• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.158-169
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• 2019

Ergot alkaloids are mycotoxin produced by fungi of the Claviceps genus, mainly by Claviceps purpurea in EU. Recently obtained informations indicates necessity for control the ergot in imported grains. Recent occurrence data of ergot alkaloids from EU countries indicate the necessities of management and control these toxins from the imported grains like rye, wheat, oat etc. The aim of this study is to optimize the liquid chromatography-tandem mass spectrometry method for determination of ergot alkaloids (ergometrine, ergosine, ergotamine, ergocornine, ergocryptine, ergocristine and their epimers (-inines) from grain and grain-based food. The test method was optimized by extracting the sample with acetonitrile containing 2 mM ammonium carbonate, purification with Mycosep cartridge, and instrumental analysis by LC-MS/MS using Syncronis C18 column. The standard calibration curves showed linearity with correlation coefficents; $R^2$ >0.99. Mean recoveries ranged from 72.0 to 111.3% at three different fortified levels (20, 50, and $100{\mu}g/kg$). The correlation coefficient expressed as precision was within the range of 1.9-12.9%. The limit or quantifications (LOQ) ranged from 0.012 to $0.058{\mu}g/kg$. The developed analytical method met the criteria of AOAC Int. and CAC validation parameters like accuracy and sensitivity. As a result, it was confirmed that the test method developed in this study is suitable for the simultaneous analysis of six species of ergot alkaloid from grains and grain products.

• Korean Journal of Environmental Agriculture
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• v.40 no.2
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• pp.108-117
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• 2021

BACKGROUND: Dichlobentiazox is a newly registered pesticide in Korea as a triazole fungicide and requires establishment of an official analysis method for the safety management. Therefore, the aim of this study was to determine the residual analysis method of dichlobentiazox for the five representative agricultural products. METHODS AND RESULTS: Three QuEChERS methods were applied to establish the extraction method, and the EN method was finally selected through the recovery test. In addition, various adsorbent agents were applied to establish the clean-up method. As a result, it was found that the recovery of the tested pesticide was reduced when using the d-SPE method with PSA and GCB, but C₁₈ showed an excellent recovery. Therefore this method was established as the final analysis method. For the analysis, LC-MS/MS was used with consideration of the selectivity and sensitivity of the target pesticide and was operated in MRM mode. The results of the recovery test using the established analysis method and inter laboratory validation showed a valid range of 70-120%, with standard deviation and coefficient of variation of less than 3.0% and 11.6%, respectively. CONCLUSION: Dichlobentiazox could be analyzed with a modified QuEChERS method, and the method determined would be widely available to ensure the safety of residual pesticides in Korea.

• The Journal of Korean society of community based occupational therapy
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• v.10 no.3
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• pp.63-74
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• 2020

Objective : The purpose of this study is to investigate the influence of internal shame and self-control on interpersonal relationships in stroke patients, and to provide evidence and information necessary for clinical trials by analyzing the relationship. Methods : For this study, 150 stroke patients receiving occupational therapy services at institutions where occupational therapists work in Jeollanam-do and Chungnam regions were targeted through email and mail from March 1, 2019 to April 30, 2019. The questionnaire was conducted using general characteristics, Relationship Change Scales(RCS), Self-Control Scales(SCS), and Internalized Shame Scale(ISS) questionnaire. Descriptive statistical analysis was performed for the general characteristics of the study subjects, and t-test and one-way batch variance analysis (ANOVA) were used to compare interpersonal relationships according to general characteristics. The relationship between internalized shame, self-control, and interpersonal competence was analyzed by Pearson's correlation coefficient, and multiple regression analysis was performed to determine the factors affecting interpersonal relationships of stroke patients. Results : As a result of comparing interpersonal competence according to general characteristics, significant differences were found in terms of age and education level. Interpersonal relationships and internalized shame, internalized shame and self-control showed a negative correlation, and self-control and interpersonal relationships had a positive correlation, but self-control was the sub-factors of interpersonal relationships such as openness, sensitivity, intimacy, It was not statistically significant with the communication item. In addition, the items of inadequacy (β =-0.32) and adventure seeking (β =-0.23), which are sub-areas of internalized shame, affect the negative direction, and physical activity (β =0.22), which is the sub-area of self-control and the self-centered (β =0.24) item was found to have an effect on the positive direction. Conclusion : Therefore, additional research is needed that can operate a rehabilitation treatment program that applies various psychological factors for the formation of interpersonal relationships among stroke patients.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.457-468
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• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.

