The superposition of ultraviolet radiation induced (photodamage) aging process is photoaging. Antioxidant peptides derived from Pinctada fucata protein as raw materials were smeared the back of light-aging. The effect of antioxidant peptides on wrinkle generating, skin restoration capacity after pulled up and measure the active of the superoxide dismutase (SOD), catalase (CAT), hydroxyproline, and glutathione peroxidase (GSH-Px) and lipid peroxidation by kit and histological examination of UVB-irradiated skin that the mitotic index of basal cells, the thickness ratio of the epidermis and dermis, fibroblast count, density of collagen fibers and volume density of dermal microvasculature were studied. The result showed that antioxidant peptides had slowed down the progress of wrinkles formation and skin elasticity deceasing induced by acute irradiation of UVB. It also significantly controlled the speed of lipid peroxidation and the reduction of the activity of SOD, GSH-Px, hydroxyprodline and CAT. Histopathological studies showed that the derived antioxidant peptides could reduce the thickness ratio of the dermis and epidermis and increase the mitotic index of basal cells, fibroblast count, density of collagen fibers and volume density of dermal microvascular, these outcomes confirmed the protective role of antioxidant peptides in the process of photoaging. 相似文献
When multiple mobile robots cooperatively explore an unknown environment, the advantages of robustness and redundancy are guaranteed. However, available traditional economy approaches for coordination of multi-robot systems (MRS) exploration lack efficient target selection strategy under a few of situations and rely on a perfect communication. In order to overcome the shortages and endow each robot autonomy, a novel coordinated algorithm based on supervisory control of discrete event systems and a variation of the market approach is proposed in this paper. Two kinds of utility and the corresponding calculation schemes which take into account of cooperation between robots and covering the environment in a minimal time, are defined. Different moving target of each robot is determined by maximizing the corresponding utility at the lower level of the proposed hierarchical coordinated architecture. Selection of a moving target assignment strategy, dealing with communication failure, and collision avoidance are modeled as behaviors of each robot at the upper level. The proposed approach distinctly speeds up exploration process and reduces the communication requirement. The validity of our algorithm is verified by computer simulations. 相似文献
Understanding scene image includes detecting and recognizing objects, estimating the interaction relationships of the detected objects, and describing image regions with sentences. However, since the complexity and variety of scene image, existing methods take object detection or vision relationship estimate as the research targets in scene understanding, and the obtained results are not satisfactory. In this work, we propose a Multi-level Semantic Tasks Generation Network (MSTG) to leverage mutual connections across object detection, visual relationship detection and image captioning, to solve jointly and improve the accuracy of the three vision tasks and achieve the more comprehensive and accurate understanding of scene image. The model uses a message pass graph to mutual connections and iterative updates across the different semantic features to improve the accuracy of scene graph generation, and introduces a fused attention mechanism to improve the accuracy of image captioning while using the mutual connections and refines of different semantic features to improve the accuracy of object detection and scene graph generation. Experiments on Visual Genome and COCO datasets indicate that the proposed method can jointly learn the three vision tasks to improve the accuracy of those visual tasks generation.