• Journal of Chest Surgery
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• v.32 no.7
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• pp.637-647
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• 1999

Background: Ischemia-reperfusion injury is one of the major contributing causes of early graft failure in lung transplantation. It has been suggested that triiodothyronine (T3) may ameliorate ischemia-reperfusion injury to various organs in vivo and in vitro. Predicting its beneficial effect for ischemic lung injury, we set out to demonstrate it by administering T3 into the in situ canine ischemia-reperfusion model. Material and Method: Sixteen adult mongrel dogs were randomly allocated into group A and B. T3 $(3.6\mug/kg)$ was administered before the initiation of single lung ischemia in group B, whereas the same amount of saline was administered in group A. Ischemia was induced in the left lung by clamping the left hilum for 100 minutes. After reperfusion, various hemodynamic parameters and blood gases were analyzed for 4 hours while intermittently clamping the right hilum in order to allow observation of the injured left lung function. Result: Arterial oxygen partial pressure $(PaO_2)$ decreased 30 minutes after reperfusion and recovered gradually thereafter in both groups. In group B the decrease of $PaO_2$ was less marked than in group A. The recovery of $PaO_2$ was faster in group B than in group A. The differences between the two groups were statistically significant from 30 minutes after reperfusion $(125\pm34$ mmHg and $252\pm44$ mmHg, p<0.05) until the end of the experiment $(178\pm42$mmHg and $330\pm37$ mmHg, p<0.05). The differences in the arterial carbon dioxide pressure, airway pressure and lung compliance showed no statistical significance. The malondialdehyde (MDA) level, measured from the tissue obtained 240 minutes after reperfusion, was lower in group B $(0.40\pm0.04\mu$M) than in group A $(0.53\pm0.05\mu$M, p<0.05). The ATP level of group B $(0.69\pm0.07\mu$M/g) was significantly higher than that of group A $(0.48\pm0.07\mu$M/g, p<0.05). The microscopic exami nation revealed varying degrees of injury such as perivascular neutrophil infiltration, capillary hemorrhage and interstitial congestion. There were no differences in the microscopic findings between the two groups. CONCLUSION T3 has beneficial effects on the ischemic canine lung injury including preservation of oxygenation capacity, less production of lipid peroxidation products and a higher level of tissue ATP. These results suggest that T3 is effective in pulmonary allograft preservation.

• Journal of Chest Surgery
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• v.32 no.5
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• pp.413-421
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• 1999

Background: Ischemia reperfusion injury is known to contribute to the major causes of the early graft failure in lung transplantation. Triiodothyronine (T3) has been suggested to ameliorate ischemia reperfusion injury from both in vivo and in vitro experiments of various organs. Prospecting its beneficial effect for pulmonary allograft preservation, we made a new solution by adding T3 into the extracellular type dextran solution. Material and Method: Twelve adult mongrel dogs underwent left lung allotransplantation. Six donor dogs were flushed with the new solution(Group 1, n=6), and the remaining six were flushed with Euro-Collins solution to serve as controls(Group 2, n=6). Allografts were stored in each preservation solution for 20 hours at 4$^{\circ}C$. Left single lung transplantations were performed. The right pulmonary artery and the right main bronchus were clamped at 15 minutes after the reperfusion and maintained throughout the experiment to evaluate the transplanted left lung function. Result: Arterial carbon dioxide tension was better in group 1 than in group 2 throughout the experiment period and the difference was statistically significant at 2 hours after reperfusion(28.0${\pm}$3.0 mmHg and 53.1${\pm}$17.4 mmHg, p<0.05). The differences of arterial oxygen partial pressure, peak airway pressure and pulmonary vascular resistance showed no statistical significance. The malondialdehyde(MDA) level, measured from tissue obtained at 120 minutes after reperfusion showed no statistically significant difference. The tissue wet/dry ratio of group 1(649${\pm}$27 %) was significantly lower than that of group 2(686${\pm}$71 %, p<0.05). The microscopic examination revealed varying degrees of injury represented mainly by findings such as perivascular neutrophil infiltration, capillary hemorrhage and interstitial congestion. These findings were less severe in group 1 than those in group 2. Conclusion: The new solution demonstrated superior allograft preservation after 20 hour ischemia compared to Euro-Collins solution in canine single left lung transplantation model, these results suggest that T3 might be a promising agent for pulmonary allograft preservation.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.117-137
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• 2009

