This study was perfomed to investigate the effects of Chunghyul-plus(CHP) on oxidative damage and hyperlipidemia in db/db mouse. After treatment with CHP, safety in cytotoxicity, heavy metal toxicity, production of reactive oxygen species(ROS), nitric oxide (N0) and proinflammatory cytokine IL-Ib, TNF-a, IL-6 in RAW 264.7 cells. Serum total cholesterol, LDL cholesterol, HDL cholesterol, triglyceride, insulin, GLP-1, glucose, food intake, body weight, organ weight, AST, ALT, ALP, BUN, creatine and histologic change of liver and aorta were measured in db/db mouse after oral administration of CHP. CHP showed safety in cytotoxicity and toxicity of liver and kidney for logn time administration. CHP increased the DPPH and ABTS radical scavenging activity. CHP showed significant inhibitory effect on reactive oxygen species (ROS), and showed inhibitory effect on nitiric oxide(NO) compared to control group. CHP decreased cytokine IL-6 production significantly, and decreased IL-1β and TNF-α compared to control group. CHP decreased body and organ weitht, intake food, and glucose levels compared to control group. CHP decreased total cholesterol and triglyceride significantly, and decreased LDL-cholesterol levels and increased HDL-cholesterol levels compared to control group. CHP decreased atherogenic index and cardiac risk factor significantly. CHP increased serum insulin and GLP-1 compared to control group. In histologic examination, lipophagy in the liver and aorta decreased in CHP treated mice and the cell was regular and boundary of vessel wall was clear compared to control group. These results suggest that CHP is effective in antioxidation activity and treatment and prevention of hyperlipidemia, atherosclerosis, diabetes, ischemic heart disease, stroke and other cardiocerebrovascular disease.
Background: In the case of multiple exposures to different types of heavy metals, such as the conditions faced by residents living near a smelter, it would be preferable to group hazardous substances with similar characteristics rather than individually related substances and evaluate the effects of each group on the human body. Objectives: The purpose of this study is to evaluate the utility of factor analysis in the assessment of health effects caused by exposure to two or more hazardous substances with similar characteristics, such as in the case of residents living near a smelter. Methods: Heavy metal concentration data for 572 people living in the vicinity of the Janghang smelter area were grouped based on several subfactors according to their characteristics using factor analysis. Using these factor scores as an independent variable, multiple regression analysis was performed on health effect markers. Results: Through factor analysis, three subfactors were extracted. Factor 1 contained copper and zinc in serum and revealed a common characteristic of the enzyme co-factor in the human body. Factor 2 involved urinary cadmium and arsenic, which are harmful metals related to kidney damage. Factor 3 encompassed blood mercury and lead, which are classified as related to cardiovascular disease. As a result of multiple linear regression analysis, it was found that using the factor index derived through factor analysis as an independent variable is more advantageous in assessing the relevance to health effects than when analyzing the two heavy metals by including them in a single regression model. Conclusions: The results of this study suggest that regression analysis linked with factor analysis is a good alternative in that it can simultaneously identify the effects of heavy metals with similar properties while overcoming multicollinearity that may occur in environmental epidemiologic studies on exposure to various types of heavy metals.
Fuel gases such as methane and propane are used in explosion hazardous area of domestic plants and can form non-uniform mixtures with the influence of process conditions due to leakage. The fire-explosion risk assessment using literature data measured under uniform mixtures, damage prediction can be obtained the different results from actual explosion accidents by gas leaks. An explosion characteristics such as explosion pressure and flame velocity of non-uniform gas mixtures with concentration change similar to that of facility leak were examined. The experiments were conducted in a closed 0.82 m long stainless steel duct with observation recorded by color high speed camera and piezo pressure sensor. Also we proposed the quantification method of non-uniform mixtures from a regression analysis model on the change of concentration difference with time in explosion duct. For the non-uniform condition of this study, the area of flame surface enlarged with increasing the concentration non-uniform in the flame propagation of methane and was similar to the wrinkled flame structure existing in a turbulent flame. The time to peak pressure of methane decreased as the non-uniform increased and the explosion pressure increased with increasing the non-uniform. The ranges of KG (Deflagration index) of methane with the concentration non-uniform were 1.30 to 1.58 [MPa·m/s] and the increase rate of KG was 17.7% in methane with changing from uniform to non-uniform.
