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A rapid and sensitive method for the determination of sulfonamide (SA) residues in fish was developed using electro-enhanced solid-phase microextraction (EE-SPME) based on nitrogen-doped three-dimensional graphene foam (NGF) functionalized monolithic column (monolith@NGF, M@NGF) combined with high performance liquid chromatography (HPLC). To improve the enrichment efficiency of SA residues in fish, porous M@NGF was prepared on the surface of stainless-steel wires by in situ polymerization using ionic liquids as the functional monomer and NGF as the conductivity enhancer. The EE-SPME method was applied for the extraction of sulfathiazole (ST), sulfamethazine (SM2), and sulfadimethoxypyrimidine (SMM) from fish. Adsorption time, agitation speed, adsorption voltage, ionic strength, the pH of sample solution, desorption time, desorption voltage, and the composition of desorption solution were optimized. The results showed that the M@NGF-based EE-SPME method enriched ST, SM2 and SMM by 74, 58 and 64 folds, respectively, and shortened the adsorption equilibrium time to 35 min. In the linear range of 5–5 000 μg/kg, the limits of detection (LODs) of this method were 1.78, 3.16 and 1.84 μg/kg for ST, SM2 and SMM, respectively, and the limits of quantification (LOQs) were 5 μg/kg for all analytes. Coefficients of determination (R2) for linear regression analysis of this method were all greater than 0.999 0, and the recoveries from spiked samples ranged from 79.2% to 110.1%, with relative standard deviations (RSDs) ranging from 1.4% to 9.8% (n = 5). This method solved the problems of low extraction efficiency and serious matrix interference of SA residues in fish, and allowed the rapid, sensitive detection of SA residues in fish.

Although previous studies have shown that repetitive transcranial magnetic stimulation (rTMS) can ameliorate addictive behaviors and cravings, the underlying neural mechanisms remain unclear. This study aimed to investigate the effect of high‐frequency rTMS with the left dorsolateral prefrontal cortex (L‐DLPFC) as a target region on smoking addiction in nicotine‐dependent individuals by detecting the change of spontaneous brain activity in the reward circuitry. We recruited 17 nicotine‐dependence participants, who completed 10 sessions of 10 Hz rTMS over a 2‐week period and underwent evaluation of several dependence‐related scales, and resting‐state fMRI scan before and after the treatment. Functional connectivity (FC) analysis was conducted with reward‐related brain regions as seeds, including ventral tegmental area, bilateral nucleus accumbens (NAc), bilateral DLPFC, and bilateral amygdala. We found that, after the treatment, individuals showed reduced nicotine dependence, alleviated tobacco withdrawal symptoms, and diminished smoking cravings. The right NAc showed increased FC with right fusiform gyrus, inferior temporal gyrus (ITG), calcarine fissure and surrounding cortex, superior occipital gyrus (SOG), lingual gyrus, and bilateral cuneus. No significant FC changes were observed in other seed regions. Moreover, the changes in FC between the right NAc and the right ITG as well as SOG before and after rTMS were negatively correlated with changes in smoking scale scores. Our findings suggest that high‐frequency L‐DLPFC‐rTMS reduces nicotine dependence and improves tobacco withdrawal symptoms, and the dysfunctional connectivity in reward circuitry may be the underlying neural mechanism for nicotine addiction and its therapeutic target. [ABSTRACT FROM AUTHOR]

Summary Considering the existence of time delay and interval uncertainty, a set‐membership state estimation problem based on zonotopes is studied for discrete‐time switched systems subject to unknown but bounded noises. To conform the actual situation, a state observer asynchronous with the subsystem is designed. The L∞$$ {L}_{\infty } $$ performance is introduced to attenuate the effect of noises in the observer design. By dealing with the interval uncertainty, the design approach of L∞$$ {L}_{\infty } $$ observer is given and transformed into a convex optimization problem which can be solved off‐line. The zonotope and the estimation interval containing state are provided based on the L∞$$ {L}_{\infty } $$ observer. Finally, a numerical example is given to verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This article studies the zonotopic set-membership state estimation problem for linear time-varying complex networks with unknown-but-bounded (UBB) noises, where the UBB noises are contained by a set of zonotopes. The objective of the addressed problem is to give two design methods, namely the correction matrix method and the state observer method, where a time-varying zonotopic sequence containing all possible states of the system is obtained. The expressions of the correction matrix and the observer gain are given under the F-radius criterion, and the desired minimum zonotopes are obtained. In addition, a state observer based on the measured output at the current moment is designed to analyze the equivalence between the above two methods. Finally, in order to demonstrate the effectiveness of the proposed state estimation algorithms, two simulation examples are presented. [ABSTRACT FROM AUTHOR]