Recently, intelligent traffic information systems have enabled people to forecast traffic conditions before hitting the road. These convenient systems operate on the basis of data reflecting current road and traffic conditions as well as distance-based data between locations. Thanks to the rapid development of ubiquitous computing, tremendous context data have become readily available making vehicle route planning easier than ever. Previous research in relation to optimization of vehicle route planning merely focused on finding the optimal distance between locations. Contexts reflecting the road and traffic conditions were then not seriously treated as a way to resolve the optimal routing problems based on distance-based route planning, because this kind of information does not have much significant impact on traffic routing until a a complex traffic situation arises. Further, it was also not easy to take into full account the traffic contexts for resolving optimal routing problems because predicting the dynamic traffic situations was regarded a daunting task. However, with rapid increase in traffic complexity the importance of developing contexts reflecting data related to moving costs has emerged. Hence, this research proposes a framework designed to resolve an optimal route planning problem by taking full account of additional moving cost such as road traffic cost and weather cost, among others. Recent technological development particularly in the ubiquitous computing environment has facilitated the collection of such data. This framework is based on the contexts of time, traffic, and environment, which addresses the following issues. First, we clarify and classify the diverse contexts that affect a vehicle's velocity and estimates the optimization of moving cost based on dynamic programming that accounts for the context cost according to the variance of contexts. Second, the velocity reduction rate is applied to find the optimal route (shortest path) using the context data on the current traffic condition. The velocity reduction rate infers to the degree of possible velocity including moving vehicles' considerable road and traffic contexts, indicating the statistical or experimental data. Knowledge generated in this papercan be referenced by several organizations which deal with road and traffic data. Third, in experimentation, we evaluate the effectiveness of the proposed context-based optimal route (shortest path) between locations by comparing it to the previously used distance-based shortest path. A vehicles' optimal route might change due to its diverse velocity caused by unexpected but potential dynamic situations depending on the road condition. This study includes such context variables as 'road congestion', 'work', 'accident', and 'weather' which can alter the traffic condition. The contexts can affect moving vehicle's velocity on the road. Since these context variables except for 'weather' are related to road conditions, relevant data were provided by the Korea Expressway Corporation. The 'weather'-related data were attained from the Korea Meteorological Administration. The aware contexts are classified contexts causing reduction of vehicles' velocity which determines the velocity reduction rate. To find the optimal route (shortest path), we introduced the velocity reduction rate in the context for calculating a vehicle's velocity reflecting composite contexts when one event synchronizes with another. We then proposed a context-based optimal route (shortest path) algorithm based on the dynamic programming. The algorithm is composed of three steps. In the first initialization step, departure and destination locations are given, and the path step is initialized as 0. In the second step, moving costs including composite contexts into account between locations on path are estimated using the velocity reduction rate by context as increasing path steps. In the third step, the optimal route (shortest path) is retrieved through back-tracking. In the provided research model, we designed a framework to account for context awareness, moving cost estimation (taking both composite and single contexts into account), and optimal route (shortest path) algorithm (based on dynamic programming). Through illustrative experimentation using the Wilcoxon signed rank test, we proved that context-based route planning is much more effective than distance-based route planning., In addition, we found that the optimal solution (shortest paths) through the distance-based route planning might not be optimized in real situation because road condition is very dynamic and unpredictable while affecting most vehicles' moving costs. For further study, while more information is needed for a more accurate estimation of moving vehicles' costs, this study still stands viable in the applications to reduce moving costs by effective route planning. For instance, it could be applied to deliverers' decision making to enhance their decision satisfaction when they meet unpredictable dynamic situations in moving vehicles on the road. Overall, we conclude that taking into account the contexts as a part of costs is a meaningful and sensible approach to in resolving the optimal route problem.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.3
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• pp.309-316
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• 2008

