• The Journal of Pediatrics of Korean Medicine
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• v.31 no.1
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• pp.52-62
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• 2017

Objectives The purpose of this study is to review pre-existing clinical practice guidelines for autism spectrum disorders, and refer those in developing a new practice guideline. Methods A total of 9 existing clinical practice guidelines for autism spectrum disorder developed from 2010 to 2016 were searched by Google scholar and Pubmed, and were reviewed those literatures in three parts: general, diagnosis & evaluation, and intervention. Results There were no consistency in the recommendation methods of 9 clinical care guidelines (such as the method of rating and recommendation intensity for diagnosis, evaluation, and treatment). However, in the diagnosis and evaluation section, frequently used evaluation and diagnostic tools are mentioned in most clinical practice guidelines, and the types of pharmacologic and non-pharmacological treatments that are mainly recommended in treatment are equally mentioned in most clinical practice guidelines could confirm. Conclusions 1. Some guideline recommendations are graded according to each criterion. Recommendations presented in various databases were based on systematic reviews or other literatures. The most utilized database were PsycINFO, CINAHL, Cochrane. 2. DSM-5 and ICD-10 were the most common used diagnostic criteria, and DSM-IV was used as a diagnostic standard in the guideline published before 2013. The tools used for diagnosis and evaluation were also varied. However, most recommended ones were ADI-R, ADOS-G, and DISCO. 3. Treatment was largely divided into pharmacological intervention and non-pharmacological intervention. In some guideline, the interventions were divided into pediatric and adult. Most of the pharmacological interventions were not recommended due to lack of evidence, but in cases in which specific symptoms were aimed, they recommended to seek professional help. 4. In addition to interventions, each guideline referred to supportive interventions that may be helpful in the daily life of patients with ASD, which may need to be addressed in future clinical guidelines.

• Biomolecules & Therapeutics
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• v.25 no.2
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• pp.112-121
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• 2017

Drug-induced liver injury (DILI) is the serious and fatal drug-associated adverse effect, but its incidence is very low and individual variation in severity is substantial. Acetaminophen (APAP)-induced liver injury accounts for >50% of reported DILI cases but little is known for the cause of individual variations in the severity. Intrinsic genetic variation is considered a key element but the identity of the genes was not well-established. Here, pre-biopsy method and microarray technique was applied to uncover the key genes for APAP-induced liver injury in mice, and a cause and effect experiment employing quantitative real-time PCR was conducted to confirm the correlation between the uncovered genes and APAP-induced hepatotoxicity. We identified the innately and differentially expressed genes of mice susceptible to APAP-induced hepatotoxicity in the pre-biopsied liver tissue before APAP treatment through microarray analysis of the global gene expression profiles (Affymetrix $GeneChip^{(R)}$ Mouse Gene 1.0 ST for 28,853 genes). Expression of 16 genes including Gdap10, Lpl, Gabra3 and Ccrn4l were significantly different (t-test: FDR <10%) more than 1.5 fold in the susceptible animals than resistant. To confirm the association with the susceptibility to APAP-induced hepatotoxicity, another set of animals were measured for the expression level of selected 4 genes (higher two and lower two genes) in the liver pre-biopsy and their sensitivity to APAP-induced hepatotoxicity was evaluated by post hoc. Notably, the expressions of Gabra3 and Lpl were significantly correlated with the severity of liver injury (p<0.05) demonstrating that these genes may be linked to the susceptibility to APAP-induced hepatotoxicity.

• Journal of the Korean Applied Science and Technology
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• v.34 no.4
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• pp.1076-1084
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• 2017

For analyzing the qualitative and quantitative analysis of fuel marker in petroleum products, the applicability of HPLC was studied. For the qualitative analysis of fuel marker in kerosene and automotive diesel, optimal analytical conditions(ratio of mobile phase solvent, flow rate, etc) in HPLC were selected and calibration curve for quantitative analysis of fuel marker was prepared based on the result of qualitative analysis. In particular, the correlation coefficient of calibration curve in kerosene and automotive diesel was shown to be 0.999 in a certain concentration range and it could be applied to the quantitative analysis. The results of analysis using the UV/Vis spectrometer, which is the current analysis method of fuel marker, were compared with the analysis results using the HPLC. The kerosene showed a low deviation of about 7 % and the automotive diesel showed a somewhat large deviation of about 20 %.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.944-958
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• 2011

