• Journal of Conservation Science
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• v.37 no.6
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• pp.723-737
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• 2021

This study analyzed the composition and structure of materials with Buddhist paper scriptures excavated from architectural sites in 'Sum Tolgoi' of the 17^th century and carried out conservation treatment base on the result of the analysis. The scriptures were covered in dust and foreign sub stances, and were so crumpled that it was impossible to identify the form. The damage, loss, and discoloration have been identified. Buddhist scriptures written in Tibetan used indigo and ink sticks on paper as a result of UV-Vis analysis, and ink sticks as black character materials from scriptures written ancient Mongolian. SEM-EDS and Micro-XRF analyses revealed that the outlines were drawn with red lines using a mix of Minium (Pb₃O₄) and Cinnabar (HgS), or Cinnabar (HgS) alone, and the contents of the scriptures were written with silver paint. Silver chloride (AgCl) and Calcium (Ca) were identified in the silver paint component of the characters, while Calcium and Orpiment (As₂S₃) were identified in the yellow lines. Concerning the paper ground, Buddhist scriptures written in ancient Mongolian were characterized by herbal plant fiber and bast fiber, and those written in Tibetan, by bast fiber. Radiocarbon dating indicates that the paper for the scriptures was produced between the 15^th and 17^th centuries. Conservation treatment of the scriptures was carried out based on the experiment on the production of pre-coated paper and how to coat that to prevent the second damage due to the deformation and fragility of the excavated paper. The scriptures were preserved and mounted, and a neutral box was made to identify the contents of the scriptures recorded on both sides after the treatment. This conservation treatment is the result of a study that applied new conservation treatment materials and methods according to the principle of conservation treatment reversibility.

• Journal of Nutrition and Health
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• v.41 no.8
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• pp.701-710
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• 2008

The wild simulated ginseng (WSG) has been effectively used in folk medicine as a remedy against hepatic disease, hypertension and arthritic disease. However, there is still lack of scientific proof about its antioxidant capability. The present study has been conducted to evaluate the protective role of the WSG ethanol extract in the CCl4-induced oxidative stress and resultant hepatic disfunction in ICR mice. The electron donating abilities and IC50 of WSG etnanol extract were 76.86 ${\pm}$ 1.06% and 33.3 ${\mu}g$/mL (that of ascobic acid was 16.5 ${\mu}g$/mL), respectively. Total antioxidant status of WSG extract was 2.13 ${\pm}$ 0.06 mmoL/mg, while the values of ascorbic acid and BHT were 3.63 ${\pm}$ 0.06 and 3.12 ${\pm}$ 0.02, respectively. ICR mice (aged 3weeks) were fed for 4 weeks on AIN-93M diet and had free access to food and water. The animals were divided into three groups: normal group (intraperitoneally (i.p) injected with PBS at 100 ${\mu}L$/mouse), group C; CCl4-induced and without any treatment. (i.p injected only PBS, 100 ${\mu}L$ /mice), group G; CCl4-induced and treated with WSG (i.p injected with 5 mg WSG extract per mouse, suspended in 100 ${\mu}L$ phosphate buffer). After the i.p. injection of WSG or PBS (5 times for 7weeks), all mice were administered CCl4 in olive oil at the last day of the experiment, except for normal group. The normal group was administered only olive oil. Determination of plasma triglyceride, total cholersterol, fasting glucose and GPT activity was performed using automatic blood analyzer. To evaluate the protective effect against the oxidative stress, DNA fragmentation and TBARS were determined in blood leucocytes and RBC and hepatocyte, respectively. Body and organs weights and food intake did not show significant differences among the groups. Blood total cholesterol of group G was similar to that of normal group, which was the lowest in group C. The fasting blood glucose level was the highest in normal group (205.20 ${\pm}$ 135.24), which were decreased in group C (134.2 ${\pm}$ 79.31) and group G (126.48 ${\pm}$ 77.05). TBARS values in a red blood cell and hepatic tisuue homogenate were lower in group G comparing to the group C. DNA% in tail, tail length (TL) and tail moment (TM) of blood leucoocytes showed the highest values in group C (20.11 ${\pm}$ 2.47, 17.36 ${\pm}$ 2.58, 94.11 ${\pm}$ 12.29) and they were significantly diminished in group G (9.63 ${\pm}$ 1.19, 7.04 ${\pm}$ 1.50, 38.64 ${\pm}$ 7.60). In conclusion, wild simulated ginseng might be a protective agent against the oxidative stress.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.