Design, dynamic modeling and testing of a novel MR damper for cable-stayed climbing robots under wind loads.

To increase the adaptability of bridge construction equipment in high-altitude settings, this study examines a magnetorheological (MR) damper designed for cable-stayed climbing robots. Initially, a novel damper incorporating a spring-MR fluid combination and three magnetic circuit units is developed. A robot-cable-wind coupling dynamic model is subsequently formulated via Hamilton's principle, based on force analysis.

Model-free distributed state estimation with local measurements.

In this paper, the state estimation problem of physical plants with unknown system dynamic is revisited from the perspective of limited output information measurement, which corresponds to those with characteristics of high-dimensional, wide-area coverage and scatter. Given this fact, a network of sensors are used to carry out the measurement with each one accessing only partial outputs of the targeted systems and a novel model-free state estimation approach, named distributed stochastic variational inference state estimation, is proposed. The key idea of this method is to compensate for the impacts of local output measurements by adding nearest-neighbor rule-based information interaction among estimators to complete the state estimation.

Impact of metabolic disorders on gallstone disease and perioperative recovery after laparoscopic cholecystectomy.

Background: Gallstone disease (GSD), nonalcoholic fatty liver disease (NAFLD), metabolic dysfunction-associated fatty liver disease (MAFLD), and metabolic syndrome (MetS) are common medical disorders worldwide. This study aimed to ascertain how NAFLD, MAFLD, MetS, and other factors affect the development of GSD, and how the GSD-associated factors influence patient recovery after laparoscopic cholecystectomy (LC).

Methods: We included 200 patients who were diagnosed with GSD and underwent LC between January 2017 and February 2022.

A data-driven epidemic model with human mobility and vaccination protection for COVID-19 prediction.

Epidemiological models allow for quantifying the dynamic characteristics of large-scale outbreaks. However, capturing detailed and accurate epidemiological information often requires consideration of multiple kinetic mechanisms and parameters. Due to the uncertainty of pandemic evolution, such as pathogen variation, host immune response and changes in mitigation strategies, the parameter evaluation and state prediction of complex epidemiological models are challenging.

Phase I study of a non-S2P SARS-CoV-2 mRNA vaccine LVRNA009 in Chinese adults.

Background: COVID-19 caused by SARS-CoV-2 is a great threat to public health. We present the safety and immunogenicity data from a phase I trial in China of an mRNA vaccine (LVRNA009).

Methods: In the single-centre, double-blind, placebo-controlled and dose-escalation study, 72 healthy unvaccinated adults aged 18-59 years were randomized (3:1) to receive LVRNA009 with one of three vaccine dosage (25, 50 and 100 μg) or placebo, to evaluate for the safety, tolerability and immunogenicity of LVRNA009.

Kinematic modelling and experimental testing of a particle-jamming soft robot based on a DEM-FEM coupling method.

Particle-jamming soft robots are characterised by high flexibility in motion and high stiffness when executing a task. Regarding particle jamming of soft robots, the discrete element method (DEM)-finite element method (FEM) coupling was used for modelling and control. At first, a real-time particle-jamming soft actuator was proposed by integrating advantages of the driving Pneu-Net and the driven particle-jamming mechanism.

[Expression level and clinical significance of CD44 and CD33 in 77 patients with benign lymphoadenosis of oral mucosa].

Purpose: To investigate the expression and clinical significance of CD44 and CD33 in benign lymphoadenosis of oral mucosa(BLOM).

Methods: From January 2017 to March 2020, seventy-seven BLOM wax blocks from the Department of Pathology of Qingdao Traditional Chinese Medicine Hospital were selected as the experimental group, and 63 cases of normal oral mucosal tissue wax blocks during the same period were selected as the control group. Immunohistochemical method was used to detect the positive expression of CD44 and CD33 in the two groups.

Reactive-diffusion epidemic model on human mobility networks: Analysis and applications to COVID-19 in China.

The complex dynamics of human mobility, combined with sporadic cases of local outbreaks, make assessing the impact of large-scale social distancing on COVID-19 propagation in China a challenge. In this paper, with the travel big dataset supported by Baidu migration platform, we develop a reactive-diffusion epidemic model on human mobility networks to characterize the spatio-temporal propagation of COVID-19, and a novel time-dependent function is incorporated into the model to describe the effects of human intervention. By applying the system control theory, we discuss both constant and time-varying threshold behavior of proposed model.

