The phenomenon of PTG of stroke patients in hospital existed, but it was at a low level. Stroke survivors with a higher level of rumination, social support, and a university level education had a higher level of PTG.

Background: With the rapid aging of the population, the issue of driving by dementia patients has been causing increasing concern worldwide. Objective: To investigate the driving difficulties faced by senior drivers with cognitive impairment and identify the specific neuropsychological test that can reflect specific domains of driving maneuvers. Methods: Senior drivers with cognitive impairment were investigated. Neuropsychological tests and a questionnaire on demographic and driving characteristics were administered. Driving simulator tests were used to quantify participants’ driving errors in various domains of driving. Results: Of the 47 participants, 23 current drivers, though they had better cognitive functions than 24 retired drivers, were found to have impaired driving performance in the domains of Reaction, Starting and stopping, Signaling, and Overall (wayfinding and accidents). The parameters of Reaction were significantly related to the diagnosis, and the scores of MMSE, TMT-A, and TMT-B. As regards details of the driving errors, “Sudden braking” was associated with the scores of MMSE (ρ= –0.707, p <  0.01), BDT (ρ= –0.560, p <  0.05), and ADAS (ρ= 0.758, p <  0.01), “Forgetting to use turn signals” with the TMT-B score (ρ= 0.608, p <  0.05), “Centerline crossings” with the scores of MMSE (ρ= –0.582, p <  0.05) and ADAS (ρ= 0.538, p <  0.05), and “Going the wrong way” was correlated with the score of CDT (ρ= –0.624, p <  0.01). Conclusion: Different neuropsychological factors serve as predictors of different specific driving maneuvers segmented from driving performance.

The positioning accuracy of industrial robots has an important influence on the stability and accuracy of robotic motion, which is one of the important indexes to measure the performance of robots. At present, some probability theory based methods are used to evaluate the positioning accuracy reliability of industrial robots. In practical engineering, the precise probability distribution of some robot's parameters cannot be obtained directly. This study firstly uses the aleatory-epistemic hybrid model to describe the uncertain parameters of industrial robots. Secondly, the uncertain parameters are considered to construct the kinematic equation of industrial robots. Thirdly, a probability-evidence hybrid reliability analysis model of industrial robots is established. Finally, the reliability interval of industrial robots under different thresholds can be obtained. Compared with the traditional method, the reliability results of industrial robots obtained by this method is an interval, which can more objectively evaluate the kinematics reliability of industrial robots. In the example, the effectiveness of the proposed method is verified by a six degrees of freedom industrial robot.