Event-Based Prescribed-Time Output Regulation of Uncertain Nonlinear Multiagent Systems.

The prescribed-time output regulation problem is investigated for a class of uncertain nonlinear multiagent systems (MASs) subject to limited communication resources. To address this challenge, an event-based distributed neuro-adaptive prescribed-time control scheme comprising distributed prescribed-time observers, a dynamic event-triggered mechanism (DETM), and neuro-adaptive prescribed-time controllers is developed. Specifically, a distributed prescribed-time observer is constructed for each agent using event-based communications to estimate the states of the exosystem.

Distributed Resilient Energy Management for Seaport Microgrid Against Stealthy Attacks With Limited Security Defense Resource.

This article investigates the distributed resilient energy management (EM) strategy for the seaport microgrid under stealthy attacks. First, based on an analysis of seaport microgrid characteristics, we construct an EM model that aims at minimizing both operating cost and security defense resource (SDR) cost. Second, we present a distributed, resilient strategy by defining node security levels and establishing dynamic security intervals.

Observer-Based Human-in-the-Loop Optimal Output Cluster Synchronization Control for Multiagent Systems: A Model-Free Reinforcement Learning Method.

This article investigates the observer-based human-in-the-loop (HiTL) optimal output cluster synchronization control problem for nonlinear multiagent systems (MASs). First, the leader is designed to be nonautonomous, with the unknown time-varying input monitored by the human operator directly. To address the problem that leader's output is not available to each follower, an observer is designed.

Platelet-Rich Plasma Versus Corticosteroids in the Treatment of Plantar Fasciitis: A Systematic Review and Meta-Analysis.

Objective: This study aims to compare the efficacy of platelet-rich plasma (PRP) and corticosteroids (CS) in treating plantar fasciitis, focusing on pain relief, foot function, and plantar fascia thickness to identify the optimal treatment approach.

Design: A comprehensive search of medical databases was conducted following PRISMA guidelines, utilizing an extensive keyword strategy. Inclusion criteria encompassed prospective RCTs involving adult patients with plantar fasciitis treated with local PRP or CS injections, specifically assessing outcomes such as the Visual Analogue Scale (VAS), American Orthopaedic Foot and Ankle Society (AOFAS) scores, and plantar fascia thickness.

The association of vitamin D with knee osteoarthritis pain: an analysis from the Osteoarthritis Initiative database.

Knee osteoarthritis (KOA) is a major cause of disability in the elderly, with its pain primarily driving medical consultations. Despite numerous studies, the role of Vitamin D in managing KOA pain remains inconclusive. This study seeks to explore the association between serum Vitamin D levels and WOMAC pain scores, providing new insights into potential treatment strategies for KOA.

Lyapunov matrix-based adaptive resilient control for unmanned marine vehicles with sensor and thruster attacks.

This paper presents the design of a Lyapunov matrix-based adaptive resilient controller for unmanned marine vehicles (UMVs) under state-dependent sensor attacks, input-dependent thruster attacks, and time delays. Different from the thruster attack model that depends on state information, the thruster attack model studied in this paper is related to control input, that is, the input-dependent thruster attacks. This implies that the designed correction signal is also affected by the attacks.

MPC-Based Asynchronous Attack Tolerant Control for Uncertain Markov Jump Cyber-Physical Systems.

The model predictive control (MPC)-based asynchronous attack tolerant control scheme is investigated in this article for uncertain Markov jump cyber-physical systems (MJCPSs) under the Denial-of-Service (DoS) attack. To tackle the problem of the system running mode may not be observed in the control center, an asynchronous model predictive controller is proposed. Specifically, a dynamic controller, which can tune the performance online, is designed besides a traditional state feedback one.

Platelet-rich plasma alleviates neuropathic pain in osteoarthritis by downregulating microglial activation.