In this article, the disturbance observer‐based proportional–integral–derivative (PID) control protocol is investigated for synchronization of complex networks with probabilistic interval time‐varying delays and multiple disturbances. For the sake of reducing conservatism, a method of probabilistic interval time‐varying delay is proposed by introducing two certain intervals with known probability distributions. Moreover, two different disturbances are taken into account. One of the disturbances is produced by an exogenous system which acts through the input channel, while the other is usual norm‐bounded disturbance. Simultaneously, a disturbance observer is designed to estimate and compensate the disturbance generated by the exogenous system. By constructing an appropriate Lyapunov–Krasovskii function, a sufficient criterion is obtained to ensure both the exponential synchronization and prescribed H∞$$ {H}_{\infty } $$ performance index. Finally, the simulation examples are employed to demonstrate the validity of the theoretical results. [ABSTRACT FROM AUTHOR]

This study is intended to discuss the noise-to-state stability (NSS) and the delay-dependent stability (DDS) of the highly nonlinear hybrid stochastic differential equation (HNHSDE) with multiple delays. Distinct from the white noise considered in the existing literature, we introduce the coloured noise characterised by a finite second-order process into the HNHSDE. Under some mild assumption conditions, we demonstrate that the HNHSDE exists a unique global solution (GS). Moreover, some criteria regarding the NSS in the qth moment of the GS are established. Furthermore, several theorems are provided for guaranteeing the pth moment asymptotic stability and the almost surely asymptotic stability of the GS with the aid of the delay-dependent Lyapunov functional and stochastic analysis theory. At last, two illustrative examples are given to show the feasibility of our developed theory findings. [ABSTRACT FROM AUTHOR]

This paper is concerned with the nonfragile predictive control problem for the networked control system (NCS) with input delay and network-induced time delays (NITDs). First, the transmission strategy governed by redundant channels is introduced to reduce the occurrence of data packet dropout between the sensor and the observer. Moreover, the event-triggered mechanism (ETM) is employed to save the network resources, where the maximum triggered interval is given. Subsequently, a nonfragile networked predictive control scheme (NPCS) is designed to address the input delay and the NITDs. Accordingly, the sufficient criterion ensuring mean-square exponential stability (MSES) is derived by employing the Lyapunov–Krasovskii stability theorem. Both the observer gain matrix (OGM) and the controller gain matrix (CGM) are gained through solving the nonlinear minimization problem with convex constraints. Finally, a simulation example is utilized to demonstrate the usefulness of the proposed main results. [ABSTRACT FROM AUTHOR]

Summary: This article investigates the dissipative fault detection (FD) problem for time‐delay nonlinear Markov jump systems with measurement outliers in the case of partially unknown transition probabilities. The stochastic communication protocol is utilized to save network bandwidth, where the scheduling model is described via a Markov chain. An outlier‐resistant FD filter is constructed with the help of adaptive saturation function technology. The sufficient conditions are derived to ensure that the FD system satisfies the stochastic stability and stochastic strict dissipativity. In addition, an FD filter without saturation constraint is also designed to compare with the outlier‐resistant FD filter, which verifies that the outlier‐resistant FD filter weakens the influence of measurement outliers effectively. Finally, two examples are provided to demonstrate the feasibility and effectiveness of the designed FD scheme. [ABSTRACT FROM AUTHOR]

Under the influence of sensor saturation and packet dropout, this paper is concerned with the fault detection (FD) problem for a class of nonlinear systems with two additive time‐varying delay components. In the addressed measurement model, the sensor is assumed to have two communication channels, which can contribute to improving the probability of successfully delivering the measurements. A FD filter is designed to generate residual signals, and the sufficient criteria are established to ensure the stochastic finite‐time stability (SFTS) of the residual system with H∞$$ {H}_{\infty } $$ performance constraint by constructing new Lyapunov‐Krasovskii functionals. Based on the established criteria, the explicit expression of the desired FD filter is obtained via solving a set of linear matrix inequalities (LMIs). Finally, the usefulness of the proposed FD scheme is verified by a simulation example. [ABSTRACT FROM AUTHOR]