Adaptive Fuzzy Event-Triggered Cooperative Control for Multi-Robot Systems: A Predefined-Time Strategy.

A predefined-time adaptive fuzzy cooperative controller with event triggering is proposed for multi-robot systems that takes into account external disturbances, input saturation, and model uncertainties in this paper. First, based on the asymmetric tan-type barrier Lyapunov function, a predefined-time controller is proposed to acquire a quick response and more precise convergence time under the directed communication topology. Second, predefined-time fuzzy logic systems are developed to approximate external disturbances and model uncertainties. Third, a dynamic relative threshold event-triggered mechanism is improved to save the communication resources of the robots. Subsequently, the proof procedure for the predefined-time stability is given using the Lyapunov stability theorem. Finally, some simulation examples, including a comparative experi-ment on multi-robot systems, are provided to test the effectiveness of the above algorithm.

Event-Triggered Finite-Time Formation Control of Underactuated Multiple ASVs with Prescribed Performance and Collision Avoidance.

In this paper, an event-triggered finite-time controller is proposed for solving the formation control problems of underactuated multiple autonomous surface vessels (ASVs), including asymmetric mass matrix, collision avoidance, maintaining communication distances and prescribed performance. First, to not only avoid collisions between the follower and leader but also maintain an effective communication distance, a desired tracking distance is designed to be maintained. Second, an improved barrier Lyapunov function (BLF) is proposed to implement the tracking error constraint. In addition, the relative threshold event-triggering strategy effectively solves the communication pressure problem and greatly saves communication resources. Finally, based on coordinate transformation, line of sight (LOS) and dynamic surface control (DSC), a comprehensive finite-time formation control method is proposed to avoid collisions and maintain communication distance. All the signals of the proposed control system can be stabilized in finite time (PFS). The numerical simulation results verify the effectiveness of the proposed control system.

Robust Fixed-Time H∞ Trajectory Tracking Control for Marine Surface Vessels Based on a Self-Structuring Neural Network.

In this study, a robust fixed-time H∞ trajectory tracking controller for marine surface vessels (MSVs) is proposed based on self-structuring neural network (SSNN). First, a fixed-time H∞ Lyapunov stability theorem is proposed to guarantee that the MSV closed-loop system is fixed-time stable (FTS) and the L 2 gain is less than or equal to γ. This shows high accuracy and strong robustness to the approximation errors. Second, the SSNN is designed to compensate for the model uncertainties of the MSV system, marine environment disturbances, and lumped disturbances term constituted by the actuator faults (AFs). The SSNN can adjust the network structure in real time through elimination rules and split rules. This reduces the computational burden while ensuring the control performance. It is proven by Lyapunov stability that all signals in the MSV system are stable and bounded within a predetermined time. Finally, theoretical analysis and numerical simulation verify the feasibility and effectiveness of the control scheme.

Connectome-based model predicts individual psychopathic traits in college students.

BACKGROUND: Psychopathic traits have been suggested to increase the risk of violations of socio-moral norms. Previous studies revealed that abnormal neural signatures are associated with elevated psychopathic traits; however, whether the intrinsic network architecture can predict psychopathic traits at the individual level remains unclear. METHODS: The present study utilized connectome-based predictive modeling (CPM) to investigate whether whole-brain resting-state functional connectivity (RSFC) can predict psychopathic traits in the general population. Resting-state fMRI data were collected from 84 college students with varying psychopathic traits measured by the Levenson Self-Report Psychopathy Scale (LSRP). RESULTS: Functional connections that were negatively correlated with psychopathic traits predicted individual differences in total LSRP and secondary psychopathy score but not primary score. Particularly, nodes with the most connections in the predictive connectome anchored in the prefrontal cortex (e.g., anterior prefrontal cortex and orbitofrontal cortex) and limbic system (e.g., anterior cingulate cortex and insula). In addition, the connections between the occipital network (OCCN) and cingulo-opercular network (CON) served as a significant predictive connectome for total LSRP and secondary psychopathy score. CONCLUSION: CPM constituted by whole-brain RSFC significantly predicted psychopathic traits individually in the general population. The brain areas including the prefrontal cortex and limbic system and large-scale networks including the CON and OCCN play special roles in the predictive model-possibly reflecting atypical cognitive control and affective processing for individuals with elevated psychopathic traits. These findings may facilitate detection and potential intervention of individuals with maladaptive psychopathic tendency.

High levels of psychopathic traits increase the risk of transferring reactive aggression to innocent people after provocation: Evidence from an ERP study.

This study investigated the neuropsychological underpinnings of reactive aggression toward innocent people in a student population with different levels of psychopathic traits. While recording event-related potentials, participants (divided into high/low psychopathic [HP/LP] traits groups) competed against two fictitious opponents in a modified Taylor Aggression Paradigm. We found that the HP group compared to the LP group selected more often high-intensity punishment for the second innocent opponent after being provoked by the first opponent. Further, a more negative N2 and a smaller P3 was found in the HP group while punishing the innocents-reflecting a tendency on antisocial-aggressive behavior. Finally, both groups showed a more negative FRN for losing than winning trials when seeing the outcome of the game. Our results suggest that high psychopathic traits increase the risk of transferring provoked aggression to innocent people-offering a psychophysiological perspective for explaining and predicting aggression against the innocents in social interactions.