• Korean Journal of Environmental Agriculture
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• v.41 no.2
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• pp.82-94
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• 2022

BACKGROUND: Spiropidion and its metabolite are tetramic acid insecticide and require the establishment of an official analysis method for the safety management because they are newly registered in Korea. Therefore, this study was to determine the analysis method of residual spiropidion and its metabolite for the five representative agricultural products. METHODS AND RESULTS: Three QuEChERS methods (original, AOAC, and EN method) were applied to optimize the extraction method, and the EN method was finally selected by comparing the recovery test and matrix effect results. Various adsorbent agents were applied to establish the clean up method. As a result, the recovery of spiropidion was reduced when using the dispersive-SPE method with MgSO₄, primary secondary amine (PSA), graphitized carbon black (GCB) and octadecyl (C₁₈) in soybean. Color interference was minimized by selecting the case including GCB and C18 in addition to MgSO₄. This method was established as the final analysis method. LC-MS/MS was used for the analysis by considering the selectivity and sensitivity of the target pesticide and the analysis was performed in MRM mode. The results of the recovery test using the established analysis method and inter laboratory validation showed a valid range of 79.4-108.4%, with relative standard deviation and coefficient of variation were less than 7.2% and 14.4%, respectively. CONCLUSION(S): Spiropidion and its metabolite could be analyzed with a modified QuEChERS method, and the established method would be widely available to ensure the safety of residual insecticides in Korea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.1-9
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• 2022

The effect of sediments in a waste dumping area on marine organisms was evaluated using sediment toxicity tests with a benthic amphipod (Monocorophium acherusicum) and bioluminescent bacterium (Vibrio fischeri) in accordance with the Korean Standard Method for Marine Wastes (KSMMW). Nine sites in the East Sea-Byeong, East Sea-Jeong, and Yellow Sea-Byeong areas were sampled from 2016 to 2019. The test results showed that the relative average survival rate (benthic amphipods) and relative luminescence inhibition rate (luminescent bacteria) were below 30%, which were judged to be "non-toxic." However, in the t-test, a total of 12 benthic amphipod samples (6, 1, 1, and 4 in 2016, 2017, 2018, and 2019, respectively) were significantly different (p<0.05) from the control samples. To identify the source of toxicity on benthic amphipods, a simple linear regression analysis was performed between the levels of eight heavy metals (Cr, As, Ni, Cd, Cu, Pb, Zn, and Hg) in sediments and the relative average survival rate. The results indicated that Cr had the highest contribution to the toxicity of benthic amphipods (p = 0.000, R2 = 0.355). In addition, Cr was detected at the highest concentration at the DB-85 station and exceeded the Marine Environment Standards every year. Although the sediments were determined as "not toxic" according to the ecotoxicity criteria of the KSMMW, the results of the statistical significance tests and toxicity identification evaluation indicated that the toxic effect was not acceptable. Therefore, revising the criteria for determining the toxic effect by deriving a reference value through quantitative risk assessment using species sensitivity distribution curves is necessary in the future.

• Journal of Food Hygiene and Safety
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• v.38 no.3
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• pp.79-88
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• 2023

Trifludimoxazin is a triazinone herbicide that inhibits the synthesis of protoporphyrinogen oxidase (PPO). The lack of PPO damages the cell membranes, leading to plant cell death. An official analytical method for the safety management of trifludimoxazin is necessary because it is a newly registered herbicide in Korea. Therefore, this study aimed to develop a residual analysis method to detect trifludimoxazin in five representative agricultural products. The EN method was established as the final extraction method by comparing the recovery test and matrix effect with those of the QuEChERS method. Various sorbent agents were used to establish the clean-up method, and no differences were observed among them. MgSO₄ and PSA were selected as the final clean-up conditions. We used LC-MS/MS considering the selectivity and sensitivity of the target pesticide and analyzed the samples in the MRM mode. The recovery test results using the established analysis method and inter-laboratory validation showed a valid range of 73.5-100.7%, with a relative standard deviation and coefficient of variation less than 12.6% and 14.5%, respectively. Therefore, the presence of trifludimoxazin can be analyzed using a modified QuEChERS method, which is widely available in Korea to ensure the safety of residual insecticides.

• Tuberculosis and Respiratory Diseases
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• v.61 no.2
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• pp.129-136
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• 2006

