Under the epidemic, closed management has turned a large number of communities into lonely islands, and the contactless delivery method of UAV has become the rigid demand in this special period. This paper studies a collaborative system of multi‐UAV multitruck transportation, which can deliver emergency materials such as medicine to remote areas or closed communities. In this system, delivery tasks are assigned to multiple trucks and multiple drones on each truck can perform delivery tasks in parallel, thereby improving delivery efficiency. We study the routing problem of this system specifically for medical supplying road network and establish mixed‐integer model and hybrid algorithm. We show by experiments that the number of trucks has more significant impact on the optimal solution than the number of drones and the performance of hybrid particle swarm optimization is better than the performance of the other algorithms.

Objective: To evaluate the effects of transcutaneous electrical acupoint stimulation (TEAS) on upper limb motor recovery during post-stroke rehabilitation. Design: Single-blind, randomized controlled trial. Setting: Four inpatient rehabilitation facilities. Subjects: A total of 204 stroke patients with unilateral upper limb motor impairment were randomly 1:1 allocated to TEAS or sham TEAS group. Baseline demographic and clinical characteristics were comparable between the two groups. Interventions: Both groups received conventional physical and occupational therapies. TEAS and sham TEAS therapy were administered to two acupoints (LI10 and TE5) with a pulse duration of 300 µs at 2 Hz on the affected forearm for 30 times over 6 weeks. Outcome measures: The upper-extremity Fugl-Meyer score (primary outcome), manual muscle testing, modified Ashworth scale, Lindmark hand function score, and Barthel index were evaluated by blinded assessors at baseline, 2, 4, 6, 10, and 18 weeks. Results: The number of patients who completed the treatment was 99 and 97 in the TEAS and the sham group. No significant between-group difference was found in the Upper-Extremity Fugl-Meyer score, Modified Ashworth Scale, Lindmark hand function score, and Barthel Index after intervention and during follow-up. However, the TEAS group exhibited 0.29 (95% CI 0.02 to 0.55) greater improvements in Manual Muscle Testing of wrist extension than the sham group ( p = 0.037) at 18 weeks. Conclusions: Administration of TEAS therapy to hemiplegic forearm could not improve the upper extremity motor recovery. However, TEAS on the forearm might provide potential benefits for strength improvement of the wrist

Corporate social responsibility (CSR) is the concrete practice of sustainable development at the enterprise level, emphasizing the human value in the production process. The proposal of Industry 5.0 begins to take the coordinated development between human and various production factors as one of the key points of corporate sustainable management. Therefore, this paper studies the optimization of medical enterprise’s operations management considering enterprise CSR under Industry 5.0. A mixed-integer programming (MIP) model is developed to maximize the CSR with the consideration of the impact of precision medical technologies such as surgical robots (SRs) and 3D bone printing on employee social welfare, corporate profits, social environment, and customer surplus value. An improved variable neighborhood tabu search (IVNTS) algorithm which combines the variable neighborhood tabu search (VNTS) algorithm and simulated annealing (SA) algorithm is designed to solve the model, and numerical experiments are analyzed to verify the effectiveness of the proposed IVNTS. The research aids medical enterprise to make reasonable operations management decisions, while providing a reference for the government to draft and implement related policies, thereby achieving sustainable social development.

Early rehabilitation with the right intensity contributes to the physical recovery of stroke survivors. In clinical practice, physicians determine whether the training intensity is suitable for rehabilitation based on patients’ narratives, training scores, and evaluation scales, which puts tremendous pressure on medical resources. In this study, a lightweight facial expression recognition algorithm is proposed to diagnose stroke patients’ training motivations automatically. First, the properties of convolution are introduced into the Vision Transformer’s structure, allowing the model to extract both local and global features of facial expressions. Second, the pyramid-shaped feature output mode in Convolutional Neural Networks is also introduced to reduce the model’s parameters and calculation costs significantly. Moreover, a classifier that can better classify facial expressions of stroke patients is designed to improve performance further. We verified the proposed algorithm on the Real-world Affective Faces Database (RAF-DB), the Face Expression Recognition Plus Dataset (FER+), and a private dataset for stroke patients. Experiments show that the backbone network of the proposed algorithm achieves better performance than Pyramid Vision Transformer (PvT) and Convolutional Vision Transformer (CvT) with fewer parameters and Floating-point Operations Per Second (FLOPs). In addition, the algorithm reaches an 89.44% accuracy on the RAF-DB dataset, which is higher than other recent studies. In particular, it obtains an accuracy of 99.81% on the private dataset, with only 4.10M parameters.

We consider the nonlinear wave equations in four-dimensional mutisymplectic formulation. The two equivalent mutisymplectic numerical methods are used to do the numerical comparison: one is the multisymplectic box scheme based on four-dimensional multisymplectic formulation; the other is the equivalent method which is derived by eliminating the medium variables from the multisymplectic box scheme. The numerical results show that the first one is more accurate than the second one in computing the local conservative quantities. For the linear wave equation, the local energy and momentum can be preserved up to round error by the first numerical method and we have proved the stability of the two equivalent numerical methods.