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This paper proposes a Takagi-Sugeno (T-S) fuzzy controller for an underactuated unmanned surface vehicle (USV) based on an event-triggered scheme (ETS) in a network environment. Firstly, a discrete-time event-triggered scheme is introduced to enhance the network resource utilization while counteracting the impact of communication delays on the performance of USV control system. Meanwhile, based on the ETS, the acting frequency of the actuators can be cut down, extending its service life. Then, an event-based T-S fuzzy controller is established. A criteria on global stability analysis and the event-triggering controller are derived by utilizing the Lyapunov functional approach. It expresses in terms of linear matrix inequalities (LMIs). Finally, the effectiveness of our proposed method is verified by numerical simulation. It is demonstrated that the presented main results not only can guarantee the performance, but also reduce the occupation of network bandwidth and the acting frequency of the actuators. [ABSTRACT FROM AUTHOR]

In this paper, we consider the finite-time consensus problem for second-order multi-agent systems with pinning control. Unlike the existing finite-time consensus algorithms for second-order multi-agent systems in which all agents' velocities and positions are assumed to have common communication weights and nonlinear couplings, we allow communication weights, nonlinear couplings and the feedback gains to be inconsistent for each agent's velocity and position. A flexible continuous protocol is designed to solve the finite-time consensus problem. Based on the Lyapunov functional approach and finite-time stability analysis, it is proved that this model not only achieves finite-time consensus for every agent but also estimates the settling time depending on initial data without assuming that α 2 =2α 1 1+α 1 . Moreover, some simulation examples are given to verify the effectiveness of the theoretical results., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 International Society of Automation. Published by Elsevier Ltd. All rights reserved.)

To discover novel natural product-based insecticides, a series of (+)-nootkatone-based amine derivatives 3a-t were prepared and evaluated for their insecticidal activities against Mythimna separata Walker, Myzus persicae Sulzer, and Plutella xylostella Linnaeus. Insecticidal assays showed that most of the title (+)-nootkatone derivatives exhibited stronger insecticidal activities against three insect pests than the precursor (+)-nootkatone after the introduction of amine groups on the parent (+)-nootkatone. Compounds 3a , 3d , 3h , 3m , 3n , 3p , and 3r displayed more promising growth inhibitory (GI) effect against M. separata than the commercially available botanical insecticide toosendanin. Compound 3o exhibited the most potent aphicidal activity with an LD 50 value of 0.011 μg/larvae, which was 2.09-fold higher than the positive control rotenone. Additionally, compounds 3g and 3n showed more promising larvicidal activity against P. xylostella with LC 50 values of 260 and 230 mg/L, respectively, superior to that of rotenone (460 mg/L). Moreover, derivatives 3g and 3n exhibited better control efficacy toward P. xylostella than rotenone under greenhouse conditions. Preliminary mechanistic studies revealed that derivative 3n could inhibit the activity of glutathione S -transferase (GST) in P. xylostella and thus exerted larvicidal activity, and molecular docking further demonstrated that 3n could interact well with some amino acid residues of GST. Finally, the toxicity assay suggested that derivatives 3g and 3n were relatively less toxic to nontarget organisms. These findings will provide insights into the development of (+)-nootkatone derivatives as green pesticides.

Social bot detection is essential for maintaining the safety and integrity of online social networks (OSNs). Graph neural networks (GNNs) have emerged as a promising solution. Mainstream GNN-based social bot detection methods learn rich user representations by recursively performing message passing along user-user interaction edges, where users are treated as nodes and their relationships as edges. However, these methods face challenges when detecting advanced bots interacting with genuine accounts. Interaction with real accounts results in the graph structure containing camouflaged and unreliable edges. These unreliable edges interfere with the differentiation between bot and human representations, and the iterative graph encoding process amplifies this unreliability. In this article, we propose a social Bot detection method based on Edge Confidence Evaluation (BECE). Our model incorporates an edge confidence evaluation module that assesses the reliability of the edges and identifies the unreliable edges. Specifically, we design features for edges based on the representation of user nodes and introduce parameterized Gaussian distributions to map the edge embeddings into a latent semantic space. We optimize these embeddings by minimizing Kullback-Leibler (KL) divergence from the standard distribution and evaluate their confidence based on edge representation. Experimental results on three real-world datasets demonstrate that BECE is effective and superior in social bot detection. Additionally, experimental results on six widely used GNN architectures demonstrate that our proposed edge confidence evaluation module can be used as a plug-in to improve detection performance.