This study was carried out to examine the effects of vitamin E on chronic gastric ulcer induced by alcohol treatment in rats. Chronic gastric ulcer model was established by oral administration of 70% ethanol at one time and supply of 15% ethanol for additional 7 days. Male Sprague-Dawley rats, approximately 200 g, were fasted for 24 hours and orally gavaged with 1 mL of 70% ethanol for the induction of acute ulcer. A supply of 15% ethanol dissolved in distilled water for 7 days were followed to maintain chronic gastric ulcer. Acute ulcer group was sacrificed at 3 hours after oral administration of 1 mL of 70% ethanol. Chronic groups were divided into three groups according to vitamin E levels; low-vitamin E (LVE, 0 mg/mL oil/day), normalvitamin E (NVE, 1 mg/mL oil/day) and high-vitamin E (HVE, 10 mg/mL oil/day). These groups were fed vitamin E free diets which were made of vitamin E free vitamin mix followed AIN-93M pattern for 7 days. Histological findings of congestion, hemorrhage and necrosis in gastric tissue were shown severely in acute ulcer group and LVE group of chronic ulcer groups. The concentration of gastrin in serum was significantly higher in LVE group. The content of histamine in stomach was lower in acute ulcer group but there was no significant difference among the chronic groups regardless of vitamin E levels. Content of malondialdehyde (MDA) in gastric tissue was higher in HVE group and activities of antioxidant enzyme, glutathione peroxidase (GPx) and catalase, were lower in HVE group. Myeloperoxidase (MPO) activities as a marker of neutrophils infiltration was significantly higher in LVE group. These results suggested that vitamin E supplementation has positive effects on healing of alcohol-induced chronic gastric ulcer through alleviation of gastric tissue injuries and reduction of the MPO activity in gastric tissue and gastrin in serum.

• Journal of Environmental Impact Assessment
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• v.28 no.3
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• pp.183-200
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• 2019

In this study, the characteristics of seasonal $PM_{2.5}$ behavior in South Korea and other Northeast Asian regions were analyzed by using the $PM_{2.5}$ ground measurement data, weather data, WRF and CMAQ models. Analysis of seasonal $PM_{2.5}$ behavior in Northeast Asia showed that $PM_{2.5}$ concentration at 6 IMS sites in South Korea was increased by long-distance transport and atmospheric congestion, or decreased by clean air inflow due to seasonal weather characteristics. As a result of analysis by applying BFM to air quality model, the contribution from foreign countries dominantly influenced the $PM_{2.5}$ concentrations of Baengnyeongdo due to the low self-emission and geographical location. In the case of urban areas with high self-emissions such as Seoul and Ulsan, the $PM_{2.5}$ contribution from overseas was relatively low compared to other regions, but the standard deviation of the season was relatively high. This study is expected to improve the understanding of the air pollutant phenomenon by analyzing the characteristics of $PM_{2.5}$ behavior in Northeast Asia according to the seasonal weather condition change. At the same time, this study can be used to establish the air quality policy in the future, knowing that the contribution of $PM_{2.5}$ concentration to the domestic and overseas can be different depending on the regional emission characteristics.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Resources Recycling
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• v.31 no.5
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• pp.67-76
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• 2022

The furniture industry has a high possibility to create value-added and a high potential to create new occupations due to the characteristics of the industry, which mainly consists of small and medium-sized enterprises (SMEs). However, the used furniture, which has sufficient reuse value, is also crushed and used as solid refuse fuel (SRF) recently. Besides, the number of waste treatment companies continues to decrease, and it occurs congestion of wood waste. As a way to solve the issue, a business model development of remanufacturing used furniture can be suggested as an alternative due to its high circular economic efficiency. Remanufacturing business including furniture industry creates positive effects in various aspects such as economic, environmental and job creation. In other words, remanufacturing is an effective recycling way to reduce input resources and energy in the production process. The results of economic analysis show that the expected annual revenue from the single worker furniture remanufacturing site was 104 million won which is 3.11 times more than the average income of a single-worker household in Korea and its B/C ratio was estimated about 30 which means high business feasibility. Revenue through furniture remanufacturing also showed 320 times higher than that of SRF production from the perspective of weight. In addition, it is shown that the GHGs reduction from the furniture remanufacturing is 2.2 ton CO₂-eq. per year, which is similar to the amount of GHGs absorption effect of 937 pine trees or 622 Korean oak trees annually. Thus the results of this study demonstrate that it is important to adopt an appropriate recycling method considering the economic and environmental effects at the end-of-life stage.