Background: To interpret lung function tests, it is necessary to determine the lower limits of normal (LLN) and to derive a consensus on the interpretative algorithm. '0.7 of LLN for the $FEV_1$/FVC' was suggested by the COPD International Guideline (GOLD) for defining obstructive disease. A consensus on a new interpretative algorithm was recently achieved by ATS/ERS in 2005. We evaluated the accuracy of '0.7 of LLN for the $FEV_1$/FVC' for diagnosing obstructive diseases, and we also determined the effect of the new algorithm on diagnosing ventilatory defects. Methods: We obtained the age, gender, height, weight, $FEV_1$, FVC, and $FEV_1$/FVC from 7362 subjects who underwent spirometry in 2005 at the Asan Medical Center, Korea. For diagnosing obstructive diseases, the accuracy of '0.7 of LLN for the $FEV_1$/FVC' was evaluated in reference to the $5^{th}$ percentile of the LLN. By applying the new algorithm, we determined how many more subjects should have lung volumes testing performed. Evaluation of 1611 patients who had lung volumes testing performed as well as spirometry during the period showed how many more subjects were diagnosed with obstructive diseases according to the new algorithm. Results: 1) The sensitivity of '0.7 of LLN for the $FEV_1$/FVC' for diagnosing obstructive diseases increased according to age, but the specificity was decreased according to age; the positive predictive value decreased, but the negative predictive value increased. 2) By applying the new algorithm, 34.5% (2540/7362) more subjects should have lung volumes testing performed. 3) By applying the new algorithm, 13% (205/1611) more subjects were diagnosed with obstructive diseases; these subjects corresponded to 30% (205/681) of the subjects who had been diagnosed with restrictive diseases by the old interpretative algorithm. Conclusion: The sensitivity and specificity of '0.7 of LLN for the $FEV_1$/FVC' for diagnosing obstructive diseases changes according to age. By applying the new interpretative algorithm, it was shown that more subjects should have lung volumes testing performed, and there was a higher probability of being diagnosed with obstructive diseases.

• Pediatric Infection and Vaccine
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• v.6 no.1
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• pp.78-85
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• 1999

Purpose : Mycoplasma pneumoniae pneumonia has been to be developed frequently in school age children and adolescence and hard to see under 3 year-old children. But it seems to be increased in number of patients with Mycoplasma pneumoniae pneumonia under 3-year old in clinical practice in these days. We have aimed to examine the characteristics of clinical findings of Mycoplasma pneumonia under 3 year-old children. Methods : We had performed retrospective review of medical records of 30 patients with Mycoplasmal pneumonia under 3-year old children who admitted to Department of Pediatrics, Kyunghee University Hospital from Jan. 1994 to Dec. 1997. The diagnostic criteriae was Cold agglutinin titer>1:64 or Mycoplasma antibody titer>1:80. Results : Mycoplasmal pneumonia was 30 out of 235 cases(12.7%) of total pneumonia under 3 year old children. Male female ratio was 1.3 : 1 and age distributions were 0~1y : 0, 1~2y : 8, 2~3y : 22 cases. Clinical symptoms and signs were cough(100.0%), sputum(83.3%), fever(80.0%) rhinorrhea(33.3%), vomiting(33.3%), moist rale(86.7%), decreased breathing sound(26.7%), wheezing(20.0%), and pharyngeal injection(30.0%). Thirteen out of 30 cases(43.3%) had unilateral infiltration, 10 cases(33.4%) had bilateral infiltration, 1 case(3.3%) had pleural effusion, and 6 cases(20.0%) had negative findings on chest radiography and there was no cases of atelectasis. On laboratory findings, 6 out of 30 cases(20.0%) had leukocytosis, 1 case(3.3%) had neutrophilia, 10 cases(30.0%) had eosinophilia, 17 cases(56.7%) had increased ESR, and 18 cases(60.6%) had positive CRP. Positive cold agglutinin titers(>1 : 64) were 19 cases(63.3%), and positive mycoplasma antibody(M-ab) titers(>1 : 80) were 27 cases(93.3%). Mycoplasma antibody test was more valuable than cold agglutinin test for the diagnosis of Mycoplasmal pneumonia and there was no correlation between cold agglutinin titer and mycoplasma antibody titer. Mycoplasma-polymerase chain reaction(M-PCR) was done with 13 cases, 12 out of 13 cases(92.3%) were positive. M-PCR test was valuable to the diagnosis of Mycoplasmal pneumonia but it will be needed to further study for their clinical application. Among 30 cases, 5 cases(16.7%) had complications, 3 cases(10.0%) had skin rash, 1 case(3.3%) had pleural effusion, 1 case(3.3%) had arthralgia, but all complications were mild and recovered without residual sequelae. Conclusion : The occurrence of Mycoplasmal pneumonia under 3 year-old children was not rare from this study. Clinical characteristics of Mycoplasmal pneumonia under 3-year old were normal radiologic findings in many cases, low complication rate, mild clinical course, and tend to rapid recovery compared with general manifestations of Mycoplasmal infectionsin children and adolescence. There were likely to be missed patients with Mycoplasmal pneumonia which did not diagnose by conventional serologic tests that had low sensitivity and specificity. We have to pay attention to the Mycoplasmal infection of the young children with pneumonia during epidemic periods of Mycoplasmal infection.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.