• Korean Journal of Ecology and Environment
• /
• v.43 no.3
• /
• pp.428-436
• /
• 2010

This study was to evaluate water quality characteristics and ecological health using a mulimetric fish model in Taehwa-River watershed during May~September 2009. The ecological health assessments were based on the Index of Biological Integrity (IBI) using fish community and the multimetric model of Qualitative Habitat Evaluation Index (QHEI). For the study, the models of IBI and QHEI were modified as 8 and 11 metric attributes, respectively. We also analyzed spatial patterns of chemical water quality over the period of 2000~2009, using the water chemistry dataset, obtained from the Ministry of Environment, Korea. Values of BOD and COD averaged $1.7\;mg\;L^{-1}$ (scope: $0.1{\sim}31.8\;mg\;L^{-1}$) and $3.6\;mg\;L^{-1}$ (scope: $0.4{\sim}33\;mg\;L^{-1}$), respectively during the study. Total nitrogen (TN) and total phosphorus (TP) averaged $2.8\;mg\;L^{-1}$ and $96.8\;{\mu}g\;L^{-1}$, respectively, indicating an eutrophic-hypertrophic state. Also, TN and TP showed longitudinal increases toward the downriver reach. In the watershed, QHEI values varied from 67.5 (fair condition) to 164.5 (good condition) by the criteria of US EPA (1993). There was a abruptly decreasing tendency from T9 site in the QHEI values. According to 1st and 2nd surveys of Taewha River, multimetric model values of IBI was averaged 26.1 (n=14) with "good" condition (B) and the spatial variation was evident. Our results suggest that the mainstream sites was getting worse health condition along the river gradient due to inputs of the point and non-point sources from the urban (Ulsan city). Overall, dataset of IBI, QHEI, and water chemistry indicated that the ecological river health showed a downriver decline and the pattern was closely associated with habitat degradations and chemical pollutions as the waters pass through the urban region.

• Journal of Korean Society of Forest Science
• /
• v.90 no.3
• /
• pp.380-387
• /
• 2001

The characteristics of ecological niche, breadth and overlap, for seventeen major tree species were evaluated in the natural deciduous forest in Mt. Chumbong area. Employed by the plot sampling method, the environmental gradient for vertical niche was based on the intensity of light within the forest, and that for horizontal niche was based on multi-dimensional resources in distribution pattern. The result showed that Fraxinus rhynchophylla had the highest value of vertical niche breadth and Maackia amurensis had the lowest, and Acer pseudo-sieboldianum had the highest value of horizontal niche breadth and Betula costata had the lowest. There was no significant correlation between both measures of niche breadth. However, the tolerance index for each species was positively correlated to the values of niche breadth. Spearman's rank correlation coefficients were applied to test the correlationship between the species ranks of tolerance index and those of two ecological niche breadths. The coefficient of $r_s=0.432$ ($P{\leq}0.1$) was not enough to support significant correlationship between the tolerance index and vertical niche breadth at the 95% probability. If Carpinus cordata, rarely reach canopy of the forest due to its own growth form, are excluded from the analysis, coefficient was calculated as $r_s=0.650$ ($P{\leq}0.01$), resulting in highly significant correlationship. The Spearman's rank correlation coefficient was $r_s=0.797$ ($P{\leq}0.01$) for tolerance indices and the values of horizontal niche breadth, indicating highly significant. Four distinctive species groups, produced by cluster analysis on the basis of ecological niche overlap for each pair of species, were in considerable accord with the positively associated species constellation pattern created by the inter-species association analysis.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.25 no.4
• /
• pp.81-96
• /
• 2020

Berthlot's reaction spectrophotometric method is generally used for the analysis of dissolved ammonium in seawater, but in recent years, a fluorescence method using an orthophthaldialdehyde-sulfite (OPA) fluorescent reagent is actively used internationally. In this study, we investigated the effects of the detection limit between the analysis methods, the reagent refractive index inherent in the spectrophotometric method, and the use of different calibration curves to understand the cause of the difference in dissolved ammonium concentration (about 0.31 𝜇M) observed in the seawater samples and a nutrient reference material between two institutions (KIOST (spectrophotometric method, one-order linear regression gradient only), Australia CSIRO (fluorescence method, quadratic formula)) conducted onboard the Australian R/V Investigator in 2017. The method detection limit (0.063 𝜇M) and the reagent refractive index background value (0.054 𝜇M) of the spectrophotometric method measured in this study could explain the difference in dissolved ammonium concentration values of the two institutes about 20% and 17%, respectively. However, when the concentration of the calibration curve of the spectrophotometric method was calculated using the same quadratic as the fluorescence method or the slope and intercept of linear regression, the difference in the dissolved ammonium concentration between the two institutions was reduced to less than the detection limit of the spectrophotometric method. Therefore, the difference in the concentration of dissolved ammonium between the two institutions, found in the nutrient reference materials and the seawater field sample during the international onboard nutrient inter-comparison experiment, may be attributed to be the effect of the different calibration curves used in the two methods rather than the effect of the difference in two analytical methods. When comparing the dissolved ammonium data from seawater samples in the future, it is recommended to pay attention to the information on the baseline, number of standard solutions, and calibration curve used in the analysis.