Background: The development of neuropathic pain (NP) is one of the reasons why the pain is difficult to treat, and microglial activation plays an important role in NP. Recently, platelet-rich plasma (PRP) has emerged as a novel therapeutic method for knee osteoarthritis (KOA). However, it's unclarified whether PRP has analgesic effects on NP induced by KOA and the underlying mechanisms unknown.

Demonstrating the effectiveness of intra-articular prolotherapy combined with peri-articular perineural injection in knee osteoarthritis: a randomized controlled trial.

Background: This study aimed to compare the efficacy of intra-articular prolotherapy (IG) combined with peri-articular perineural injection (PG) in the management of knee osteoarthritis (KOA).

Methods: A total of 60 patients with the diagnosis of KOA were included in this double-blinded randomized controlled clinical trials. The inclusion criteria were as follow: (1) 48-80 years old; (2) the diagnose of KOA; (3) the grade 2 and 3 of the Kellgern-Lawrence grading scale; (4) the pain, crepitation, and knee joint stiffness continuing for 3 months at least.

Attack-resilient fault detection for interconnected systems under DoS attack.

In light of the expanding cyber-space applications, the imperative consideration of cyber-attack ramifications on system security is evident. This paper presents a resilient dynamic event-triggered fault detection scheme for a class of nonlinear interconnected systems subjected to denial of service (DoS) attacks. To counteract multifaceted threats, the co-design challenge involving switched-type fault detection filters and a resilient dynamic event-triggered transmission mechanism is addressed.

End-to-end model-based trajectory prediction for ro-ro ship route using dual-attention mechanism.

With the rapid increase of economic globalization, the significant expansion of shipping volume has resulted in shipping route congestion, causing the necessity of trajectory prediction for effective service and efficient management. While trajectory prediction can achieve a relatively high level of accuracy, the performance and generalization of prediction models remain critical bottlenecks. Therefore, this article proposes a dual-attention (DA) based end-to-end (E2E) neural network (DAE2ENet) for trajectory prediction.

Fixed-time command-filtered composite adaptive neural fault-tolerant control for strict-feedback nonlinear systems.

The research investigates the fixed-time command-filtered composite adaptive neural fault-tolerant (FCCANF) control issue of strict-feedback nonlinear systems (SFNSs). There exist unknown functions and bounded disturbances in the considered systems. Radial basis function neural networks (RBFNNs) will be used in the estimate of the unknown functions.

Transcranial direct current stimulation attenuates chronic pain in knee osteoarthritis by modulating BDNF/TrkB signaling in the descending pain modulation system.

Knee osteoarthritis (KOA) is the most common cause of chronic pain, but its pain mechanisms are complex and may be closely related to the descending pain modulation system. Transcranial direct current stimulation (tDCS) is used for relieving pain, but its analgesic mechanisms are still being explored. The purpose of this study was to investigate the role of BDNF/TrkB signaling in chronic pain in KOA and to investigate whether this signaling is related to the analgesic effect of tDCS.

Continuous and Periodic Event-Triggered Sliding-Mode Control for Path Following of Underactuated Surface Vehicles.

This article develops continuous and periodic event-triggered sliding-mode control (SMC) algorithms for path following of underactuated surface vehicles (USVs). Based on the SMC technology, a continuous path-following control law is designed. The upper bounds of quasi-sliding modes for path following of USVs are established for the first time.

Heading and velocity guidance based path following of autonomous surface vehicle with uncertainty attenuation and asymmetric saturated constraints.

The path following of underactuated autonomous surface vehicle (ASV) with line-of-sight (LOS)-based heading and velocity guidance is studied thoroughly in the presence of complex uncertainties and asymmetric input saturation that actuators are likely to suffer from. On the basis of the extended-state-observer-based LOS (ELOS) principle and guided velocity design strategies, a finite-time heading and velocity guidance control (HVG) scheme is presented. Firstly, an improved ELOS (IELOS) is developed such that the unknown sideslip angle can be estimated directly, instead of requiring one more step to calculate it by the output of observers and relying on the equivalent assumption between actual heading angle and guidance angle.

