• Journal of Chest Surgery
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• v.40 no.6 s.275
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• pp.414-419
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• 2007

Background: Replacing the ascending aorta is a standard surgical option for treating acute type A aortic dissection. But replacing the aortic arch has recently been reported as an acceptable procedure for this disease. We compared the effects of aortic arch replacement for treating acute type A aortic dissection with the effects of ascending aortic replacement. Material and Method: From 2002 to 2006, 25 patients undewent surgical treatment for acute type A aortic dissection, 12 patients undewent ascending aortic replacement and 13 patients underwent aortic arch replacement. Among the aortic arch group, an additional distal stent-graft was inserted during the operation in 5 patients. 19 patients (11 arch replaced patients and 8 ascending aortic replaced patients) were followed up at the out patient clinic for an average of $756{\pm}373$ days. All the patients undewent CT scanning and we analyzed their distal aortic segments. Result: 4 patients who underwent ascending aortic replacement died, so the overall mortality rate was 16%. Among the 11 long term followed-up arch replacement patients, 2 patients (18.1 %) developed distal aortic dilatation and one of them underwent thoracoabdominal aortic replacement later on. However, among the 8 the ascending aortic replaced patients, 5 patients (62.5%) developed distal aortic dilatation. Conclusion: Aortic arch replacement is one of the safe options for treating acute type A aortic dissection. Aortic arch replacement for treating acute type A aortic dissection could contribute to a reduced distal aortic dilatation rate and fewer secondary aortic procedures.

• Journal of Korea Water Resources Association
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• v.53 no.7
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• pp.493-505
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• 2020

The rainfall-runoff model has been generally adopted to obtain a consistent runoff sequence with the use of the long-term ground-gauged based precipitation data. The Thiessen polygon is a commonly applied approach for estimating the mean areal rainfall from the ground-gauged precipitation by assigning weight based on the relative areas delineated by a polygon. However, spatial bias is likely to increase due to a sparse network of the rain gauge. This study aims to generate continuous runoff sequences with the mean areal rainfall obtained from radar rainfall estimates through a PRMS rainfall-runoff model. Here, the systematic error of radar rainfall is corrected by applying the G/R Ratio. The results showed that the estimated runoff using the corrected radar rainfall estimates are largely similar and comparable to that of the Thiessen. More importantly, one can expect that the mean areal rainfall obtained from the radar rainfall estimates are more desirable than that of the ground in terms of representing rainfall patterns in space, which in turn leads to significant improvement in the estimation of runoff.

• Ecology and Resilient Infrastructure
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• v.2 no.2
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• pp.185-190
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• 2015

Greenhouse gas (GHG) emission from agricultural lands is recognized as one of important factors of global warming. The objective of this short communication was to evaluate the applicability of different soil GHG emission prediction models on agricultural systems in Korea. Four models, namely, DNDC, DAYCENT, EXPERT-N and COUP, were selected and the basic structure (e.g., components and sub-model), input variables, and output variables were compared. In particular, the availability and compilation of essential input variables were assessed. Major input variables needed for operating these predictive models were found to be available through database systems established by national organizations such as the Korea Meteorological Administration, the Korean Soil Information System, and the Rural Development Administration. However, in order to apply these models in Korea, it was necessary to calibrate and validate each of the models for the domestic landscape settings and climate conditions. In addition, field data of long-term monitoring of GHG emission from agricultural lands are limited and therefore should be measured.