• Journal of Korean Society of Forest Science
• /
• v.83 no.2
• /
• pp.175-190
• /
• 1994

In order to get fundamental information for prediction of landslide hazard, both forest and site factors affecting slope stability were investigated in many areas of active landslides. Twelve descriptors were identified and quantified to develop the prediction model by multivariate statistical analysis. The main results obtained could be summarized as follows : The main factors influencing a large scale of landslide were shown in order of precipitation, age group of forest trees, altitude, soil texture, slope gradient, position of slope, vegetation, stream order, vertical slope, bed rock, soil depth and aspect. According to partial correlation coefficient, it was shown in order of age group of forest trees, precipitation, soil texture, bed rock, slope gradient, position of slope, altitude, vertical slope, stream order, vegetation, soil depth and aspect. The main factors influencing a landslide occurrence were shown in order of age group of forest trees, altitude, soil texture, slope gradient, precipitation, vertical slope, stream order, bed rock and soil depth. Two prediction models were developed by magnitude and frequency of landslide. Particularly, a prediction method by magnitude of landslide was changed the score for the convenience of use. If the total store of the various factors mark over 9.1636, it is evaluated as a very dangerous area. The mean score of landslide and non-landslide group was 0.1977 and -0.1977, and variance was 0.1100 and 0.1250, respectively. The boundary value between the two groups related to slope stability was -0.02, and its predicted rate of discrimination was 73%. In the score range of the degree of landslide hazard based on the boundary value of discrimination, class A was 0.3132 over, class B was 0.3132 to -0.1050, class C was -0.1050 to -0.4196, class D was -0.4195 below. The rank of landslide hazard could be divided into classes A, B, C and D by the boundary value. In the number of slope, class A was 68, class B was 115, class C was 65, and class D was 52. The rate of landslide occurrence in class A and class B was shown at the hige prediction of 83%. Therefore, dangerous areas selected by the prediction method of landslide could be mapped for land-use planning and criterion of disaster district. And also, it could be applied to an administration index for disaster prevention.

• Clinical and Experimental Pediatrics
• /
• v.48 no.6
• /
• pp.599-605
• /
• 2005

Purpose : The purpose of this study was to examine the causes, clinical courses and outcomes in children with acute respiratory distress syndrome(ARDS), and evaluate the physiologic variables as prognostic factors in the patients. Methods : Retrograde medical chart review was carried out in 24 patients who were diagnosed with ARDS at the pediatric intensive care unit(PICU) during 20-month period. Results : The incidence of ARDS among all PICU admission was 3.7 percent and the mortality rate was 37.5 percent, which was 14.8 percent of overall deaths in PICU. The most common causes of ARDS were pneumonia and sepsis. We found significant differences between survivors and nonsurvivors in $PaO_2/FiO_2$ ratio(P/F ratio), alveolar arterial oxygen gradient and oxygenation index(OI) on the second day from the onset of ARDS. Therapies for ARDS such as high frequency oscillator ventilation(HFOV), recruitment maneuver and low dose corticosteroid improved the P/F ratio and OI, especially in survivors. Conclusion : The mortality rate of children with ARDS was 37.5 percent; an important cause of death in PICU. HFOV, recruitment maneuver and low dose corticosteroid seemed to be effective in pediatric ARDS. The P/F ratio, alveolar arterial oxygen gradient and OI on the second day from the onset of ARDS may be useful as prognostic factors.

• Korean Journal of Soil Science and Fertilizer
• /
• v.40 no.4
• /
• pp.311-325
• /
• 2007

The concept of metal bioavailability, rather than total metal in soils, is increasingly becoming important for a thorough understanding of risk assessment and remediation. This is because bioavailable metals generally represented by the labile or soluble metal components existing as either free ions or soluble complexed ions are likely to be accessible to receptor organismsrather than heavy metals tightly bound on soil surface. Consequently, many researchers have investigated the bioavailability of metals in both soil and solution phases together with the key soil properties influencing bioavailability. In order to study bioavailability changes various techniques have been developed including chemical based extraction (weak salt solution extraction, chelate extraction, etc.) and speciation of metals using devices such as ion selective electrode (ISE) and diffusive gradient in the thin film (DGT). Changes in soil metal bioavailability typically occur through adsorption/desorption reactions of metal ions exchanged between soil solution and soil binding sites in response to changes in environment factors such as soil pH, organic matter (OM), dissolved organic carbon (DOC), low-molecular weight organic acids (LMWOAs), and index cations. Increasesin soil pH result in decreases in metal bioavailability through adsorption of metal ions on deprotonated binding sites. Organic matter may also decrease metal bioavailability by providing more negatively charged binding sites, and metal bioavailability can also be decreases as concentrations of DOC and LMWOAs increase as these both form strong chelate complexeswith metal ions in soil solution. The interaction of metal ions with these soil properties also varies depending on the soil and metal type.