Event-Triggered Distributed Secondary Control With Model-Free Predictive Compensation in AC/DC Networked Microgrids Under DoS Attacks.

This article presents an event-triggered distributed secondary control with predictive compensation based on the model-free predictive control under Denial-of-Service (DoS) attacks in ac/dc-networked microgrids. First, models of ac/dc networked microgrids in both electric network and communication network are established. On this premise, event-triggered distributed secondary control is proposed to solve the problems of strong communication burden and low-power distribution accuracy.

Adaptive composite dynamic surface neural control for nonlinear fractional-order systems subject to delayed input.

In the article, the adaptive composite dynamic surface neural controller design problem for nonlinear fractional-order systems (NFOSs) subject to delayed input is discussed. A fractional-order auxiliary system is first designed to solve the input-delay problem. By using the developed novel estimation models, the defined prediction errors and the states of error system can decide the weights of radial basis function neural networks (RBFNNs).

Can noninvasive Brain Stimulation Improve Pain and Depressive Symptoms in Patients With Neuropathic Pain? A Systematic Review and Meta-Analysis.

Context: Noninvasive brain stimulations (NIBS) have been increasingly applied to the patients with neuropathic pain (NP), while the effectiveness of NIBS in the management of NP is still conflicting.

Objectives: To examine the effectiveness of NIBS on pain and depression symptoms of patients with NP.

Methods: A comprehensive literature retrieval was performed on MEDLINE, Embase, PsycINFO, PEDro, and CENTRAL from the establishment of the databases to June 2021.

Anti-Attack Event-Triggered Control for Nonlinear Multi-Agent Systems With Input Quantization.

In this article, an anti-attack event-triggered secure control scheme for a class of nonlinear multi-agent systems with input quantization is developed. With the help of neural networks approximating unknown nonlinear functions, unknown states are obtained by designing an adaptive neural state observer. Then, a relative threshold event-triggered control strategy is introduced to save communication resources including network bandwidth and computational capabilities.

Botulinum toxin type a combined with transcranial direct current stimulation reverses the chronic pain induced by osteoarthritis in rats.

Osteoarthritis (OA) is the most common cause to lead to chronic pain. Sensitization of pain pathways including central sensitization and peripheral sensitization has been regarded as a major cause of OA pain refractory to treatment. Addressing peripheral sensitization or central sensitization alone may not adequately treat OA pain.

Gait Prediction and Variable Admittance Control for Lower Limb Exoskeleton With Measurement Delay and Extended-State-Observer.

The measurement delay of the feedback control system is a universal problem in industrial engineering, which will degrade output performance, especially causing undesirable chatter responses. In this study, a deep-Gaussian-process (DGP)-based method for operator's gait prediction is proposed to estimate the real-time motion intention and to compensate for the measurement delay of the inertial measurement unit (IMU). On the basis of these gait prediction uncertainties quantified by the DGP method, a variable admittance controller is designed to reduce real-time human-exoskeleton interaction torque.

Transcranial Direct Current Stimulation Alleviates the Chronic Pain of Osteoarthritis by Modulating NMDA Receptors in Midbrain Periaqueductal Gray in Rats.

Purpose: Osteoarthritis (OA) is the most common cause to lead to chronic pain. Transcranial direct current stimulation (tDCS) has been widely used to treat nerve disorders and chronic pain. The benefits of tDCS for chronic pain are apparent, but its analgesic mechanism is still unclear.

BoNT/A alleviates neuropathic pain in osteoarthritis by down-regulating the expression of P2X4R in spinal microglia.

Neuropathic pain in osteoarthritis is one of the reasons why the pain is difficult to treat, and P2X4R plays an important role in neuropathic pain. In addition, BoNT/A has been proven to have analgesic effects on both neuropathic pain and osteoarthritis, but its exact mechanism is still unknown. This study aims to investigate the relationship between the analgesic effect of BoNT/A on osteoarthritis and the expression of P2X4R in spinal cord microglia.