The seasonal variations of nitrifying bacterial population sampled from 3 sites in Moon-Chon reservoir were analyzed by in situ hybridization with fluorescently labeled rRNA-targeted oligonucleotide probes from August 2000 until July 2001. In addition, physico-chemical parameters such as temperature, pH, chi-a and DOC were measured to determine correlations between those factors and the size of nitrifying bacterial populations. Total bacterial numbers varied in the range of $0.8{\sim}1.5{\times}10^6\;cells/ml$ independent of sites and had the maximal values in March at all 3 stations. The ratio of eubacteria to total bacteria ranged from 44.9% to 79.5%, and the ratio of each nitrifying bacteria to eubacterial numbers reached only $1.0{\sim}7.4%$. The variations of ammonia-oxidizing bacteria ranged from $1.1{\times}10^4$ to $3.0{\times}10^4\;cells/ml$ without noticeable peak values whereas those of nitrite-oxidizing bacteria varied in $1.3{\sim}5.7{\times}10^4\;cells/ml$ with the increasing tendency in winter regardless of the sites. Moreover it was observed that the numbers of nitrite-oxidizing bacteria were higher than those of ammonia-oxidizing bacteria. Total bacterial numbers correlated with water temperature (r = 0.355, p<0.05) and DOC (r = 0.58G, p<0.01) positively whereas nitrite-oxidizing bacteria correlated with temperature (r = -0.416, p<0.05) and pH (r = -0.568, p = 0.001) negatively. In addition, DOC represented good correlations with eubacterial numbers (r = 0.448, p<0.01). These results indicate that temperature, DOC and pH might be one of the main factors affecting variations of bacterial populations in the aquatic ecosystem. It was also suggested that FISH method is a useful tool for detection of slow growing nitrifying bacteria.
Shim, JeongHee;Hwang, Jae Ran;Lee, Sang Yong;Kwon, Jung-No
Korean Journal of Environmental Biology
/
v.32
no.4
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pp.297-305
/
2014
In order to understand the contribution of seaweed aquaculture to nutrients and carbon cycles in coastal environments, we measured the nutrients & carbon uptake rates of Porphyra yezoensis Ueda sampled at Nakdong-River Estuary using a chamber incubation method from November 2011 to April 2012. It was observed that the production rate of dissolved oxygen by P. yezoensis (n=30~40) was about $68.8{\pm}46.0{\mu}mol\;{g_{FW}}^{-1}h^{-1}$ and uptake rate of nitrate, phosphate and dissolved inorganic carbon (DIC) was found to be $2.5{\pm}1.8{\mu}mol\;{g_{FW}}^{-1}h^{-1}$, $0.18{\pm}0.11{\mu}mol\;{g_{FW}}^{-1}h^{-1}$ and $87.1{\pm}57.3{\mu}mol\;{g_{FW}}^{-1}h^{-1}$, respectively. There was a positive linear correlation existed between the production rate of dissolved oxygen and the consumption rates of nitrate, phosphate and DIC, respectively, suggesting that these factors may serve as good indicators of P. yezoensis photosynthesis. Further, there was a negative logarithmic relationship between fresh weight of thallus and uptake rates of nutrients and $CO_2$, which suggested that younger specimens (0.1~0.3 g) were much more efficient at nutrients and $CO_2$ uptake than old specimens. It means that the early culturing stage than harvesting season might have more possibilities to be developed chlorosis by high rates of nitrogen uptake. However, N & C demanding rates of Busan and Jeollabuk-do, calculated by monthly mass production and culturing area, were much higher than those of Jeollanam-do, the highest harvesting area in Korea. Chlorosis events at Jeollabuk-do recently might have developed by the reason that heavily culture in narrow area and insufficient nutrients in maximum yield season (Dec.~Jan.) due mostly to shortage of land discharge and weak water circulation. The annual DIC uptake by P. yezoensis in Nakdong-River Estuary was estimated about $5.6{\times}10^3\;CO_2$ ton, which was about 0.03% of annual carbon dioxide emission of Busan City. Taken together, we suggest more research would be helpful to gain deep insight to evaluate the roles of seaweed aquaculture to the coastal nutrients cycles and global carbon cycle.
Until now, the pore size distribution, PSD, of soil profile has been calculated from soil moisture characteristic data by water release method or mercury porosimetry using the capillary rise equation. But the current methods are often difficult to use and time consuming. Thus, in this work, theoretical framework for an easy and fast technique was suggested to estimate the PSD from unsaturated hydraulic conductivity data in an undisturbed field soil profile. In this study, unsaturated hydraulic conductivity data were collected and simulated by the variation of soil parameters in the given boundary conditions (Brooks and Corey soil parameters, ${\alpha}_{BC}=1-5L^{-1}$, b = 1 - 10; van Genuchten soil parameters, ${\alpha}_{VG}=0.001-1.0L^{-1}$, m = 0.1 - 0.9). Then, $K_s$ (1.0 cm $h^{-1})$ was used as the fixed input parameter for the simulation of each models. The PSDs were estimated from the collected K(h) data by model simulation. In the simulation of Brooks-Corey parameter, the saturated hydraulic conductivity, $K_s$, played a role of scaling factor for unsaturated hydraulic conductivity, K(h) Changes of parameter b explained the shape of PSD curve of soil intimately, and a ${\alpha}_{BC}$ affected on the sensitivity of PSD curve. In the case of van Genuchten model, $K_s$ and ${\alpha}_{VG}$ played the role of scaling factor for a vertical axis and a horizontal axis, respectively. Parameter m described the shape of PSD curve and K(h) systematically. This study suggests that the new theoretical technique can be applied to the in situ prediction of PSD in undisturbed field soil.
