• Environmental Analysis Health and Toxicology
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• v.15 no.1_2
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• pp.19-29
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• 2000

Acetanilide may be released into the environment through air and wastewater from its production and use sites as an intermediate in the synthesis of pharmaceuticals and dyes. Acetanilide is biodegraded rapidly under aerobic conditions and decomposed by indirect photolysis in the presence of OH radicals. An estimated bioconcentration factor of 4.5 suggests that bioaccumulation in aquatic organisms is low. Ecotoxicological data on acetanilide exist on acute toxicity to fishes of 4 species only. According to the EUSES system, the lowest PNEC (Predicted no effect concentration) in fishes is 0.01 mg/1 and PEC (Predicted environmental concentration) for surface water on a regional scale is 9.1$\times$10$\^$－5/mg/l as the worst case. RCR (Risk characterization ratio) of acetanilide for surface water on a regional scale was estimated as 9.1$\times$10-3, which is safe enough for fishes, RCR on a local basis slightly exceeds the value 1 in water and sediment; that is, 1.3 and 1.6, respectively, which suggests the existence of ecotoxicological risk at the vicinity of the manufacturing site. For the refinement of environmental risk assessment on acetanilide, more data should be collected regarding prolonged fish toxicity, acute toxicity toward daphnia and algae. It is, therefore, recommended that acetanilide should be a candidate for further work to supplement the lacking data until it is proved to be safe in the ecotoxicological aspects.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.4
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• pp.213-220
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• 2009

In order to predict the risk of freeze injury for 'Changhowon Hwangdo' peach trees, we used the dormancy depth (i.e., the daily chill unit accumulation during the overwintering period) as a proxy for the short-term, physiological tolerance to freezing temperatures. A Chill-days model was employed and its parameters such as base temperature and chilling requirement were optimized for peach trees based on the 12 observational experiments during the 2008-2009 winter. The model predicted the flowering dates much closer to the observations than other models without considering dormancy depth, showing the strength of employing dormancy depth into consideration. To derive empirical equations for calculating the probabilistic freeze risk, the dormancy depth was then combined with the browning ratio and the budburst ratio of frozen peach fruit branches. Given the exact date and the predicted minimum temperature, the equations calculate the probability of freeze damages such as a failure in budburst or tissue browning. This method of employing dormancy depth in addition to freezing temperature would be useful in locating in advance the risky areas of freezing injury for peach trees production under the projected climate change.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.672-679
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• 2018

This study was conducted to predict the potential distribution and risk of invasive alien plant, Amaranthus patulus, in an agricultural area of South Korea. We collected 254 presence localities of A. patulus using field survey and literature search and stimulated the potential distribution area of A. patulus using maximum entropy modeling (MaxEnt) with six climatic variables. Two different kinds of agricultural risk index, raster risk index and regional risk index, were estimated. The 'raster risk index' was calculated by multiplying the potential distribution by the field area in $1{\times}1km$ and 'regional risk index' was calculated by multiplying the potential distribution by field area proportion in the total field of South Korea. The predicted potential distribution of A. patulus was almost matched with actual presence data. The annual mean temperature had the highest contribution for distribution modeling of A. patulus. Area under curve (AUC) value of the model was 0.711. The highest regions were Gwangju for potential distribution, Jeju for 'raster risk index' and Gyeongbuk for 'regional risk index'. This different ranks among the index showed the importance about the development of various risk index for evaluating invasive plant risk.

• Korean Journal of Construction Engineering and Management
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• v.18 no.2
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• pp.71-80
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• 2017

In recent years, the reduction of international award and project loss by Korean contractors have become a big issue not only in industry but also in academic fields. However, many researches have not focused on small and medium subcontractors but on the large contractors, even though the number of international project by small and medium companies is more than by large companies. Therefore, this study focuses on analyzing the predicted risk before bid and the actual risk after award in international subcontracting projects. In addition, it provides the difference between project performances according to the contract types and the project profitability. This study is expected to give more informed risk knowledge to small and medium subcontractors, which enables them to pay attention to managing risk for better project performances.