Recently, to prevent damage to the landscape, outstanding landscape areas have been designated in advance. In particular, as a fundamental way to evaluate landscape elements, landscape diversity is an important criterion to assess an area with a high conservative value. Therefore, the purpose of this study is to develop a quantitative evaluation model of landscape diversity based on landscape elements and to verify the model by applying it to the study sites. The assessment indicators derived from the literature analysis are topography, vegetation, land-use pattern, and unusual landscape. Topography diversity is subdivided into land undulation and land-form. Vegetation diversity is subdivided into plant community diversity and stratification diversity. To quantitatively analyse each indicator's diversity, SHDI was selected as the central metric. All of the quantitative measures were implemented by using the statistical tool, FRAGSTATS. Through the process of each indicator's standardization and summary, the final landscape diversity index was calculated. The results of the study are significant as it was the initial study of landscape diversity evaluation to seek applicability. However, the results of the Landscape Diversity Evaluation Model in this study based on 4 indicators synthetically demonstrate that more than one or two outstanding indicators can be underrated. Therefore, each 4 assessment indicator results should be considered individually. Furthermore, using the maximum value for each indicator's standardization reflects that it is necessary to analyse various examples to obtain higher objectivity later.
An area's topography refers to the shape of the earth's surface, described by its elevation, slope, and aspect, among other features. The topographical conditions determine energy flowsthat move water and energy from higher to lower elevations, such as how much solar energy will be received and how much wind or rain will affect it. Another common factor, the topographic wetness index (TWI), is a calculation in digital elevation models of the tendency to accumulate water per slope and unit area, and is one of the most widely referenced hydrologic topographic factors, which helps explain the location of forest vegetation. Analyses of topographical factors can be calculated using a geographic information system (GIS) program based on digital elevation model (DEM) data. Recently, a large number of free open source software (FOSS) GIS programs are available and developed for researchers, industries, and governments. FOSS GIS programs provide opportunitiesfor flexible algorithms customized forspecific user needs. The majority of biodiversity in island areas exists at about 20% higher elevations than in land ecosystems, playing an important role in ecological processes and therefore of high ecological value. However, island areas are vulnerable to disturbances and damage, such as through climate change, environmental pollution, development, and human intervention, and lacks systematic investigation due to geographical limitations (e.g. remoteness; difficulty to access). More than 4,000 of Korea's islands are within a few hours of its coast, and 88% are uninhabited, with 52% of them forested. The forest ecosystems of islands have fewer encounters with human interaction than on land, and therefore most of the topographical conditions are formed naturally and affected more directly by weather conditions or the environment. Therefore, the analysis of forest topography in island areas can be done more precisely than on its land counterparts, and therefore has become a major focus of attention in Korea. This study is focused on calculating the performance of different topographical factors using FOSS GIS programs. The test area is the island forests in Korea's south and the DEM of the target area was processed with GRASS GIS and SAGA GIS. The final slopes and TWI maps were produced as comparisons of the differences between topographic factor calculations of each respective FOSS GIS program. Finally, the merits of each FOSS GIS program used to calculate the topographic factors is discussed.
The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.
To predict the influence of volcano eruption on agriculture in South Korea we evaluated the dispersal ranges of the volcanic ashes toward the South Korea based on the possibilities of volcano eruption in Mt. Baekdu. The possibilities of volcano eruption in Mt. Baekdu have been still being intensified by the signals including magmatic unrest of the volcano and the frequency of volcanic earthquakes swarm, the horizontal displacement and vertical uplift around the Mt. Baekdu, the temperature rises of hot springs, high ratios of
This study was conducted to delineate temporal and spatial patterns of potential risk of cold injury by combining the short-term cold hardiness of Campbell Early grapevine and the IPCC projected climate winter season minimum temperature at a landscape scale. Gridded data sets of daily maximum and minimum temperature with a 270m cell spacing ("High Definition Digital Temperature Map", HD-DTM) were prepared for the current climatological normal year (1971-2000) based on observations at the 56 Korea Meteorological Administration (KMA) stations using a geospatial interpolation scheme for correcting land surface effects (e.g., land use, topography, and elevation). The same procedure was applied to the official temperature projection dataset covering South Korea (under the auspices of the IPCC-SRES A2 and A1B scenarios) for 2071-2100. The dormancy depth model was run with the gridded datasets to estimate the geographical pattern of any changes in the short-term cold hardiness of Campbell Early across South Korea for the current and future normal years (1971-2000 and 2071-2100). We combined this result with the projected mean annual minimum temperature for each period to obtain the potential risk of cold injury. Results showed that both the land areas with the normal cold-hardiness (-150 and below for dormancy depth) and those with the sub-threshold temperature for freezing damage (
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70