• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.105-111
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• 2021

Rice lodging is an annual occurrence caused by typhoons accompanied by strong winds and strong rainfall, resulting in damage relating to pre-harvest sprouting during the ripening period. Thus, rapid estimations of the area of lodged rice are necessary to enable timely responses to damage. To this end, we obtained images related to rice lodging using a drone in Gimje, Buan, and Gunsan, which were converted to 128 × 128 pixels images. A convolutional neural network (CNN) model, a deep learning model based on these images, was used to predict rice lodging, which was classified into two types (lodging and non-lodging), and the images were divided in a 8:2 ratio into a training set and a validation set. The CNN model was layered and trained using three optimizers (Adam, Rmsprop, and SGD). The area of rice lodging was evaluated for the three fields using the obtained data, with the exception of the training set and validation set. The images were combined to give composites images of the entire fields using Metashape, and these images were divided into 128 × 128 pixels. Lodging in the divided images was predicted using the trained CNN model, and the extent of lodging was calculated by multiplying the ratio of the total number of field images by the number of lodging images by the area of the entire field. The results for the training and validation sets showed that accuracy increased with a progression in learning and eventually reached a level greater than 0.919. The results obtained for each of the three fields showed high accuracy with respect to all optimizers, among which, Adam showed the highest accuracy (normalized root mean square error: 2.73%). On the basis of the findings of this study, it is anticipated that the area of lodged rice can be rapidly predicted using deep learning.

• Journal of IKEEE
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• v.27 no.1
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• pp.116-121
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• 2023

In this paper, we develop a deep learning structure for a complex microbial incubator that applies deep learning prediction result information. The proposed complex microbial incubator consists of pre-processing of complex microbial data, conversion of complex microbial data structure, design of deep learning network, learning of the designed deep learning network, and GUI development applied to the prototype. In the complex microbial data preprocessing, one-hot encoding is performed on the amount of molasses, nutrients, plant extract, salt, etc. required for microbial culture, and the maximum-minimum normalization method for the pH concentration measured as a result of the culture and the number of microbial cells to preprocess the data. In the complex microbial data structure conversion, the preprocessed data is converted into a graph structure by connecting the water temperature and the number of microbial cells, and then expressed as an adjacency matrix and attribute information to be used as input data for a deep learning network. In deep learning network design, complex microbial data is learned by designing a graph convolutional network specialized for graph structures. The designed deep learning network uses a cosine loss function to proceed with learning in the direction of minimizing the error that occurs during learning. GUI development applied to the prototype shows the target pH concentration (3.8 or less) and the number of cells (10⁸ or more) of complex microorganisms in an order suitable for culturing according to the water temperature selected by the user. In order to evaluate the performance of the proposed microbial incubator, the results of experiments conducted by authorized testing institutes showed that the average pH was 3.7 and the number of cells of complex microorganisms was 1.7 × 10⁸. Therefore, the effectiveness of the deep learning structure for the complex microbial incubator applying the deep learning prediction result information proposed in this paper was proven.

• Journal of Chest Surgery
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• v.39 no.8 s.265
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• pp.588-597
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• 2006

