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It is well understood that motor dysfunctions in patients can be restored through a certain amount of repetitive training. Robots and virtual reality offer an excellent solution to incentivize and optimize training intensity while also reducing the workload for therapists. In this paper, leveraging virtual reality technologies and haptic robots, we have developed a cost-effective robot-assisted training system and three training exercises for hand rehabilitation. The Unity game engine was utilized to create training scenarios where hand avatars interact with virtual objects. Off-the-shelf haptic robots were employed to manipulate the hand avatars, enabling completion of training tasks with a realistic tactile experience. Haptic feedback is rendered using impedance control laws. Additionally, to address the needs of both patients and therapists we propose to employ robot-assisted force and feedback force. These mechanisms are designed to provide assistance to patients during tasks if needs and to transmit the patient's force feedback to the therapist, facilitating comprehensive interaction and communication between the two parties. Several experiments were conducted involving six healthy subjects, who used electrode stimulation to simulate impaired limbs, to demonstrate the effectiveness of the proposed training frameworks. [ABSTRACT FROM AUTHOR]

Safety concern among electric scooter riders drives them onto sidewalks, endangering pedestrians and making them uncomfortable. Regulators' solutions are inconsistent and conflicting worldwide. Widely accepted pedestrian safety metrics may lead to converging solutions. Adapting the time-to-collision from car traffic safety, we define projected time-to-collision and experimentally study pedestrians' objective and subjective safety. We design isolated and crowd experiments using e-scooter-to-pedestrian interactions to assess the impact of various factors on objective safety. In addition, we conducted a pedestrian survey to relate the subjective safety and the metric. We report a strong correlation between subjective safety and the projected time-to-collision when agents face each other and no relation when the e-scooter overtakes a pedestrian. As a near-miss metric correlated with pedestrian comfort, projected time-to-collision is implementable in policy-making, urban architecture, and e-scooter design to enhance pedestrian safety. Regulators' approach to electric scooters on sidewalks is inconsistent and conflicting worldwide. Maintaining a minimum projected time-to-collision as a near-miss metric provides a sufficient condition for pedestrian safety as well as improving pedestrian subjective perceived safety. [ABSTRACT FROM AUTHOR]

Long-term memory formation requires de novo RNA and protein synthesis. Using differential display PCR, we found that the NCoR1 cDNA fragment is differentially expressed between fast learners and slow learners, with fast learners showing a lower expression level than slow learners in the water maze learning task. Fast learners also show lower NCoR1 mRNA and protein expression levels. In addition, spatial training decreases both NCoR1 mRNA and protein expression, whereas NCoR1 conditional knockout (cKO) mice show enhanced spatial memory. In studying the molecular mechanism, we found that spatial training decreases the association between NCoR1 and DEC2. Both NCoR1 and DEC2 suppress the expression of BDNF, integrin α3 and SGK1 through C/EBPα binding to their DNA promoters, but overexpression of DEC2 in NCoR1 cKO mice rescues the decreased expression of these proteins compared with NCoR1 loxP mice overexpressing DEC2. Further, spatial training decreases DEC2 expression. Spatial training also enhances C/EBPα binding to Bdnf, Itga3 and Sgk1 promoters, an effect also observed in fast learners, and both NCoR1 and DEC2 control C/EBPα activity. Whereas knockdown of BDNF, integrin α3 or SGK1 expression impairs spatial learning and memory, it does not affect Y-maze performance, suggesting that BDNF, integrin α3 and SGK1 are involved in long-term memory formation, but not short-term memory formation. Moreover, NCoR1 expression is regulated by the JNK/c-Jun signaling pathway. Collectively, our findings identify DEC2 as a novel interacting protein of NCoR1 and elucidate the novel roles and mechanisms of NCoR1 and DEC2 in negative regulation of spatial memory formation. [ABSTRACT FROM AUTHOR]

In this paper, we propose a fault detection, fault isolation, and control reconfiguration (FDIR) for multiple automated guided vehicles (AGVs) to accomplish object transportation under actuator failures. Firstly, the observers are designed for the AGVs to detect any occurring faults in actuators. Secondly, banks of observers are employed to isolate the broken actuators. Finally, according to the isolation results, the controllers are reconfigured to accommodate the faults. The stability of the proposed methods is verified using the Lyapunov technique. It is worth noting that the proposed FDIR method considers the uncertainties in system dynamics, enhancing its practicality and convenience for implementation. The effectiveness of the proposed algorithm is demonstrated via both numerical and experimental examples involving multiple omnidirectional AGVs experiencing actuator faults. [ABSTRACT FROM AUTHOR]

This paper investigates the resilient annular finite‐time synchronization and boundedness problems for master‐slave systems under dynamic event‐triggered scheme (ETS), actuator faults, and scaling attacks. A comprehensive model for characterizing scaling attacks is presented. The switched dynamic ETS is developed to reduce the bandwidth pressure. Two different internal variables are designed, each of which changes based on the switching manifold. Simultaneously, the resilient problem of switched master‐slave systems with respect to stochastic scaling attacks is considered, where there are limited malicious signals introduced by the adversary. Based on the Lyapunov‐like function involving the different internal dynamic variables, a set of criteria is established in the form of linear matrix inequalities (LMIs), which guarantee the annular finite‐time boundedness. Finally, two examples are presented to verify the theoretical findings. [ABSTRACT FROM AUTHOR]

Cooperative robotics has gained considerable traction in the industrial sector with the expeditious use of multi-agent systems. Containment control is an emergent topic in cooperative multi-agent systems, with applications in areas such as warehouse robotics, inventory management, and transportation. Containment control is an amalgamation of formation and consensus control, which predominantly uses groups of multiple agents assigned as leaders and followers. This survey paper provides a comprehensive overview of key topics in containment control of multi-agent systems ranging from containment concepts to controllers. The paper discusses the role of communication and network topologies, the importance of accurate sensor measurements and agent dynamics, and various controller design and stability analysis techniques. The paper concludes by highlighting the promising research directions and challenges in the field along with real-world applications. Overall, this survey paper provides a valuable resource for researchers, practitioners, and students interested in the development of advanced multi-agent systems with containment control. [ABSTRACT FROM AUTHOR]