofs of these results depend on the properties of non-negative matrices and M-matrices. Several examples show that this strategy can effectively select appropriate pinning nodes, and that it can achieve better results for both directed and undirected networks.

The effect of the α-glucosidase inhibitor acarbose on cardiovascular outcomes in patients with coronary heart disease and impaired glucose tolerance is unknown. We aimed to assess whether acarbose could reduce the frequency of cardiovascular events in Chinese patients with established coronary heart disease and impaired glucose tolerance, and whether the incidence of type 2 diabetes could be reduced.

Hyperglycemia is an independent risk factor for diabetic cardiomyopathy in humans; however, the underlying mechanisms have not been thoroughly elucidated. Zebrafish (Danio rerio) was used in this study as a novel vertebrate model to explore the signaling pathways of human adult cardiomyopathy. Hyperglycemia was induced by alternately immersing adult zebrafish in a glucose solution or water. The hyperglycemic fish gradually exhibited some hallmarks of cardiomyopathy such as myocardial hypertrophy and apoptosis, myofibril loss, fetal gene reactivation, and severe arrhythmia. Echocardiography of the glucose-treated fish demonstrated diastolic dysfunction at an early stage and systolic dysfunction at a later stage, consistent with what is observed in diabetic patients. Enlarged hearts with decreased myocardial density, accompanied by decompensated cardiac function, indicated that apoptosis was critical in the pathological process. Significant upregulation of the expression of Nkx2.5 and its downstream targets calreticulin (Calr) and p53 was noted in the glucose-treated fish. High-glucose stimulation in vitro evoked marked apoptosis of primary cardiomyocytes, which was rescued by the p53 inhibitor pifithrin-μ. In vitro experiments were performed using compound treatment and genetically via cell infection. Genetically, knockout of Nkx2.5 induced decreased expression of Nkx2.5, Calr and p53. Upregulation of Calr resulted in increased p53 expression, whereas the level of Nkx2.5 remained unchanged. An adult zebrafish model of hyperglycemia-induced cardiomyopathy was successfully established. Hyperglycemia-induced myocardial apoptosis was mediated, at least in part, by activation of the Nkx2.5–Calr–p53 pathway in vivo, resulting in cardiac dysfunction and hyperglycemia-induced cardiomyopathy.

Sepsis is a critical condition affecting patients worldwide. Systemic inflammatory response syndrome in sepsis contributes to organ dysfunction and mortality. The oXiris is a recently developed continuous renal replacement therapy (CRRT) hemofilter indicated for the adsorption of cytokines from the bloodstream. In our study, in a septic child, CRRT with three filters, including the oXiris hemofilter, resulted in a downregulation of inflammatory biomarkers and a reduction of vasopressors. Herein, we described the first report of such usage in septic children.

Porous media widely exists in natural aquifers, engineering materials (such as materials used to remove contaminants from water) and oil reservoirs, etc. Due to the complexity of particles contained in porous media, the fluid flow and contaminants transport are undoubtedly affected by the particle geometry of porous media. Two kinds of particle geometry models are developed to assess whether the geometry of grain plays an important role on chlorohydrocarbon contaminant transport and bioremediation. Porous medium properties such as tortuosity, permeability and entry pressure are quantified for the two kinds of particle geometries. Meanwhile, a laboratory experiment for perchloroethylene (PCE) transport is performed in a two-dimensional (2D) sandbox to verify permeability and entry pressure derived by different particle geometries. Comparison between geometry models and experimental results indicate rectangular particles (RP) with high μ(the ratio of width to length) and ellipse particles (EP) with low η(the ratio of semi-long axis to semi-shorter axis) agree well with the experiment. Moreover, the grains geometry that forms the porous matrix's solid domain applied in the experiment is also identified according to the numerical simulation of PCE migration. Furthermore, two kinds of particle geometries are coupled with UTCHEM, to derive the effects of particle geometry on Trichloroethylene (TCE) transport, redistribution and biodegradation by methanotrophs for a realistic three-dimensional (3D) aquifer application. Results suggest the geometry of grain has a significant influence on the properties of a porous medium. The remediation efficiency became higher when μincreased for RP and ηdecreased for EP. PCE infiltration rate was lowest for RP with high μand EP with low η. Simulation results based on realistic groundwater bioremediation indicated RP with μ = 0.9, EP with η = 1.1 and EP with η = 1.3 achieved the highest bioremediation efficiency for TCE contamination.

To investigate the effect of microplastics on the transport and retention of antibiotics in subsurface environment, polypropylene (PP) and ciprofloxacin (CIP) are selected as typical microplastic and antibiotic contaminant, respectively. The key factors and main control mechanisms are systematically investigated using a combination of adsorption experiments, column experiments and numerical model. The adsorption experiments indicate the largest adsorption capacity of CIP on PP is 1.03mg·g-1. Simultaneously, the results of column experiments and numerical model suggest that PP can significantly affect the migration behavior and retention of CIP in porous media. CIP mobility is positively correlated to flow velocity, initial concentration of CIP and ionic strength (Na+, Ca2+and Ba2+). Moreover, compared to monovalent cation (Na+), divalent cations (Ca2+, Ba2+) have a stronger enhancement effect on CIP mobility and a stronger inhibition effect on CIP retention in saturated porous media. The transport of CIP in saturated porous media containing PP is simulated by a single-point kinetic model, and the equations of the transport kinetic parameters of CIP are obtained through regression analysis. The research could help to gain insight into understanding the environmental behavior of antibiotic in the groundwater system, and provide scientific basis for the accurate prediction and assessment of environmental risk caused by microplastic and antibiotic in the groundwater system.

