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| 1 | Single-cell analysis reveals bronchoalveolar epithelial dysfunction in COVID-19 patients显示文摘Dear Editor,In 2019,a zoonotic coronavirus named severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)was identified as the causative agent of Coronavirus Disease 2019(COVID-19).As of 8 June 2020,the World Health Organization(WHO)has reported 6,912,751 globally confirmed cases with 400,469 deaths.Although generally causes mild disease,SARS-CoV-2 infection can result in serious outcomes,including acute lung injury(ALI)and acute respiratory distress syndrome(ARDS),the leading cause of mortality in patients with comorbidities.Recent autopsy studies of COVID-19 patients revealed mononuclear infiltration and excessive production of mucus in the infected lung,especially in the damaged small airways and alveoli(Bian and Team,2020;Liu et al.,2020). | Jiangping He Shuijiang Cai Huijian Feng Baomei Cai Lihui Lin Yuanbang Mai Yinqiang Fan Airu Zhu Huang Huang Junjie Shi Dingxin Li' Yuanjie Wei Yueping Li Yingying Zhao’ Yuejun Pan He Liu Xiaoneng Mo Xi He Shangtao Cao FengYu Hu Jincun Zhao Jie Wang Nanshan Zhong Xinwen Chen Xilong Deng Jiekai Chen | 2020 | Protein & Cell2020，11，9： | 7 |
| 2 | Online identification of time-varying dynamical systems for industrial robots based on sparse Bayesian learning显示文摘Nowadays, industrial robots have been widely used in manufacturing, healthcare, packaging, and more. Choosing robots in these applications mainly attributes to their repeatability and precision. However, prolonged and loaded operations can deteriorate the accuracy and efficiency of industrial robots due to the unavoidable accumulated kinematical and dynamical errors. This paper resolves these aforementioned issues by proposing an online time-varying sparse Bayesian learning(SBL) method to identify dynamical systems of robots in real-time. The identification of dynamical systems for industrial robots is cast as a sparse linear regression problem. By constructing the dictionary matrix, the parameters of the robot dynamics are effectively estimated via a re-weighted1-minimization algorithm. Online recursive methods are integrated into SBL to achieve real-time system identification. By including sparsity and promoting online learning, the proposed method can handle time-varying dynamical systems and therefore improve operational stability and accuracy. Experimental results on both simulated and real selective compliance assembly robot arm(SCARA) robots have demonstrated the effectiveness of the proposed method for industrial robots. | SHEN Tan DONG YunLong HE DingXin YUAN Ye | 2022 | Science China(Technological Sciences)2022，65，2： | 4 |
| 3 | Event- triggered control for networked control systems with quantization and packet losses显示文摘 | QU Fenglin GUAN Zhihong HE Dingxin | 2015 | Journal of the Franklin Institute2015，352，3： | 1 |
| 4 | A Fractional-Order Ultra-Local Model-Based Adaptive Neural Network Sliding Mode Control of n-DOF Upper-Limb Exoskeleton With Input Deadzone显示文摘This paper proposes an adaptive neural network sliding mode control based on fractional-order ultra-local model for n-DOF upper-limb exoskeleton in presence of uncertainties,external disturbances and input deadzone.Considering the model complexity and input deadzone,a fractional-order ultra-local model is proposed to formulate the original dynamic system for simple controller design.Firstly,the control gain of ultra-local model is considered as a constant.The fractional-order sliding mode technique is designed to stabilize the closed-loop system,while fractional-order time-delay estimation is combined with neural network to estimate the lumped disturbance.Correspondingly,a fractional-order ultra-local model-based neural network sliding mode controller(FO-NNSMC) is proposed.Secondly,to avoid disadvantageous effect of improper gain selection on the control performance,the control gain of ultra-local model is considered as an unknown parameter.Then,the Nussbaum technique is introduced into the FO-NNSMC to deal with the stability problem with unknown gain.Correspondingly,a fractional-order ultra-local model-based adaptive neural network sliding mode controller(FO-ANNSMC) is proposed.Moreover,the stability analysis of the closed-loop system with the proposed method is presented by using the Lyapunov theory.Finally,with the co-simulations on virtual prototype of 7-DOF iReHave upper-limb exoskeleton and experiments on 2-DOF upper-limb exoskeleton,the obtained compared results illustrate the effectiveness and superiority of the proposed method. | Dingxin He HaoPing Wang Yang Tian Yida Guo | 2024 | IEEE/CAA Journal of Automatica Sinica2024，11，3： | 0 |
| 5 | Syntheses, Optical Properties and Photoactivated Insecticidal Activities of Cyclic Arylethynylsilanes显示文摘综合体和包含一或二个 trialkyne 衣袋的周期的 arylethynylsilanes 的光性质被描述。象基于这些结合的结构的特征的紫外力的系列,光致发光和量产量那样的光性质与对方相比。对豹脚蚊 albopictus (Skuse ) 的 4th 中间形态幼虫的用光使敏化的杀虫的活动被评估。 | Shao Guang Li Yong Yu Huijuan He Ting Jiang Dingxin | 2011 | Chinese Journal of Chemistry2011，29，2： | 0 |
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