• Nutrition Research and Practice
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• v.10 no.4
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• pp.411-417
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• 2016

BACKGROUND/OBJECTIVES: Metabolic syndrome (MetS) is a set of interrelated metabolic risk factors that increase the risk of cardiovascular morbidity and mortality. Studies regarding the specificity and sensitivity of serum levels of leptin and uric acid as predictors of MetS are limited. The aim of this study was to evaluate the serum levels of leptin and uric acid in terms of their specificity and sensitivity as predictors of MetS in the studied Jordanian group. SUBJECTS/METHODS: In this cross sectional study, 630 adult subjects (308 men and 322 women) were recruited from the King Hussein Medical Center (Amman, Jordan). The diagnosis of MetS was made according to the 2005 International Diabetes Federation criteria. Receiver operating characteristic curves were used to determine the efficacy of serum levels of leptin and uric acid as predictors of MetS in the studied Jordanian group. RESULTS: Study results showed that for identification of subjects with MetS risk, area under the curve (AUC) for leptin was 0.721 and 0.683 in men and women, respectively. Serum uric acid levels in men showed no significant association with any MetS risk factors and no significant AUC, while uric acid AUC was 0.706 in women. CONCLUSION: Serum leptin levels can be useful biomarkers for evaluation of the risk of MetS independent of baseline obesity in both men and women. On the other hand, serum uric acid levels predicted the risk of MetS only in women.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.193-199
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• 2017

The objective of this research is to investigate how consumers react differently to financial and social risk/return, referred to as an 'asymmetric effect'. A lab-based experiment using a counterfeit but real-branded product examined the robustness of the statement that priming the interdependent versus independent self can result in differences in financial and social risk taking behavior in the context of counterfeit product purchase choice. Three hundred fifty-eight participants took part in the experiment. They were primed with different self-construal and evaluated purchase intention to the counterfeit product. As predicted, when evaluate in the context of loss claim of counterfeit product, risks were more activated, however, there was an asymmetric effect that self-construal priming had on financial and social risks. Interdependence primed participants were more likely to take a financial risk thus perform more purchase intention of counterfeit product and less likely to take a social risk than their independence primed counterparts, which led to lower purchase intention. The results of this research shed light on the various directions of future studies on the responses toward counterfeit product.

• Journal of Korea Water Resources Association
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• v.49 no.9
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• pp.749-759
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• 2016

The aim of this study is to apply and to evaluate the radar-based risk prediction algorithm for damage reduction by sudden localized heavy rain in urban areas. The algorithm is combined with three processes such as "detection of cumulonimbus convective cells that can cause a sudden downpour", "automatic tracking of the detected convective cells", and "risk prediction by considering the possibility of sudden downpour". This algorithm was applied to rain events that people were marooned in small urban stream. As the results, the convective cells were detected through this algorithm in advance and it showed that it is possible to determine the risk of the phenomenon of developing into local heavy rain. When use this risk predicted results for flood prevention operation, it is able to secure the evacuation time in small streams and be able to reduce the casualties.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.149-155
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• 2020

Air pollution is a problem of environmental health risk in big cities. Recently, researchers have proposed using various artificial intelligence technologies to predict air pollution. The proposed model is Cooperative of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS), to predict air pollution of Korean cities using Python. Data air pollutant variables were collected and the Air Korean Web site air quality index was downloaded. This paper's aim was to predict on the health risks and the very unhealthy values of air pollution. We have predicted the air pollution of the environment based on the air quality index. According to the results of the experiment, our model was able to predict a very unhealthy value.

• Environmental Analysis Health and Toxicology
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• v.24 no.3
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• pp.261-270
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• 2009

To make measurable regulatory decisions of chemicals, it is necessary to consider their effect on the human health and ecosystem. In principle, this is based on relevant toxicity studies conducted by accepted guidelines. However, current regulatory programs in various countries confront challenges related to risk assessment of large numbers of chemicals within the restricted resources and time. Therefore there is a need for more efficient approach to limit the number of tests to be conducted. This promotes the development of powerful nontesting methods (e.g. (Q)SARs) and permits to use the predicted data for regulatory purpose. In this article, current status of non-testing methods in various chemical regulatory programs was reviewed in terms of their application and research activity on them. Finally, their usefulness associated with development of domestic regulatory program was suggested.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.31 no.2
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• pp.88-93
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• 2020

Objectives: Mood disorder is highly comorbid with attention deficit/hyperactivity disorder (ADHD), and comorbid ADHD symptoms are associated with suicide risk. The aim of this study was to examine the association between comorbid ADHD symptoms and the number of suicide attempts among patients with unipolar and bipolar depression. Methods: In this cross-sectional study, 100 patients with either unipolar or bipolar depression constituted the final sample. Pearson's correlation and multiple regression analyses were conducted to examine the association between comorbid ADHD symptoms and suicide risk. Results: Among patients with bipolar depression, the number of suicide attempts was significantly correlated with ADHD symptoms (r=0.324, p<0.01). ADHD symptoms significantly predicted the number of suicide attempts (β=0.249, p<0.05). Conclusion: Our findings underscore the importance of screening and assessing ADHD symptoms in male young adults with depressive disorders.