Observer-Based Multiagent Bipartite Consensus With Deterministic Disturbances and Antagonistic Interactions.

This article studies the multiagent bipartite consensus in networks with deterministic disturbances and antagonistic interactions. An observer-based output-feedback controller design is provided to guarantee the bipartite consensus with deterministic disturbances that satisfy the matching condition. Then, by considering that the bandwidths of communication channels are limited in practical systems, the event-triggered scenario of the proposed output controller for the bipartite consensus is further studied; the node-based broadcast updating fashion is utilized and the Zeno behavior is ruled out.

Consensus-Based Distributed Reduced-Order Observer Design for LTI Systems.

In this article, we refocus on the distributed observer construction of a continuous-time linear time-invariant (LTI) system, which is called the target system, by using a network of observers to measure the output of the target system. Each observer can access only a part of the component information of the output of the target system, but the consensus-based communication among them can make it possible for each observer to estimate the full state vector of the target system asymptotically. The main objective of this article is to simplify the distributed reduced-order observer design for the LTI system on the basis of the consensus communication pattern.

Consensus of Continuous-Time Linear Multiagent Systems With Discrete Measurements.

This article concerns the robust consensus problem of continuous-time linear multiagent systems (MASs) with uncertainty and discrete-time measurement information, where the output measurement information is in the data-sampled form. Distributed output-feedback protocol with or without controller interaction is proposed for each agent. Specifically, the output-feedback protocol runs in continuous time with an output error correction term mixed with the discrete-time measurement information.

An iterative Q-learning based global consensus of discrete-time saturated multi-agent systems.

This paper addresses the consensus problem of discrete-time multiagent systems (DTMASs), which are subject to input saturation and lack of the information of agent dynamics. In the previous works, the DTMASs with input saturation can achieve semiglobal consensus by utilizing the low gain feedback (LGF) method, but computing the LGF matrices by solving the modified algebraic Riccati equation requires the knowledge of agent dynamics. In this paper, motivated by the reinforcement learning method, we propose a model-free Q-learning algorithm to obtain the LGF matrices for the DTMASs achieving global consensus.

A New Model for Complex Dynamical Networks Considering Random Data Loss.

Model construction is a very fundamental and important issue in the field of complex dynamical networks. With the state-coupling complex dynamical network model proposed, many kinds of complex dynamical network models were introduced by considering various practical situations. In this paper, aiming at the data loss which may take place in the communication between any pair of directly connected nodes in a complex dynamical network, we propose a new discrete-time complex dynamical network model by constructing an auxiliary observer and choosing the observer states to compensate for the lost states in the coupling term.

Novel epidemic models on PSO-based networks.

This paper proposes two spatio-temporal epidemic network models based on popularity and similarity optimization (PSO), called r-SI and r-SIS, respectively, in which new connections take both popularity and similarity into account. In the spatial dimension, the epidemic process is described by the diffusion equation; in the time dimension, the growth of an epidemic is described by the logistic map. Both models are represented by partial differential equations, and can be easily solved.

Modeling and analysis of epidemic spreading on community networks with heterogeneity.

A large number of real world networks exhibit community structure, and different communities may often possess heterogeneity. In this paper, considering the heterogeneity among communities, we construct a new community network model in which the communities show significant differences in average degree. Based on this heterogeneous community network, we propose a novel mathematical epidemic model for each community and study the epidemic dynamics in this network model.

Distributed Finite Time Consensus of Secondorder Multi-agent Systems via Pinning Control (August 2018).

The robust distributed finite time consensus of second-order multi-agent systems via pinning control has been investigated in this paper. A new nonsingular finite time TSM control method is proposed for second-order single system with disturbances. Based on the pinning error function vector, robust distributed finite time consensus of second-order multi-agent systems via pinning control method is given.

State Estimation for General Complex Dynamical Networks with Incompletely Measured Information.

Estimating uncertain state variables of a general complex dynamical network with randomly incomplete measurements of transmitted output variables is investigated in this paper. The incomplete measurements, occurring randomly through the transmission of output variables, always cause the failure of the state estimation process. Different from the existing methods, we propose a novel method to handle the incomplete measurements, which can perform well to balance the excessively deviated estimators under the influence of incomplete measurements.

