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Abstract Background Neoadjuvant chemotherapy (NAC) for locally advanced gastric and gastroesophageal junction adenocarcinoma (LAGC) has been recommended in several guidelines. However, there is no global consensus about the optimum of NAC regimens. We aimed to determine the optimal NAC regimen for LAGC. Methods A systematic review and Bayesian network meta-analysis was performed. The literature search was conducted from inception to June 2022. The odds ratio (OR) value and 95% confidence interval (95% CI) were used for assessment of R0 resection rate and pathological complete response rate (pCR) as primary outcomes. The hazard ratio (HR) value and 95% CI were interpreted for the assessment of overall survival (OS) and disease-free survival (DFS) as second outcomes. The risk ratio (RR) value and 95% CI were used for safety assessment. Results Twelve randomized controlled trials were identified with 3846 eligible participants. The network plots for R0 resectability, OS, and DFS constituted closed loops. The regimens of TPF (taxane and platinum plus fluoropyrimidine), ECF (epirubicin and cisplatin plus fluorouracil), and PF (platinum plus fluoropyrimidine) showed a meaningful improvement of R0 resectability, as well as OS and/or DFS, compared with surgery (including surgery-alone and surgery plus postoperative adjuvant chemotherapy). Importantly, among these regimens, TPF regimen showed significant superiority in R0 resection rate (versus ECF regimen), OS (versus ECF regimen), DFS (versus PF and ECF regimens), and pCR (versus PF regimen). Conclusions The taxane-based triplet regimen of TPF is likely the optimal neoadjuvant chemotherapy regimen for LAGC patients.

The present paper presents a newly designed dexterous mobile parallel mechanism for fusion reactor vacuum vessel assembly, the robot system has advantages in terms of compact design, the capability to carry out heavy-duty machining tasks, evacuation, and has less space occupation compared to other robot systems in existence. Despite different robot systems are studied in the fusion reactor, there is still a lack of research on mechanism development for vacuum vessel assembly, which is attractive to future fusion reactors. In the fusion reactor, the robot systems will carry out different tasks, such as welding and machining. The assembly tasks of the vacuum vessel will be performed from inside of the vacuum vessel on-site. Then the paper introduces the single-objective and multi-objective optimization design of the proposed mechanism, the optimized objective is considered to be a combination of parallel mechanism dynamic machining force, dexterity, stiffness, and workspace volume. The design variables are derived from the geometry of the fixed and movable platforms, which include mass, inertia, the sizes of the platforms, and distances between universal joints located on the platforms. In the multi-objective optimization, non-dominated sorting genetic algorithm II is adopted and different trajectories are designed to simulate the machining process, which further turns the local optimization problem into a global optimization problem. Finally, the optimized results are extracted and analyzed. Simulation results indicate the effectiveness of the proposed multi-objective optimization approaches and multi-objective optimization is found to be more reliable than single-objective optimization.

The hybrid kinematic mechanism (HKM) as an alternative remote handling subsystem of the Demonstration Fusion Power Plant (DEMO) breeding blanket (BB) is undergoing extensive theoretical analysis and feasibility verification. In this paper, the forward and inverse kinematic models of the HKM are derived by combining the Newtonian iterative method and the analytical method. Cartesian space trajectory planning is designed based on the trajectories of the HKM lifting of inboard and outboard BBs. The continuous smooth inverse kinematic solutions in the HKM joint space are obtained based on the polynomial interpolation method. For the characteristics of the HKM piston thread driving, the end-effector position error caused by the degradation of the spherical joint into a universal joint is analyzed and calculated. During the lifting of the left inboard BB, there is a maximum absolute error ∆P = 3.1 mm, and as the error continues to expand to the bottom of the BB it causes a risk of collision. Combining the overall effects of driving control, rigid–flexible coupling, etc., on position accuracy, an open-loop variable parameter error compensation plan based on the Levenberg–Marquardt (LM) nonlinear damping least-squares algorithm is proposed and validated in this paper. The simulation results show that the maximum absolute error after compensation is less than 1 mm as the mesh density increases, and the absolute position accuracy can be further improved by local mesh encryption. This study verifies the feasibility of the HKM as a BB remote handling subsystem and provides an option for high-precision control of the HKM.

This study aimed to discuss the research efforts in developing virtual reality (VR) technology for different training applications. To begin with, we describe how VR training experiences are typically created and delivered using the current software and hardware. We then discuss the challenges and solutions of applying VR training to different application domains, such as first responder training, medical training, military training, workforce training, and education. Furthermore, we discuss the common assessment tests and evaluation methods used to validate VR training effectiveness. We conclude the article by discussing possible future directions to leverage VR technology advances for developing novel training experiences.

The vacuum vessel (VV) inside and outside inspection of the Demonstration Fusion Power Plant (DEMO) is very difficult due to various constraints, such as non-magnet effect material requirements, constrained space, and neutrons on its surfaces. We propose a design method for wall-climbing mobile robots (WMR) based on the vortex principle and investigate key technologies to meet VV inspection requirements. We developed a kinematic model based on the robot’s motion control requirements and a trajectory tracking control algorithm according to the tractrix principle, enabling the robot to follow the path for autonomous inspection. The impeller is designed based on the vortex principle. The aerodynamic characteristics and structural strength of the impeller were also analysed and optimised. A sliding-mode robust pressure control system was designed for the robot’s negative pressure adsorption, and its effectiveness was verified by simulation. Finally, an initial test prototype verified the structural design and vortex adsorption performance. We also addressed the potential applications of the WMR in DEMO and other fusion reactors.