Pd-based nanomaterials have been considered as an effective catalyst for formic acid electrooxidation reaction (FAOR). Herein, we reported two types of polyaniline (PANI)-promoted Pd catalysts. One was an nPANI/Pd electrocatalyst prepared by the electropolymerization of aniline and the electrodeposition of Pd. The other was a Pd/C/nPANI catalyst prepared by the direct electropolymerization of aniline on a commercial Pd/C catalyst. The results show that PANI alone has no catalytic activity for FAOR; however, PANI can exhibit a significant promoting effect to Pd. The current densities of FAOR on the Pd catalysts with a PANI coating show a significant increase compared with that of the Pd reference catalyst without PANI as a promoter. The promoting effects of PANI are strongly dependent on the electropolymerization potential cycles (n). The highest catalytic activities for FAOR of all the nPANI/Pd and Pd/C/nPANI catalysts were those of 15PANI/Pd and Pd/C/20PANI. The mass-specific activity (MSA) of Pd in 15PANI/Pd was 7.5 times that of the Pd catalyst, and the MSA and intrinsic activity of Pd/C/20PANI were 2.3 and 3.3 times that of the Pd/C catalyst, respectively. The enhanced performance of Pd catalysts is proposed as an electronic effect between Pd nanoparticles and PANI.

Cardiosphere‐derived cells (CDCs) effect therapeutic regeneration after myocardial infarction (MI) both in animal models and in humans. Here, we test the hypothesis that cell‐cell contact plays a role in mediating the observed therapeutic benefits of CDCs, above and beyond conventional paracrine effects. Human CDCs or vehicle were injected into immunodeficient (SCID) mouse hearts during acute MI. CDC transplantation augmented the proportion of cycling (Ki67+) cardiomyocytes and improved ventricular function. CDC‐conditioned media only modestly augmented the percentage of Ki67+cardiomyocytes (>control but

Our aim was to examine whether the combined use of apolipoprotein B (apoB)apolipoprotein A1 (apoA1) and non-high-density lipoprotein cholesterol (non-HDL-C) was useful before routine clinical lipid measurement in predicting coronary heart disease (CHD).

Aim:Accumulating evidence suggests that endoplasmic reticulum (ER) stress plays a fundamental role in the initiation and development of atherosclerosis. Atorvastatin is known to exert pleiotropic effects on cardiovascular system. This study was designed to examine the effect of atorvastatin on homocysteine (Hcy)‐induced activation of ER stress and the potential mechanisms regarding AMP‐activated protein kinase (AMPK). Methods and results:Apolipoprotein E‐deficient (apoE−/–) mice were administrated with methionine or atorvastatin and sacrificed 2 months later for plasma tests and immunohistochemical analysis. To further study the mechanisms, human umbilical vein endothelial cells (HUVECs) were incubated with various concentrations of Hcy for 1 h, or 500 μmol/L Hcy for 1–24 h. Furthermore, we challenged HUVECs with Hcy in the presence or absence of atorvastatin, 5‐amino‐4‐imidazolecarboxamide riboside‐l‐beta‐D‐ribofuranoside (AICAR), an AMPK agonist, and AMPK‐DN that expressed a dominant‐negative mutant of AMPK. Expression levels of ER stress markers were measured by real‐time PCR and Western blot analysis. Our data revealed that atorvastatin prevented Hcy‐induced ER stress in the aortic roots of hyperhomocysteinemic mice. In vitrostudy showed atorvastatin suppressed Hcy‐induced ER stress in HUVECs as well. AICAR is found to have the same effect as that of atorvastatin, which could be antagonized by AMPK‐DN. Conclusions:Atorvastatin inhibits Hcy‐induced ER stress both in vitroand in vivo. The protective effect of atorvastatin against Hcy‐induced vascular injury is mediated by AMPK activation.

This paper discusses asymptotic stability and stabilization for a class of nonlinear descriptor systems with delay. The nonlinearity of the system is a continuous function of the time and system state, and the Jacobi matrix of the function is norm‐bounded. A sufficient condition for the existence and uniqueness of the solution to the descriptor system is proposed by a linear matrix inequality (LMI) approach. Under the condition, using nonlinear methods, the asymptotic stability for the system is obtained. In addition, to stabilize the descriptor system, a parameterized representation of the state feedback controller is given in terms of a solution to an LMI. Finally, the effectiveness of the approach is illustrated by numerical examples.