An Adaptive Primal-Dual Subgradient Algorithm for Online Distributed Constrained Optimization.

In this paper, we consider the problem of solving distributed constrained optimization over a multiagent network that consists of multiple interacting nodes in online setting, where the objective functions of nodes are time-varying and the constraint set is characterized by an inequality. Through introducing a regularized convex-concave function, we present a consensus-based adaptive primal-dual subgradient algorithm that removes the need for knowing the total number of iterations in advance. We show that the proposed algorithm attains an [where ] regret bound and an bound on the violation of constraints; in addition, we show an improvement to an regret bound when the objective functions are strongly convex.

Epidemic spreading in metapopulation networks with heterogeneous infection rates.

In this paper, we study epidemic spreading in metapopulation networks wherein each node represents a subpopulation symbolizing a city or an urban area and links connecting nodes correspond to the human traveling routes among cities. Differently from previous studies, we introduce a heterogeneous infection rate to characterize the effect of nodes' local properties, such as population density, individual health habits, and social conditions, on epidemic infectivity. By means of a mean-field approach and Monte Carlo simulations, we explore how the heterogeneity of the infection rate affects the epidemic dynamics, and find that large fluctuations of the infection rate have a profound impact on the epidemic threshold as well as the temporal behavior of the prevalence above the epidemic threshold.

Inhibitory effects of transcription factor Ikaros on the expression of liver cancer stem cell marker CD133 in hepatocellular carcinoma.

CD133 is a cellular surface glycoprotein that has been reported as a marker for the enrichment of cancer stem cells (CSCs). However, the regulatory mechanism of CD133 remains unknown. CSCs have been proposed to contribute to radioresistance and multi-drug resistance.

Diagnostic value of parasternal pulmonary artery short-axis view for the anomalous origin of the left coronary artery from the pulmonary artery.

Objective: To evaluate the diagnostic value of parasternal pulmonary artery (PA) short-axis view for the anomalous origin of left coronary artery (LCA) from the pulmonary artery by echocardiography.

Methods: A total of 13 patients (3 boys) aged from 2 months to 12 years were enrolled. Transthoracic echocardiography, including cross-sectional imaging and color Doppler flow imaging, were performed, and their diagnoses were confirmed by operation.

Noninvasive perioperative evaluation of right ventricular function in children with tetralogy of Fallot.

Early and accurate noninvasive means of identifying right ventricular (RV) dysfunction in children with tetralogy of Fallot (TOF) are needed. RV function was examined using tissue Doppler imaging (TDI), strain rate (SR), and strain analysis (SA) in children before (N = 37) and after (6-12 months; N = 32) TOF repair, and in a control group of children (N = 37). Plasma concentrations of N-terminal pro-brain natriuretic peptide (NT-proBNP) and matrix metalloproteinase 9 (MMP-9) were measured.

Time-varying human mobility patterns with metapopulation epidemic dynamics.

In this paper, explicitly considering the influences of an epidemic outbreak on human travel, a time-varying human mobility pattern is introduced to model the time variation of global human travel. The impacts of the pattern on epidemic dynamics in heterogeneous metapopulation networks, wherein each node represents a subpopulation with any number of individuals, are investigated by using a mean-field approach. The results show that the pattern does not alter the epidemic threshold, but can slightly lower the final average density of infected individuals as a whole.

A new method for evaluating tricuspid valve displacement in children with Ebstein's anomaly: using the annulus and coronary sinus as a reference point.

This study aimed to investigate the reference point for the downward displacement of the posterior and anterior leaflets of the tricuspid valve using echocardiography in children with Ebstein's anomaly. This study enrolled 25 patients with Ebstein's anomaly. The extent of downward displacement of the posterior and anterior leaflets of the tricuspid valve was evaluated by echocardiography using the tricuspid annulus and the coronary sinus as reference points.

[Echocardiographic diagnosis of partial anomalous pulmonary venous connection].

Objective: To investigate partial anomalous pulmonary venous connection (PAPVC) with echocardiography.

Methods: The right ventricular volume overload was detected by routine echocardiography in 37 child patients, who underwent further echocardiography to find the abnormal locations of pulmonary vein opening at superior, inferior vena cava and right atrium. The ultrasound results were compared with surgical findings.