COVID-19 has globally spread to over 4 million people and the epidemic situation in Japan is very serious. The purpose of this research was to assess the risk of COVID-19 epidemic dissemination in Japan by estimating the current state of epidemic dissemination and providing some epidemic prevention and control recommendations. Firstly, the period from 6 January to 31 March 2020 was divided into four stages and the relevant parameters were estimated according to the imported cases in Japan. The basic reproduction number of the current stage is 1.954 (95% confidence interval (CI) 1.851–2.025), which means COVID-19 will spread quickly, and the self-healing rate of Japanese is about 0.495 (95% CI 0.437–0.506), with small variations in the four stages. Secondly, the results were applied to the actual reported cases from 1 to 5 April 2020, verifying the reliability of the estimated data using the accumulated reported cases located within the 95% confidence interval and the relative error of forecast data of five days being less than $2.5\%$ . Thirdly, considering the medical resources in Japan, the times the epidemic beds and ventilators become fully occupied are predicted as 5 and 15 May 2020, respectively. Keeping with the current situation, the final death toll in Japan may reach into the millions. Finally, based on experience with COVID-19 prevention and control in China, robust measures such as nationwide shutdown, store closures, citizens isolating themselves at home, and increasing PCR testing would quickly and effectively prevent COVID-19 spread.

The unique drive principle and strong manipulation ability of spider legs have led to several bionic robot designs. However, some parameters of bionic actuators still need to be improved, such as torque. Inspired by the hydraulic drive principle of spider legs, this paper describes the design of a bionic actuator characterized by the use of air pressure on each surface and its transmittance in the direction of movement, achieving a torque amplification effect. The produced torque is as high as 4.78 N m. In addition, its torque characteristics during folding motions are similar to those during unfolding motions, showing that the bionic actuator has stable bidirectional drive capability.

In this paper, we formulate and solve a novel real-life large-scale automotive parts paint shop scheduling problem, which contains color arrangement restrictions, part arrangement restrictions, bracket restrictions, and multi-objectives. Based on these restrictions, we construct exact constraints and two objective functions to form a large-scale multi-objective mixed-integer linear programming problem. To reduce this scheduling problem’s complexity, we converted the multi-objective model into a multi-level objective programming problem by combining the rule-based scheduling algorithm and the adaptive Partheno-Genetic algorithm. The rule-based scheduling algorithm is adopted to optimize color changes horizontally and bracket replacements vertically. The adaptive Partheno-Genetic algorithm is designed to optimize production based on the rule-based scheduling algorithm. Finally, we apply the model to the actual optimization problem that contained 829,684 variables and 137,319 constraints, and solved this problem by Python. The proposed method solves the optimal solution, consuming 575 s.

Model set of a valve‐controlled asymmetric hydraulic system was built, and uniform switched control (USC) strategy was proposed for multi‐model set hydraulic system. Aiming at each subsystem model, the uniform feedback linearisation control (FLC) structure was put forward based on the FLC method, and switch control strategy was used by adjusting switch gain between different sub‐models. The boundary layer function was designed in order to enhance the system robustness and to reduce oscillation which is caused by discontinuous item. Furthermore, the switch control gain was further revised according to different load condition. At last, the USC, FLC control, and proportional differential (PD) control strategy was carried out by experiment, and the results show that the maximum speed tracking error of PD and FLC control was 1.1 and 1 mm/s, respectively. The USC strategy speed error is <0.25 mm/s. Compared with the PD and the FLC, the USC was found to be more speed accuracy in multiple state hydraulic system control.