Soil hydraulic properties such as hydraulic conductivity or water retention which are costly to measure can be indirectly generated by soil pedotransfer function (PTF) using easily obtainable soil data. The field soil structure description which is routinely recorded could also be used in PTF as an input to reduce the uncertainty. The purposes of this study were to use qualitative morphological soil structure descriptions and soil structural index into PTF and to evaluate their contribution in the prediction of soil hydraulic properties. We transformed categorical morphological descriptions of soil structure into quantitative values using categorical principal component analysis (CATPCA). This approach was tested with a large data set from the US National Pedon Characterization database with the aid of a categorical regression tree analysis. Six different PTFs were used to predict the saturated hydraulic conductivity and those results were averaged to quantify the uncertainty. Quantified morphological description was successively used in multiple linear regression approach to predict the averaged ensemble saturated conductivity. The selected stepwise regression model with only the transformed morphological variables and structural index as predictors predicted the $K_{sat}$ with $r^2$ = 0.48 (p = 0.018), indicating the feasibility of CATPCA approach. In a regression tree analysis, soil structure index and soil texture turned out to be important factors in the prediction of the hydraulic properties. Among structural descriptions size class turned out to be an important grouping parameter in the regression tree. Bulk density, clay content, W33 and structural index explained clusters selected by a two step clustering technique, implying the morphologically described soil structural features are closely related to soil physical as well as hydraulic properties. Although this study provided relatively new method which related soil structure description to soil structure index, the same approach should be tested using a datasets containing the actual measurement of hydraulic properties. More insight on the predictive power of soil structure index to estimate hydraulic properties would be achieved by considering measured the saturated hydraulic conductivity and the soil water retention.

• Journal of Information Technology Applications and Management
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• v.28 no.6
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• pp.69-85
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• 2021

In the era of the 4th Industrial Revolution, not only artificial intelligence, big data, robots, and biotechnology, but also cultural industries that require human creativity will lead. Among the cultural industries, the animation industry has high industrial utilization value due to its high connection with other industries. Among them, animation characters play the most important role as the subject leading the story of animation. In particular, the villain character not only serves as a medium for the main character to lead the story, but also captivates the audience with a different presence from the main character, adding to the fun and completeness of the animation. These characters consist of visual elements such as form and color, of which color is a tool that effectively conveys the character's personality and role to the audience, and is the first visual element to be considered in delicately describing the character's emotions and the relationship between characters. Therefore, this study attempts to analyze the color of the villain character. To this end, we will select eight Disney animations to derive the characteristics of the villain character's color by analyzing the color, value, chroma, and color association of the colors used in the Disney villain character. As a result of the analysis, the colors mainly used by Disney to convey the villain's image were red (R) and Orange (YR), and there was no difference depending on the times or animation production methods. Second, the brightness of Disney villain characters appeared to be the same medium/famous regardless of the times and production methods, and the frequency of use of high brightness was very low. In terms of saturation, the frequency of use of high and low saturation was high. Third, blackish (Bk), Strong (S), dull (Dl), and deep (Dp) tones were mainly used for tones. In particular, in recent 3D animations than previously produced 2D animations, the use of low chroma and the high black mixing rate increased. Fourth, it can be seen that Disney uses color as a visual method to more clearly express the psychology of the villain character using color association. In conclusion, the color selection of animation characters should be carefully considered as a tool to convey the character's personality, role, and emotion beyond simply using color, and the color selection of characters using color associations and symbols strengthens the narrative structure. It is hoped that this study will help analyze and select the character color of animation.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.425-432
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• 2011

To control non-point source pollution at a watershed scale, rainfall-runoff characteristics from forest watersheds should be investigated since the forest is the dominant land use in Korea. Long-term monitoring would be an ideal method. However, computer models have been utilized due to limitations in cost and labor in performing long-term monitoring at the watersheds. In this study, the Geo-spatial interface to the Water Erosion Prediction Project (GeoWEPP) model was evaluated for its runoff prediction from a coniferous forest dominant watersheds. The $R^2$ and the NSE for calibrated result comparisons were 0.77 and 0.63, validated result comparisons were 0.92, 0.89, respectively. These comparisons indicated that the GeoWEPP model can be used in evaluating rainfall-runoff characteristics. To estimate runoff changes from a coniferous forest watershed with various cover degree scenarios, ten cover degree scenarios (10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%) were run using the calibrated GeoWEPP model. It was found that runoff increases with decrease in cover degree. Runoff volume was the highest ($206,218.66m^3$) at 10% cover degree, whereas the lowest ($134,074.58m^3$) at 100% cover degree due to changes in evapotranspiration under various cover degrees at the forest. As shown in this study, GeoWEPP model could be efficiently used to investigate runoff characteristics from the coniferous forest watershed and effects of various cover degree scenarios on runoff generation.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.77-86
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• 2023

Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.

