This study investigated the effects of oligonol, a low-molecular-polyphenol derived from lychee peel, against diabetes-induced pancreatic damage via oxidative stressinduced inflammation. Oligonol was orally administered at 10 or 20 mg/kg body weight/day for 10 days to streptozotocin-induced diabetic rats, and the rats were compared with nondiabetic and diabetic control rats. The diabetic rats showed loss of body weight and increased pancreatic weight, and the oral administration of oligonol attenuated these parameters. Moreover, the administration of oligonol caused a significant decrease in the serum glucose level and a significant increase in the serum and pancreatic insulin and C-peptide levels in the diabetic rats. Oligonol also significantly reduced the enhanced levels of reactive oxygen species and 2-thiobarbituric acid reactive substance, which are oxidative stress biomarkers, in the serum and pancreas. Oligonol treatment reduced the overexpression of phospho-p38, phospho-ERK1/2, phospho-inhibitor of nuclear factor-kappa B (NF-κB), NF-κBp65, and NF-κBp65-induced inflammatory protein such as cyclooxygenase-2, inducible nitric oxide synthase, tumor necrosis factor-α, and interleukin-6. Furthermore, oligonol treatment led to significantly attenuated histological damage in the pancreas.On the basis of these results, we conclude that a plausible mechanism of oligonol's antidiabetic action may be its antioxidative stress-related anti-inflammatory action.
This paper handles with detection of leaf diseases using deep learning networks which have learned the color and shape parameters of leaf diseases. This paper considers the color distribution and shape information of leaf diseases, and exploits two deep leaning networks in training the normal leaves and diseases. The input color image is partitioned into small segments using color clustering, and the color information of each segment is inspected by the Color Network. When a segment is determined as abnormal (that is, disease segment), the shape parameters of the segment are inspected by Shape Network to classify the disease types. This paper uses HSV color space for Color Network and proposes 24 parameters for Shape Network such as boundary length ratio, densities of subregions, correlation coefficients of x-y coordinates in the disease segments. According to the experiments with three types of diseases (type A, B, C) for images of iceberg, strawberry, coffee, sunflower, chinar, blackgram, citrus, and apple leaves images, leaf diseases are detected with 97.9% recall for a segment unit and 99.3% recall for an input image where there are more than two disease segments.
The purpose of this study is to analyse the occurrence and evolution of Mao suit which is important position in the modern costume history of China and to provide a source of design inspiration to contemporary fashion designers. In the research method, literature review and case studies was conducted in parallel. For the literature review, changes of Mao suit in each age were reviewed with reference to the related documents, Chinese costume and cultural history, prior research papers and internet resources. The case analysis was qualitatively done focusing on the silhouette, color and detail of clothes in fashion collections.
Most public guide robots installed in public spots such as exhibition halls and lobbies of department store etc., have poor capability to distinguish the users who require services. As to provide suitable services, public guide robots should have a human detection system that makes it possible to evaluate intention of customers from their movement direction. In this paper, a DPS (Directional Perception System) is realized based on face detection technology. In particular, to catch human movement efficiently and reduce computational time, human detection technology using face rectangle, which is obtained from the human face, is developed. DPS determines which customer needs services of public guide robots by investigating the size and direction of face rectangle. If DPS is adapted, guide service will be provided with more satisfaction and reliability, and power efficiency also can be added up because public guide robots provide services only for the users who expresses their intentions of wanting services explicitly. Finally, through several experiments, the feasibility of the proposed DPS is verified.
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