• Journal of Animal Science and Technology
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• v.55 no.5
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• pp.399-403
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• 2013

This study was conducted to investigate the basic concept of multiple trait effective daughter contribution (MTEDC) for dairy cattle sires and calculate effective daughter contribution (EDC) by applying a five lactation multiple trait model using milk yield test records of daughters for the Multiple-trait Across Country Evaluation (MACE). Milk yield data and pedigree information of 301,551 cows that were the progeny of 2,046 Korean and imported dairy bulls were collected from the National Agricultural Cooperative Federation and used in this study. For MTEDC approximation, the reliability of the breeding value was separated based on parents average, own yield deviation and mate adjusted progeny contribution. EDC was then calculated by lactation using these reliabilities. The average number of recorded daughters per sire by lactations were 140.57, 94.24, 55.14, 29.20 and 14.06 from the first to fifth lactation, respectively. However, the average EDC per sire by lactation using the five lactation multiple trait model was 113.49, 89.28, 73.56, 54.02 and 35.08 from the first to fifth lactation, respectively, while the decrease of EDC in late lactations was comparably lower than the average number of recorded daughters per sire. These findings indicate that the availability of daughters without late lactation records is increased by genetic correlation using the multiple trait model. Owing to the relatedness between the EDC and reliability of the estimated breeding value for sire, understanding the MTEDC algorithm and continuous monitoring of EDC is required for correct MACE application of the five lactation multiple trait model.

• Applied Biological Chemistry
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• v.39 no.1
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• pp.70-76
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• 1996

A series of the herbicidal pyridylsulfonyl areas, none substitutent, 1-(4,6-dimethoxypyrimidine-2-yl)-3-(2-pyridylsulfonyl) urea, 3 and 3-trifluoromethyl substitutent, 1-(4,6-dimethoxypyrimidine-2-yl)-3-(3-trifluoromethyl-2-pyridylsulfonyl) urea, 5(Flazasulfuron) were synthesizied and the rate of hydrolysis of their has been studied in 25%(v/v) aqueous dioxane at $45^{\circ}C$. From the results of solvent effect($m{\ll}1,\;n{\ll}3\;&\;{\mid}m{\mid}{\ll}{\mid}{\ell}{\mid}$), thermodynamic parameter (${\Delta}S^{\neq}=0.54{\sim}\;-2.19\;e.u.\;&\;{\Delta}H^{\neq}=0.025\;Kcal.mol.^{-1}$), hydrolysis product analysis, $pK_a$ constant(3: 4.9 & 5: lit.4.6) and the rate equation, a marked difference in the kinetics of the reaction of 3 and 5(Flazasulfuron) was observed. It may be concluded that the hydrolysis of 5 proceeds through the $A-S_N2Ar$ reaction via conjugate acid$(5H^+)$ below pH 7.0, whereas, above pH 9.0, the hydrolysis proceeds through irreversibly $(E_1)_{anion}$ and reversibly $(E_1CB)_R$ mechanism via conjugate base(CB), respectively. But in case of 5, $A-S_N2Ar,\;(E_1)anion\;and\;(E_1CB)_R$ mechanism involved Smile rearrangement. The mate of rearrangement of 5 to a 3-trifluoromethyl-2-pyridylpyrimidinyl urea(PPU) in acid and 3-trifluoromethyl-2-pyridyl-4.6-dimethoxypyridinyl amine (PPA) in base was increased about 3.5 times by the introduction of trifluoromethyl group in the 3-position on the 2-pyridyl ring. From the basis of these findings, a possible mechanism for the hydrolysis of 5 was proposed and discussed.

• Journal of radiological science and technology
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• v.8 no.2
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• pp.47-63
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• 1985

This paper was aimed to study the effects of Cobalt-60 gamma ray irradiation on Albino rat blood cells and the activity of enzymes were measured using blood cell auto analyzer (Cell-Dyn 900) and enzyme autoanalyzer (Gilford 3500) respectively. Cobalt-60 gamma rays those are grouped into 200R, 400R, 600R, 800R, 1,000R, 1,200R, 1,300R, 1,400R, 1,500R and 1,600R to the rats of male and female and measured the numeral varieties of blood corpuscles of the rats and the active varieties of enzyme of acid, alkaline phosphatase (ACP, ALP), lactic acid dehydrogenase (LDH), glutamic oxaloacetic transaminase (GOT) and glutamic pyruvic transaminase. (GPT) those came out after 1, 3, 5 or 7 days. The results are summarized as follows: 1. In both case of male and female, the numeral varieties of the erythrocytes, in the 200R group of irradiation showed the minimum value in the 3 days group and a tendency of increase in the 5 and 7 days groups, while the numeral varieties of the leucocytes in every groups of irradiation showed a tendency of a rapid decrease after a day. The numeral varieties of the blood platelet in both case of male and female didn't show generally any great change in a day and 3 days groups, but showed a rapid decreasing appearance after the 5 days. 2. In both case of male and female, the activities of ACP were on the decrease gradually after 3 days of the irradiation and the activities of ALP were on the decrease after 5 days. Similarly in both case of mate and female, the activities of LDH showed the decrease after 3 and 5 days, and the phenomenous of GOT showed an appearance of increase in a day, but decreased after 3 days. As for the GPT activities couldn't find any great change in the male rats in comparison with the control groups, but in the female rats a tendency of the increase in 600R, 800R, 1,000R groups after 3 days. 3. In the case of the irradiation of high quantity of ray more than 1,200R, all rats died after 4 days, and by the irradiation of 1,600R all rats died after 3 days, and it showed the sensitive response of a living body to the irradiation of high quantity.

• Analytical Science and Technology
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• v.8 no.3
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• pp.321-334
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• 1995

Basic studies for the effective extraction of ammonium pyrrolidine dithiocarbamate(APDC) complexes of Co(II), Ni(II) and Cu(II) into a solvent have been performed. The maximum distribution ratio was appeared (log D=1.3543) at pH 2.0 and the partition coefficient was 2.489 in the extraction of $4{\times}10^{-5}M$ APDC itself into chloroform. From the UV/visible spectra of metal-chelates in aqueous and organic solutions, the pH to form stable 1:2 metal-ligand complexes were Co(II):5.0, Ni(II):8.0 and Cu(II):8.0, respectively and only 1 minute was enough to be partitioned into the chloroform. Besides, the partition and extraction equilibria of the complexes were investigated by back-extracting $10.0{\mu}g/ml$ metal-chelates from the solvent into an aqueous solution beacuse of their slight solubilities in the aqueous solution. The distribution coefficients and extractabilities were as follows : at pH 6.5~8.5 of the aqueous solution, log D=2.834 : E(%)=99.9% for $Co(PDC)_2$, at pH 11, log D=5.699 E%=100 for $Ni( PDC)_2$, and at pH 6.0, log D=2.025 : E(%)=99.1% for $Cu(PDC)_2$. And the extraction and formation constants were log $K_{ex}=9.671$ : log ${\beta}_2=6.938$ for $Co(PDC)_2$, log $K_{ex}=9.646$ : log ${\beta}_2=7.071$ for $Ni( PDC)_2$, and log $K_{ex}=9.074$ : log ${\beta}_2=7.049$ for $Cu(PDC)_2$, respectively. From these results, an optimum extraction procedure can be constructed for the separative concentration of trace metallic ions, and the quantitative determination of them in advanced materials and environmental samples will be expected without any influence of sample matrixes.

• 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.