• Journal of Veterinary Science
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• v.23 no.6
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• pp.12.01-12.10
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• 2022

Background: Staphylococcus aureus and Streptococcus agalactiae are the main cause of clinical mastitis in dairy cattle in Argentina, whereas coagulase-negative staphylococci (CNS) and environmental streptococci are the main cause of subclinical mastitis. Bacteria isolated from infected animals show increasing antimicrobial resistance. Objectives: This study aims to determine the antimicrobial resistance of staphylococci and streptococci isolated from milk with mastitis, and to genotypically characterize the methicillin-resistant (MR) staphylococci. Methods: Isolation was performed on blood agar and identification was based on biochemical reactions. Antimicrobial susceptibility was according to the Clinical and Laboratory Standards Institute guidelines. The antimicrobial resistance genes, SCCmec type and spa type were detected by the polymerase chain reaction method. Results: We isolated a total of 185 staphylococci and 28 streptococci from 148 milk samples. Among the staphylococcal isolates, 154 were identified as CNS and 31 as S. aureus. Among the 154 CNS, 24.6% (n = 38) were resistant to penicillin, 14.9% (n = 23) to erythromycin, 17.5% (n = 27) to clindamycin, 6.5% (n = 10) to cefoxitin and oxacillin. Among the S. aureus isolates, 16.1% (n = 5) were resistant to penicillin, 3.2% (n = 1) to cefoxitin and oxacillin (MRSA). Six MR isolates (5 CNS and 1 MRSA) were positive to the mecA gene, and presented the SCCmec IVa. The MRSA strain presented the sequence type 83 and the spa type 002. Among the 28 streptococcal isolates, 14.3% (n = 4) were resistant to penicillin, 10.7% (n = 3) to erythromycin and 14.3% (n = 4) to clindamycin. Conclusions: The present findings of this study indicate a development of antimicrobial resistance in main bacteria isolated from cows with mastitis in Argentina.

• The Korea Journal of Herbology
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• v.28 no.6
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• pp.47-51
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• 2013

Objectives : The Illicii Veri Fructus was not only traditional medicine but also food in Asia. The aim of this study was selection of optimum solvent in the fruit of Illicii Veri Fructus because an appropriate solvent affect a medicinal effect. Methods : Illicii Veri Fructus was carried out ultrasonic-assisted extraction as various solvents. Two main compounds, p-anisaldehyde and anethole, were successfully analyzed by high performance liquid chromatography-photodiode array detector (HPLC-PDA) and carried out method validation according to ICH guideline. The optimum solvent selected by comparing with yields of two main ingredients. Results : The p-anisaldehyde and anethole were detected at approximately 8.0 min and 19.8 min, respectively. It was all below 5.0% that RSD of retention time and peak area for two main peaks. Calibration curves of two compounds were good linearity as $R^2$ >0.9999. All of the precisions and accuracy were good intra-day and inter-day as below 5.0% RSD. Limited of detection (LOD) of p-anisaldehyde and anethole were analyzed as $0.134{\mu}g/mL$ and $4.286{\mu}g$, respectively. Limited of quantification (LOQ) of two compounds were $0.407{\mu}g$ and $12.989{\mu}g$, respectively. As a result of this study, p-anisladehyde was detected as 0.209 ~ 0.467%, however anethole was not detected in the distilled water. Conclusions : Anethole was main component as 5.329 ~ 6.815% except for water extraction. Methanol extraction among various solvents was detected the highest contents of p-anisaldehyde and anethole as 0.467(${\pm}0.008$)% and 6.815(${\pm}0.220$)%, respectively.

• 한국체육학회지인문사회과학편
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• v.55 no.1
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• pp.457-467
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• 2016

Understanding professional baseball fans' expenditure is expected to provide fundamental marketing information that help increase each team's marketing profits and values and produce a better economic impact on its community. In this regard, this study employed a survey method with a total of 372 residents located in Changwon. A questionnaire included factors such as demographics, consumption patterns and perceived socio-psychic effect(PSE), all of which were derived from literature review. A binary logistic regression was modeled with a dichotomous dependent variable, expenditure(30,000 won more or less). The following were input in the model as the independent variables in order to see the relationships; gender, marriage, education, occupation, income, location, age, leisure type, distance, companion, transportation, interest, and PSE. The results of the logistic regression analysis are as follows. Overall, the model was statistically significant, χ²(21, N=372)=59.159, p=.000. Cox and Snell R² was reported as .147 and .200 respectively. So, the model accounted for between 14.7% and 20.0% of the variation in expenditure. Among the independent variables, income, location, companion, and PSE were found to be the significant factors to expenditure. For income, subjects with 2 million won less of income, compared to those with 4 million won more, were .38 times less likely to pay the money of 30,000 won more. For location, subjects in Masan, compared to those in Jinhae, were 3.49 times more likely to pay 30,000 won more. Subjects in Changwon, compared to those in Jinhae, were 3.05 times more likely to pay 30,000 won more. For companion, people visiting the stadium alone, compared to those with friends/colleague, were .36 times less likely to pay 30,000 won more. For PSE, the odds of 30,000 won more paid increased by 1.37 times with one-unit increase in PSE.