Robust finite-time consensus control for multi-agent systems with disturbances and unknown velocities.

In this paper, we investigated the finite-time consensus tracking problem for multi-agent systems with external bounded disturbances and input bounded disturbances and unknown velocities. Based on the Lyapunov finite-time theorem, a novel finite-time consensus control is constructed by using the backstepping method. For unknown velocities, the high-gain observer is used to estimate the velocity information. It is proved that the consensus can be achieved in finite time. The consensus shows fast response and strong robustness to various disturbances. Finally, the effectiveness of the results is illustrated by numerical simulations.

Neural correlates of decision making after unfair treatment.

Empirical evidence indicates that people are inequity averse. However, it is unclear whether and how suffering unfairness impacts subsequent behavior. We investigated the consequences of unfair treatment in subsequent interactions with new interaction partners and the associated neural mechanisms. Participants were experimentally manipulated to experience fair or unfair treatment in the ultimatum game (UG), and subsequently, they were given the opportunity to retaliate in the dictator game (DG) in their interactions with players who had not played a role in the previous fair or unfair treatment. The results showed that participants dictated less money to unrelated partners after frequently receiving unfair offers in the previous UG (vs. frequently receiving fair offers in the previous UG), but only when they were first exposed to unfair UG/DG. Stronger activation in the right dorsal anterior insula was found during receiving unfair offers and during the subsequent offer-considering phase. The regional homogeneity (ReHo), a measure of the local synchronization of neighboring voxels in resting-state brain activity, in the left ventral anterior insula and left superior temporal pole was positively correlated with the behavior change. These findings suggest that unfair treatment may encourage a spread of unfairness, and that the anterior insula may be not only engaged in signaling social norm violations, but also recruited in guiding subsequent adaptive behaviors.

Dissociation between morality and disgust: an event-related potential study.

This study explored the neural correlates of morality and disgust, particularly, how the mechanisms that mediate our avoidance of physically disgusting and morally abhorrent behaviors are neurologically dissociated during the time-course of processing. Twelve participants were asked to judge the acceptability of different types of behaviors, which varied in their level of moral wrongness and physical disgust, while event-related potentials (ERPs) were recorded. The main results showed that the two morally wrong conditions elicited greater amplitudes of P300-400 at frontal sites than the neutral condition and the physically disgusting, but not morally wrong, condition. The physically disgusting conditions (with and without moral content) elicited significantly more positive deflections in the 500-600 ms timeframe than the neutral condition at central-posterior sites. These findings indicate that our aversion to harmful substances in the physical environment and offensive behaviors in the social environment may be neurologically dissociable in the temporal dimension. Furthermore, the detection of moral violations may be processed earlier in time than that of physical disgust.

Temporal dynamics of disgust and morality: an event-related potential study.

Disgust is argued to be an emotion that motivates the avoidance of disease-causing entities in the physical domain and unacceptable behaviors in the social-moral domain. Empirical work from behavioral, physiological and brain imaging studies suggests moral judgments are strongly modulated by disgust feelings. Yet, it remains unclear how they are related in the time course of neural processing. Examining the temporal order of disgust emotion and morality could help to clarify the role of disgust in moral judgments. In the present research, a Go/No-Go paradigm was employed to evoke lateralized readiness potentials (LRPs) to investigate the temporal order of physical disgust and moral information processing. Participants were asked to give a "yes" or "no" response regarding the physical disgust and moral wrongness of a social act. The results showed that the evaluation of moral information was processed prior to that of physical disgust information. This suggests that moral information is available earlier than physical disgust, and provides more data on the biological heterogeneity between disgust and morality in terms of the time course of neural activity. The findings implicate that physical disgust emotion may not be necessary for people to make moral judgments. They also suggest that some of our moral experience may be more fundamental (than physical disgust experience) to our survival and development, as humans spend a considerable amount of time engaging in social interaction.

Relationship of adrenomedullin expression and microvessel density and prognosis in smooth muscle tumor of uterus.

The aim of this paper was to investigate the relationship between the expression of adrenomedullin (ADM) and microvessel density (MVD) and prognosis in smooth muscle tumor of uterus. The expression of ADM was detected using immunohistochemical staining in specimens from 15 normal controls, 28 cases of uterine leiomyoma (LE) and 19 cases of uterine leiomyosarcoma (LES). The MVD was assayed by immunostainting with CD34. There was a positive correlation between the ADM expression and MVD in LE and LES respectively (r s = 0.823, P < 0.01; r s = 0.793, P < 0.01). The expression of ADM in LE was statistically lower than that in LES (P < 0.05). There was a positive correlation between the ADM expression and mitotic figures in LES (P < 0.05): the more mitotic figures, the higher levels of the ADM expression and poor prognosis. The ADM is an important angiogenic factor in smooth muscle tumor of uterus. The ADM can be used as an accessory marker in estimating the malignant potency of LE and judging the prognosis of LES, and as a novel molecular target of anti-angiogenic and anticarcinogenic strategies.