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Hypoperfusion following acute stroke is common in the infarct core and periphery tissues. The present study evaluated the efficacy of salvianolic acid (SA) on the cerebral perfusion of patients who had suffered from acute stroke using perfusion-weighted magnetic resonance imaging (PWI) to examine the blood perfusion of the affected brain tissue prior to and following treatment. Patients who were admitted to PLA 153 Central Hospital within 72 h of acute stroke symptom onset and had a Glasgow coma scale ≥5 were randomized into two groups: SA and control groups. Patients in the SA group were administered SA 0.13 g/day for 14 days. PWI was performed for all patients at admission and post-treatment. The National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS) were applied to assess neurological function at admission and 3 months post treatment. A total of 159 patients were enrolled (85 patients in the SA group and 74 patients in the control group). A total of 62 patients in the SA group and 51 patients in the control group exhibited hypoperfusion in the ipsihemisphere of the diffusion-weighted magnetic resonance imaging (DWI) lesion. In addition, relative cerebral blood volume (rCBV), a ratio of the signal value of the region of interest in the same hemisphere of the DWI lesion to that of its mirror in the PWI CBV map, decreased significantly following treatment with SA compared with the control group in patients with hypoperfusion (P=0.02), which were indicated by PWI images at admission, in the DWI lesions or the surrounding areas. Additionally, there was no significant difference in patients with normal perfusion at admission in rCBV in DWI lesions or its surrounding area between the two groups at day 15. However, a significant improvement in NIHSS (P=0.001) and mRS (P=0.005) was indicated in the SA group compared with the control at day 90. The present study indicated that SA may improve the neurological dysfunction of patients with acute stroke, which may be explained by the increased perfusion of hypoperfused brain tissues.

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An unmanned aerial vehicle (UAV) is a small, fast aircraft with many useful features. It is widely used in military reconnaissance, aerial photography, searches, and other fields; it also has very good practical-application and development prospects. Since the UAV's flight orientation is easily changeable, its orientation and flight path are difficult to control, leading to its high damage rate. Therefore, UAV flight-control technology has become the focus of attention. This study focuses on simulating a UAV's flight and orientation control, and detecting collisions between a UAV and objects in a complex virtual environment. The proportional-integral-derivative control algorithm is used to control the orientation and position of the UAV in a virtual environment. A version of the bounding-box method that combines a grid with a k-dimensional tree is adopted in this paper, to improve the system performance and accelerate the collision-detection process. This provides a practical method for future studies on UAV flight position and orientation control, collision detection, etc.

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