In this article, the stochastic analysis and H ∞ controller design problems of networked systems with packet dropouts and false data injection attacks are investigated. Different from the existing literature, we focus on the linear networked systems with external disturbances and both sensor-controller channel and controller-actuator channel are studied. First, we present a discrete-time modeling framework that leads to a stochastic closed-loop system with randomly varying parameters. To facilitate the analysis and H ∞ control of resulting discrete-time stochastic closed-loop system, an equivalent yet analyzable stochastic augmented model is further constructed by matrix exponential computation. Based on this model, a stability condition is derived in the form of linear matrix inequality (LMI) with the aid of a reduced-order confluent Vandermonde matrix, Kronecker product operation, and law of total expectation. Specifically, the dimension of the LMI obtained in this article does not increase as the upper bound of consecutive packet dropouts does, which is also different from the existing literature. Subsequently, a desired H ∞ controller is obtained such that the original discrete-time stochastic closed-loop system is exponentially mean-square stable with a prescribed H ∞ performance. Finally, a numerical example and a direct current motor system are exploited to substantiate the effectiveness and practicability of the designed strategy.

Automatic rumor detection is critical for maintaining a healthy social media environment. The mainstream methods generally learn rich features from information cascades by modeling the cascade as a tree or graph structure where edges are built based on interactions between a tweet and retweets. Some psychology studies have empirically shown that users' various subjective factors always cause the uncertainty of interactions such as differences among interactive behavior activation thresholds or semantic relevancy. However, previous works model interactions by employing a simple fully connected layer on fixed edge weights in the graph and cannot reasonably describe this inherent uncertainty of complex interactions. In this article, inspired by the fuzzy theory, we propose a novel neuro-fuzzy method, fuzzy graph convolutional networks (FGCNs), to sufficiently understand uncertain interactions in the information cascade in a fuzzy perspective. Specifically, a new strategy of graph construction is first designed to convert each information cascade into a heterogeneous graph structure with the consideration of explicit interactive behaviors between a tweet and its retweet, as well as implicit interactive behaviors among retweets, enriching more structural clues in the graph. Then, we improve graph convolutional networks by incorporating edge fuzzification (EF) modules. The EFs adapt edge weights according to predefined membership to enhance message passing in the graph. The proposed model can provide a stronger relational inductive bias for expressing uncertain interactions and capture more discriminative and robust structural features for rumor detection. Extensive experiments demonstrate the effectiveness and superiority of FGCN on both rumor detection and early rumor detection.

This paper studies the resilient current controller design for the networked DC microgrid system with multiple constant power loads (CPLs) under a new type of time-constrained denial-of-service (DoS) attack. Different from the existing DoS attack models, which are often characterized by DoS frequency and DoS duration, this paper only considers the duration characteristics of the sporadic/aperiodic DoS attacks, and proposes a new type of time-constrained DoS attack model. Under the effects of such DoS attacks, a switching state feedback control law is constructed and a switching-like DC microgrid system model is then established. Furthermore, based on an attack-parameter-dependent time-varying Lyapunov function (TVLF) method, the exponential stability criterion of the resulting DC microgrid system under aperiodic DoS attacks is derived, and a new resilient controller design method is proposed. Finally, simulation studies are given to verify the effectiveness and merits of the proposed resilient control design scheme on achieving the desired control performance and attack resilience., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 ISA. Published by Elsevier Ltd. All rights reserved.)

This article is concerned with the problem of observer-based dynamic event-triggered control for a networked control system (NCS) under a class of power-constrained denial-of-service (DoS) attacks that aim at impeding the network communication from time to time. First, by carefully modeling such DoS attacks as aperiodic pulse-width-modulated (PWM) jamming signals, a switching observer, adapting to the DoS attacks, is delicately constructed to deal with the unavailability of full-state information. Second, to economize the limited bandwidth resources, a dynamic event-triggered communication scheme is designed under the aperiodic DoS jamming attacks, whose duration and frequency are assumed to be restricted. Third, a switching system model with artificial state delay is formulated, which characterizes the effects of the aperiodic DoS attacks and event-triggered communication scheme in a unified framework. Then, the asymptotic stability analysis and controller/observer synthesis conditions of the resulting switching system are obtained by using a piecewise Lyapunov-Krasovskii functional approach. Furthermore, a co-design method of the dynamic triggering parameters, controller, and observer gains is presented. Finally, an example is employed to verify the effectiveness of the obtained results.