Background: The surgical repair of a tetralogy of Fallot (TOF) has been performed successfully with a favorable early and late outcome. However, the later development of pulmonary regurgitation and stenosis remains a problem. The development of pulmonary regurgitation and stenosis may be changed by the size of right ventricular outflow tract (RVOT) reconstruction at the initial total correction. Hence, it is necessary to investigate the ideal size of RVOT reconstruction. Material and Method: This prospective study was carried out to determine how a surgical strategy and the RVOT size affect the occurrence of pulmonary regurgitation and stenosis. From January 2002 to December 2004, 62 patients underwent the TOF total correction. The RVOT size (diameter of pulmonary valve annulus) of each case was measured after the RVOT reconstruction and converted to a Z value. A pre-scheduled follow up (at discharge, 6 months, 1 year, 2 years and 3 years) was carried out by echocardiography to evaluate the level of pulmonary regurgitation and stenosis. Result: The patients were divided to two groups (transannular group n=12, nontransannular group n=50) according to the method of a RVOT reconstruction. The Z value of RVOT=iameter of pulmonary valve annulus) (transannular group -1, $range\;-3.6{\sim}-0.8;$ nontransannular group -2.1, $range\;-5.2{\sim}-1.5)$ and the average pRV/LV after surgery ${(transannular group 0.44{\pm}0.09,\;nontransannular group\;0.42{\pm}0.09)}$ did not show any significant difference between two groups. The occurrence of pulmonary regurgitation above a moderate degree was more frequent in the transannular group (p<0.01). In nontransannular group, the development of pulmonary regurgitation more than moderate degree occurred to the patients with larger RVOT size (Z value>0, p<0.02) and the progressing pulmonary stenosis more than mild to moderate degree developed in the patients with smaller RVOT size (Z value<-1.5, p<0.05). A moderate degree of pulmonary stenosis developed for 4 nontransannular patients. Three underwent additional surgery and one underwent a balloon valvuloplasty. Their Z value of RVOT were -3.8, -3.8 -2.9, -1.8, respectively. Conclusion: When carring out a TOF total correction, transannular RVOT reconstruction group has significantly more pulmonary regurgitation. In the nontransannular RVOT reconstruction. the size of the RVOT should be maintained from Z value -1.5 to 0. If the Z value is less than -1.5, we should follow up carefully for the possibility of pulmonary stenosis.

• Tuberculosis and Respiratory Diseases
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• v.58 no.1
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• pp.31-42
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• 2005

Background : Peroxiredoxins (Prxs) are a relatively newly recognized, novel family of peroxidases that reduce $H_2O_2$ and alkylhydroperoxide into water and alcohol, respectively. There are 6 known isoforms of Prxs present in human cells. Normally, Prxs exist in a head-to-tail homodimeric state in a reduced form. However, in the presence of excess $H_2O_2$, it can be oxidized on its catalytically active cysteine site into inactive oxidized forms. This study surveyed the types of the Prx isoforms present in the pulmonary epithelial, macrophage, endothelial, and other cell lines and observed their response to oxidative stress. Methods : This study examined the effect of exogenous, excess $H_2O_2$ on the Prxs of established cell lines originating from the pulmonary epithelium, macrophages, and other cell lines, which are known to be exposed to high oxygen partial pressures or are believed to be subject to frequent oxidative stress, using non-reducing SDS polyacrylamide electrophoresis (PAGE) and 2 dimensional electrophoresis. Result : The addition of excess $H_2O_2$ to the culture media of the various cell-lines caused the immediate inactivation of Prxs, as evidenced by their inability to form dimers by a disulfide cross linkage. This was detected as a subsequent shift to its monomeric forms on the non-reducing SDS PAGE. These findings were further confirmed by 2 dimensional electrophoresis and immunoblot analysis by a shift toward a more acidic isoelectric point (pI). However, the subsequent reappearance of the dimeric Prxs with a comparable, corresponding decrease in the monomeric bands was noted on the non-reducing SDS PAGE as early as 30 minutes after the $H_2O_2$ treatment suggesting regeneration after oxidation. The regenerated dimers can again be converted to the inactivated form by a repeated $H_2O_2$ treatment, indicating that the protein is still catalytically active. The recovery of Prxs to the original dimeric state was not inhibited by a pre-treatment with cycloheximide, nor by a pretreatment with inhibitors of protein synthesis, which suggests that the reappearance of dimers occurs via a regeneration process rather than via the de novo synthesis of the active protein. Conclusion : The cells, in general, appeared to be equipped with an established system for regenerating inactivated Prxs, and this system may function as a molecular "on-off switch" in various oxidative signal transduction processes. The same mechanisms might applicable other proteins associated with signal transduction where the active catalytic site cysteines exist.