In this paper, the issue of observer designs for a class of nonlinear continuous‐time systems with time‐delay is addressed, where the nonlinear function is not necessarily Lipschitz. It is shown that both full‐order and reduced‐order observers can be obtained by means of the same linear matrix inequality. A numerical example is presented to show the effectiveness of the proposed approach. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

Network‐based robust control of stochastic systems with nonlinear perturbations is investigated in this paper. State and static output feedback controllers are designed, respectively, for stochastic networked control systems subject to the presence of network‐induced delay, transmitted data dropout and nonlinear perturbations. Using the Lyapunov‐Krasovskii functional and descriptor system approach, a state feedback controller and a static output feedback controller are constructed in terms of linear matrix inequalities, respectively. With the controllers, the corresponding closed‐loop systems are stochastically ultimately bounded in the mean square. Two examples are provided to demonstrate the effectiveness of the proposed methods. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

Abstract: This paper deals with the observer design problem for a class of descriptor Markovian jumping systems with nonlinear perturbations. The problem addressed is to design full-order and reduced-order observers, respectively, such that the dynamics of each estimation error is guaranteed to be globally exponentially stable in the mean square. Sufficient conditions for the existence of both full-order and reduced-order observers are given, which are equivalent to a set of linear matrix inequalities. An example is presented to illustrate the effectiveness of the proposed method.

This paper discusses a generalized quadratic stabilization problem for a class of discrete‐time singular systems with time‐delay and nonlinear perturbation (DSSDP), which the satisfies Lipschitz condition. By means of the S‐procedure approach, necessary and sufficient conditions are presented via a matrix inequality such that the control system is generalized quadratically stabilizable. An explicit expression of the static state feedback controllers is obtained via some free choices of parameters. It is shown in this paper that generalized quadratic stability also implies exponential stability for linear discrete‐time singular systems or more generally, DSSDP. In addition, this new approach for discrete singular systems (DSS) is developed in order to cast the problem as a convex optimization involving linear matrix inequalities (LMIs), such that the controller can stabilize the overall system. This approach provides generalized quadratic stabilization for uncertain DSS and also extends the existing robust stabilization results for non‐singular discrete systems with perturbation. The approach is illustrated here by means of numerical examples.

This paper considers the globally asymptotic stabilization problem of multi‐input multi‐output bilinear systems with undamped natural response. Under the conditions for asymptotic stabilization by static state feedback control and system detectability, two output dynamic feedback controllers with saturation bounded control are constructed. The global asymptotic stability of the closed‐loop system is verified by Lyapunov stability theory and LaSalle's Lemma. An example is given to demonstrate the obtained results.

The H∞almost disturbance decoupling problem is considered. In this paper, a nonlinear design is proposed to find a state feedback controller for bilinear systems. The closed‐loop system is internally stable and achieves disturbance attenuation in nonlinear H∞sense. We defined a special form of Lyapunov function, which is constructed in terms of one or a set of positive definite constant matrices. If, except of the origin of system, the corresponding polynomial of the positive definite matrix (or several polynomials relevant to the positive definite constant matrices) has (have) no zero on a given subset of state space, then we can construct a controller to solve our problem. It is found that the controller structure could be complicated, but is feasible in computation and may require optimization technique to search the solution. We consider both SIMO and MIMO cases with illustrated examples.

An H∞-γ-suboptimal strongly robust performance problem (H∞-γ-SSRPP), for a class of linear systems with multiple time delays and parameter uncertainties is considered in this paper. A set of necessary and sufficient conditions for the existence of control laws that achieve the above mentioned strongly robust performance is derived and characterized in terms of the solutions of three well-defined linear matrix inequalities (LMIs). An explicit parameterization of these laws is also provided.

Objective: To investigate the effect and safety of ketogenic diet (KD) for the treatment of paediatric patients with super-refractory status epilepticus (SRSE) in febrile infection-related epilepsy syndrome (FIRES). Method: From January 1, 2015 to October 31, 2017, ten critically ill paediatric patients with SRSE in FIRES were included in this study and treated with KD. The treatment effects of KD were evaluated by using continuous encephalography (CEEG) and amplitude-integrated electro-encephalography (aEEG). Results: All 10 patients fulfilled the diagnostic criteria of SRSE in FIRES and achieved ketosis within 24–72 h following the administration of KD. CEEG and aEEG were monitored for several weeks to assess the efficacy of KD on status epilepticus (SE). SE was contained in 8 patients within 2 to 19 days after initiation of KD, and KD was discontinued in the other 2 patients. One of the 10 patients demonstrated severe adverse effects. Conclusion: KD may be an alternative and safe treatment option in critical paediatric patients with SRSE in FIRES.

The synchronization control problem for a class of switched complex networks with additive time-varying delays is studied.Firstly,the switched complex network drive-response system for system node parameter switching is studied.The appropriate Lyapunov function is constructed under the influence of additive time delay.According to Lyapunov stability theory and inequality technique,the sufficient conditions for mean-square exponential synchronization of the system are obtained.And these conclusions are expressed by linear matrix inequality (LMI).Secondly,the matrix inequality is solved by using LMI toolbox to synchronize the master-slave system.Finally,a numerical example is given to verify the effectiveness of the proposed method.