This paper is concerned with the observer-based event-triggered control for a continuous networked linear system subject to denial-of-service (DoS) attacks, where the attacks are launched periodically to block the data transmission in control channels. First, a new observer state-based resilient event-triggering scheme is developed in the presence of DoS attacks. Second, a novel event-based switched system model is established by considering the effect of the event-triggering scheme and DoS attacks simultaneously. By virtue of this new model combined with a piecewise Lyapunov-Krasovskii functional method, the sufficient conditions are derived to guarantee exponential stability of the resulting switched system. It is shown that the proposed results can establish a quantitative relationship among the launching/sleeping periods of the attacks, the event-triggering parameters, the sampling period, and the exponential decay rate. Third, criteria for designing a desired observer-based event-triggered controller are provided and expressed in terms of a set of linear matrix inequalities. Finally, an offshore structure model is presented to illustrate the efficiency of the developed control method.

In this paper, the event-based controller synthesis problem for networked control systems under the resilient event-triggering communication scheme (RETCS) and periodic denial-of-service (DoS) jamming attacks is studied. First, a new periodic RETCS is designed under the assumption that the DoS attacks imposed by power-constrained pulsewidth-modulated jammers are partially identified, that is, the period of the jammer and a uniform lower bound on the jammer's sleeping periods are known. Second, a new state error-dependent switched system model is constructed, including the impacts of the RETCS and DoS attacks. According to this new model, the exponential stability criteria are derived by using the piecewise Lyapunov functional. In these criteria, the relationship among DoS parameters, the triggering parameters, the sampling period, and the decay rate is quantitatively characterized. Then, a criterion is also proposed to obtain the explicit expressions of the triggering parameter and event-based state feedback controller gain simultaneously. Finally, the obtained theoretical results are verified by a satellite yaw-angles control system.

In this study, we established two doubled haploid (DH) libraries with a total of 207 DH lines. We applied BR and GA inhibitors to all DH lines at seedling stage and measured seedling BR and GA inhibitor responses. Moreover, we evaluated field traits for each DH line (untreated). We conducted genome-wide association studies (GWAS) with 62,049 genome wide SNPs to explore the genetic control of seedling traits by BR and GA. In addition, we correlate seedling stage hormone inhibitor response with field traits. Large variation for BR and GA inhibitor response and field traits was observed across these DH lines. Seedling stage BR and GA inhibitor response was significantly correlate with yield and flowering time. Using three different GWAS approaches to balance false positive/negatives, multiple SNPs were discovered to be significantly associated with BR/GA inhibitor responses with some localized within gene models. SNPs from gene model GRMZM2G013391 were associated with GA inhibitor response across all three GWAS models. This gene is expressed in roots and shoots and was shown to regulate GA signaling. These results show that BRs and GAs have a great impact for controlling seedling growth. Gene models from GWAS results could be targets for seeding traits improvement., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Breeders have been successful in increasing crop performance by exploiting genetic diversity over time. However, the reported annual yield increases are not sufficient in view of rapid human population growth and global environmental changes. Exotic germplasm possesses high levels of genetic diversity for valuable traits. However, only a small fraction of naturally occurring genetic diversity is utilized. Moreover, the yield gap between elite and exotic germplasm widens, which increases the effort needed to use exotic germplasm and to identify beneficial alleles and for their introgression. The advent of high-throughput genotyping and phenotyping technologies together with emerging biotechnologies provide new opportunities to explore exotic genetic variation. This review will summarize potential challenges for utilization of exotic germplasm and provide solutions., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Unraveling the function of genes affecting agronomic traits is accelerating due to progress in DNA sequencing and other high-throughput genomic approaches. Characterized genes can be exploited by plant breeders by using either marker-aided selection (MAS) or transgenic procedures. Here, we propose a third 'outlet', 'molecular strengthening' (MOST), as alternative option for exploiting detailed molecular understanding of trait expression, which is comparable to the pharmaceutical treatment of human diseases. MOST treatments can be used to enhance yield stability. Alternatively, they can be used to control traits temporally, such as flowering time to facilitate crosses for plant breeders. We also discuss the essence for developing MOST treatments, their prospects, and limitations., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

This paper is concerned with the control design problem of event-triggered networked systems with both state and control input quantizations. Firstly, an innovative delay system model is proposed that describes the network conditions, state and control input quantizations, and event-triggering mechanism in a unified framework. Secondly, based on this model, the criteria for the asymptotical stability analysis and control synthesis of event-triggered networked control systems are established in terms of linear matrix inequalities (LMIs). Simulation results are given to illustrate the effectiveness of the proposed method., (Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.)