• Asian-Australasian Journal of Animal Sciences
• /
• v.28 no.1
• /
• pp.50-57
• /
• 2015

This study was conducted to investigate the effect of soybean meal (SM) and soluble starch (SS) on biogenic amine production and microbial diversity using in vitro ruminal fermentation. Treatments comprised of incubation of 2 g of mixture (expressed as 10 parts) containing different ratios of SM to SS as: 0:0, 10:0, 7:3, 5:5, 3:7, or 0:10. In vitro ruminal fermentation parameters were determined at 0, 12, 24, and 48 h of incubation while the biogenic amine and microbial diversity were determined at 48 h of incubation. Treatment with highest proportion of SM had higher (p<0.05) gas production than those with higher proportions of SS. Samples with higher proportion of SS resulted in lower pH than those with higher proportion of SM after 48 h of incubation. The largest change in $NH_3$-N concentration from 0 to 48 h was observed on all SM while the smallest was observed on exclusive SS. Similarly, exclusive SS had the lowest $NH_3$-N concentration among all groups after 24 h of incubation. Increasing methane ($CH_4$) concentrations were observed with time, and $CH_4$ concentrations were higher (p<0.05) with greater proportions of SM than SS. Balanced proportion of SM and SS had the highest (p<0.05) total volatile fatty acid (TVFA) while propionate was found highest in higher proportion of SS. Moreover, biogenic amine (BA) was higher (p<0.05) in samples containing greater proportions of SM. Histamines, amine index and total amines were highest in exclusive SM followed in sequence mixtures with increasing proportion of SS (and lowered proportion of SM) at 48 h of incubation. Nine dominant bands were identified by denaturing gradient gel electrophoresis (DGGE) and their identity ranged from 87% to 100% which were mostly isolated from rumen and feces. Bands R2 (uncultured bacterium clone RB-5E1) and R4 (uncultured rumen bacterium clone L7A_C10) bands were found in samples with higher proportions of SM while R3 (uncultured Firmicutes bacterium clone NI_52), R7 (Selenomonas sp. MCB2), R8 (Selenomonas ruminantium gene) and R9 (Selenomonas ruminantium strain LongY6) were found in samples with higher proportions of SS. Different feed ratios affect rumen fermentation in terms of pH, $NH_3$-N, $CH_4$, BA, volatile fatty acid and other metabolite concentrations and microbial diversity. Balanced protein and carbohydrate ratios are needed for rumen fermentation.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_1
• /
• pp.655-667
• /
• 2023

Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R²), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R² of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.37 no.8
• /
• pp.975-981
• /
• 2013

A robust optimization is only one of the ways to minimize the effects of variances in design variables on the objective functions at the preliminary design stage. To predict the variances and to formulate the probabilistic constraints are the most important procedures for the robust optimization formulation. Though several methods such as the process capability index and the six sigma technique were proposed for the prediction and formulation of the variances and probabilistic constraints, respectively, there are few attempts using a percent defective which has been widely applied in the quality control of the manufacturing process for probabilistic constraints. In this study, the robust optimization for a lower control arm of automobile vehicle was carried out, in which the design space showing the mean and variance sensitivity of weight and stress was explored before robust optimization for a lower control arm. The 2nd order Taylor expansion for calculating the standard deviation was used to improve the numerical accuracy for predicting the variances. Simplex algorithm which does not use the gradient information in optimization was used to convert constrained optimization into unconstrained one in robust optimization.

• Asian-Australasian Journal of Animal Sciences
• /
• v.27 no.8
• /
• pp.1131-1140
• /
• 2014

This research focused on the effects of different doses of Bacillus subtilis KN-42 on the growth performance, diarrhea incidence, faecal bacterial flora, and the relative number of Lactobacillus and Escherichia coli in faeces of weaned piglets to determine whether the strain can serve as a candidate antimicrobial growth promoter. A total of 360 piglets (initial body weight $7.14{\pm}0.63$ kg) weaned at $26{\pm}2$ days of age were randomly allotted to 5 treatment groups (4 pens per treatment with 18 pigs per pen) for a 28-day trial. Dietary treatments were basal diet without any antimicrobial (negative control; NC), basal diet supplemented with 120 mg/kg feed of neomycin sulfate (positive control; PC) and basal diet supplemented with $2{\times}10^9$ (L), $4{\times}10^9$ (M) and $20{\times}10^9$ (H) CFU/kg feed of B. subtilis KN-42. During the overall period, average daily gain and feed efficiency of piglets were higher in groups PC, M, and H than those in group NC (p<0.05), and all probiotics and antibiotics groups had a lower diarrhea index than group NC (p<0.05). The 16S rDNA gene-based methods were used to analyze faecal bacterial flora on day 28 of experiment. The result of denaturing gradient gel electrophoresis analysis showed that supplementation of B. subtilis KN-42 to the diet changed the bacterial communities, with a higher bacterial diversity and band number in group M than in the other four groups. Real-time polymerase chain reaction analysis showed that the relative number of Lactobacillus were higher in groups PC and H than in group NC (p<0.05), and the supplemented B. subtilis KN-42 to the diet also reduced the relative number of E. coli (p<0.05). These results suggest that dietary addition of B. subtilis KN-42 can improve the growth performance and gastrointestinal health of piglets.