Stochastic Optimal Control for Robot Manipulation Skill Learning Under Time-Varying Uncertain Environment.

In this article, a novel stochastic optimal control method is developed for robot manipulator interacting with a time-varying uncertain environment. The unknown environment model is described as a nonlinear system with time-varying parameters as well as stochastic information, which is learned via the Gaussian process regression (GPR) method as the external dynamics. Integrating the learned external dynamics as well as the stochastic uncertainties, the complete interaction system dynamics are obtained. Then the iterative linear quadratic Gaussian with learned external dynamics (ILQG-LEDs) method is presented to obtain the optimal manipulation control parameters, namely, the feedforward force, the reference trajectory, as well as the impedance parameters, subject to time-varying environment dynamics. The comparative simulation studies verify the advantages of the presented method, and the experimental studies of the peg-hole-insertion task prove that this method can deal with complex manipulation tasks.

Discrete-time practical robotic control for human-robot interaction with state constraint and sensorless force estimation.

Employing a continuous-time control algorithm to control the practical system based on discrete-time digital computer will lead to the cost of performance degeneration. To address this issue, this paper proposes a discrete-time barrier Lyapunov function based controller for human-robot interaction in constrained task space to guarantee control performance. The Euler discrete-time stability of closed-loop system controlled by the proposed method is proved, and a feasible difference scheme to support the stability analysis is uncovered based on monotonic scaling. The parameter dependence of this study is well discussed, which involves sample interval and preset boundary of state constraints, and based on the architecture of barrier Lyapunov function, the dependence relationship is demonstrated by using analytical synthesis technique. With a certain sample interval, the proposal of controller parameters is qualified to guarantee that end-effector states are constrained with preset boundary. The discrete-time neural network estimation is designed to approximate the human being's behavior to rebuild the reference trajectory from the desired trajectory and impedance for smoothing the human-robot interaction. Controlled discrete-time states and estimated force are uniformly ultimately bounded, and the convergence vicinity around the origin is proven to be determined by sample interval, lumped uncertainty and preset boundary of state constraints. Numerical simulation and experimental results verify the effectiveness of proposed discrete-time barrier Lyapunov function based methods.

Therapeutic effect of low-molecular-weight heparin on adult sepsis: a meta-analysis.

BACKGROUND: Low-molecular-weight heparin (LMWH) is a part of standard supportive therapy for sepsis, but clinical research on anticoagulant therapy is still controversial. The aim of the present study was to explore the efficacy and safety of LMWH in adult septic patients by meta-analysis. METHODS: Information on randomized controlled trials was retrieved from PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and China Wanfang Database from the establishment of each database to February 20, 2020. The therapeutic efficacy indexes of LMWH for adult septic patients were analyzed by Stata15.0 software. RESULTS: A total of 684 septic patients were included in 10 trials. The results showed that, compared with conventional treatment, LMWH significantly reduced prothrombin time [mean difference (MD) =-0.48, 95% confidence interval (CI): -0.83 to -0.13], Acute Physiology And Chronic Health Evaluation II score (MD=-4.42, 95% CI: -5.50 to -3.33), and 28-day mortality [relative risk (RR) =0.52, 95% CI: 0.38-0.70], and increased platelet count (MD =34.99, 95% CI: 23.37-46.60). LMWH significantly reduced levels of tumor necrosis factor-α, interleukin-6, and D-dimer, and the incidence of multiple organ dysfunction syndrome (MODS), with statistically significant differences. In addition, LMWH did not increase bleeding events (RR =1.29, 95% CI: 0.76-2.17). CONCLUSIONS: On the basis of routine treatment, LMWH can improve coagulation function, reduce inflammatory reaction and the risk of bleeding, reduce the incidence of MODS and 28-day mortality rate, and improve the prognosis of adult patients with sepsis.

CacyBP/SIP promotes the proliferation of colon cancer cells.

CacyBP/SIP is a component of the ubiquitin pathway and is overexpressed in several transformed tumor tissues, including colon cancer, which is one of the most common cancers worldwide. It is unknown whether CacyBP/SIP promotes the proliferation of colon cancer cells. This study examined the expression level, subcellular localization, and binding activity of CacyBP/SIP in human colon cancer cells in the presence and absence of the hormone gastrin. We found that CacyBP/SIP was expressed in a high percentage of colon cancer cells, but not in normal colonic surface epithelium. CacyBP/SIP promoted the cell proliferation of colon cancer cells under both basal and gastrin stimulated conditions as shown by knockdown studies. Gastrin stimulation triggered the translocation of CacyBP/SIP to the nucleus, and enhanced interaction between CacyBP/SIP and SKP1, a key component of ubiquitination pathway which further mediated the proteasome-dependent degradation of p27kip1 protein. The gastrin induced reduction in p27kip1 was prevented when cells were treated with the proteasome inhibitor MG132. These results suggest that CacyBP/SIP may be promoting growth of colon cancer cells by enhancing ubiquitin-mediated degradation of p27kip1.