This research examines deep learning based image recognition models for beef sirloin classification. The sirloin of beef can be classified as the upper sirloin, the lower sirloin, and the ribeye, whereas during the distribution process they are often simply unified into the sirloin region. In this work, for detailed classification of beef sirloin regions we develop a model that can learn image information in a reasonable computation time using the MobileNet algorithm. In addition, to increase the accuracy of the model we introduce data augmentation methods as well, which amplifies the image data collected during the distribution process. This data augmentation enables to consider a larger size of training data set by which the accuracy of the model can be significantly improved. The data generated during the data proliferation process was tested using the MobileNet algorithm, where the test data set was obtained from the distribution processes in the real-world practice. Through the computational experiences we confirm that the accuracy of the suggested model is up to 83%. We expect that the classification model of this study can contribute to providing a more accurate and detailed information exchange between suppliers and consumers during the distribution process of beef sirloin.
As a sensor of cellular energy status, AMP-activated protein kinase (AMPK) plays an important role in the pathophysiology of diabetes and its complications. Because AMPK is also expressed in podocytes, podocyte AMPK would be an important factor contributing to development of podocyte injury. We investigated the roles of AMPK in the pathological changes of podocyte synaptopodin induced by angiotensin II (Ang II), a major injury inducer. Mouse podocytes were incubated in media containing various concentrations of Ang II and AMPK-modulating agents, and the changes of synaptopodin were analyzed by confocal imaging and Western blotting. Ang II and compound C, an AMPK inhibitor, concentrated and re-localized synaptopodin from peripheral cytoplasm to the internal cytoplasm portion in podocytes. Ang II also reduced synaptopodin protein and mRNA, which were reversed by metformin and 5-aminoimidazole-4-carboxamide ribonucleoside. Losartan, an Ang II type 1 receptor antagonist, also recovered synaptopodin mRNA, which was suppressed by Ang II. We suggest that Ang II induces the relocation and suppression of podocyte synaptopodin by suppression of AMPK and via Ang II type 1 receptor, which would be an important mechanism in Ang II-induced podocyte phenotypical changes.
This study was carried out to find a useful mushroom at Chungnam Agricultural Research And Extention Service. Twenty materials used were collected from domestic and exotic area. These races were compared bontanical characteristics to leading varieties by PCR-RAPD methods. Mycelial growth temperature of Chongpung and Myongwol were at 20 to 25 ℃ and 25 to 30 ℃ at PDA medium, respectively mycelial growth of these varieties were similiar at pH 6.5 to 7.5. In case of mushroom cultivation temperature ranges, Chongpung was at 5 to 26℃ and Myongwol was at 7 to 28℃, but the optimum temperature range of these were appeared at 15 to 19℃. Culture temperature of these was 23℃ and period of mycelial culture was needed 23 to 24 days under 850cc/pp, while was needed 11 to 12 days at waste cotton medium. Cap color of these at first inducing mushroom was all dark blue, but at late growing stages Chongpung was shown as grey, and Myongwol was shown as dark grey. Yield of Chongpung was appeared as 46kg/3.3m2 and that of Myongwol was 41kg /3.3m2, while Chunchu No2 as check was 40kg/3.3m2. Results from PDA medium and PCR-RAPD analysis two of these were different from others.