Probing the electronic structures of crystalline Mg-silicates at high pressure is essential for understanding the various macroscopic properties of mantle materials in Earth's interior. Quantum chemical calculations based on the density functional theory are used to explore the atomic configuration and electronic structures of Earth materials at high pressure. Here, we calculate the partial density of states (PDOS) and O K-edge energy-loss near-edge structure (ELNES) spectra for $MgSiO_3$ perovskite at 25 GPa and 120 GPa using the WIEN2k program based on the full-potential linearized projected augmented wave (FP-LPAW) method. The calculated PDOS and O K-edge ELNES spectra for $MgSiO_3$ Pv show significant pressure-induced changes in their characteristic spectral features and relative peak intensity. These changes in spectral features of $MgSiO_3$ Pv indicate that the pressure-induced changes in local atomic configuration around O atoms such as Si-O, O-O, and Mg-O length can induce the significant changes on the local electronic structures around O atoms. The result also indicates that the significant changes in O K-edge features can results from the topological densification at constant Si coordination number. This study can provide a unique opportunity to understand the atomistic origins of pressure-induced changes in local electronic structures of crystalline and amorphous $MgSiO_3$ at high pressure more systematically.
Purpose: To investigate the relation of the gastric epithelial cell proliferation, apoptosis and genotypes of H. pylori in children. Methods: Histologic grading by updated Sydney system, PCNA immunostaining, TUNEL method and the genotypes (cagA, picB and iceA) by PCR were performed in H. pylori positive (N=20) and negative (N=20) gastric biopsy specimens. Results: PCNA index was significantly different between H. pylori positive children ($77.4{\pm}13.12$) and H. pylori negative children ($52.3{\pm}12.20$) (p=0.000). There were positive correlations between PCNA index and H. pylori density (r=0.624, p=0.000), polymorphonuclear neutrophil activity (r=0.460, p=0.005) and chronic inflammation (r=0.433, p=0.009). Apoptosis index of H. pylori positive children ($0.70{\pm}0.411$) was significantly higher than of H. pylori negative children ($0.14{\pm}0.201$) (p=0.000). Positive correlations between apoptosis index and H. pylori density (r=0.691, p=0.000), polymorphonuclear neutrophil activity (r=0.585, p=0.000) and chronic inflammation (r=0.535, p=0.001) were noted. As PCNA index increased, apoptosis index significantly increased (r=0.527, p=0.001). The positive rates of genotypes were cagA 90%, picB 75%, iceA1 60% and iceA2 15%, respectively. There were no significant correlations between the status of the genotypes and PCNA index, apoptosis index, the endoscopic findings and the histologic findings. Conclusion: PCNA index and apoptosis index in H. pylori positive children were higher than in H. pylori negative children but were not related to H. pylori genotypes. This study suggested that correlatively increased gastric epithelial cell proliferation and apoptosis are important to pathogenesis of H. pylori infection in children.
Background: Correct preoperative staging of esophageal cancer is a prerequisite for adequate treatment. We prospectively compared the accuracy of positron emission tomography (PET) with [fluorine-18]FDG in the staging of esophageal cancer to that of computed tomography (CT). Material and Method: The findings of FDG PET and of chest CT including lower neck and the upper abdomen of 20 biopsy-proven squamous cell carcinoma patients (male, 19; female, 1; mean age, 61) were compared with the pathologic findings obtained from a curative esophagectomy with lymph node dissection. Result: The sensitivities of FDG PET and CT for diagnosis of primary tumor were the same, 90.0% (18/20). Both FDG PET and CT failed to show the primary tumor in 2 of 20 patients; one had a 1cm sized carcinoma in situ and the other had T1 stage cancer. By using the results of the pathologic examinations of 193 removed lymph node groups, we calculated the diagnostic sensitivities, specificities and accuracies of PET and CT (*$\chi$2 p < 0.005). Sensitivity** Specificity Accuracy* PET 55.6%(30/54) 97.1%(135/139) 85.5%(165/193) CT 13.0%(7/54) 98.6%(137/139) 74.6%(144/193) One of four patients with a false-positive for PEThad had active pulmonary tuberculosis. Among the 24 tumor involved lymph node groups, PET failed to show tumor metastasis in 5 lymph node groups abutting the tumor and in 14 lymph node groups located where the decay correction was not performed. Conclusion: Based on the above findings, it is suggested that [F-18]FDG-PET is superior to CT in the detection of nodal metastases and in the staging of patients with esophageal cancer.
Shin, Kook-Sik;Lim, Woo-Jin;Lee, Sang Eun;Lee, Jae Seon;Cha, Geun Sig
Korean Journal of Soil Science and Fertilizer
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v.42
no.6
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pp.513-521
/
2009
The primary goal of this research was to develop an optimized analytical procedure for soil analysis based on ion-selective microelectrodes for agricultural purposes, which can perform on-site measurement of various ions in soil easily and rapidly. For the simple and rapid on-site diagnosis, an analysis of soil chemicals was performed employing a multicomponent-in-situ-extractant and an evaluation of ionselective microelectrodes were conducted through the regressive correlation method with a standard analytical approach widely employed in this area. Examination of sensor responses between various soil nutrient extractants revealed that 0.01M HCl and 1M LiCl provided the most ideal Nernstian response. However, 1M LiCl deteriorated the selective response for analytes due to high concentration (1M) of lithium cation. Thus, employing either 0.1M HCl as an extractant followed by 10 times dilution, or 0.01M HCl as an extractant without further dilution was chosen as the optimal extractant composition. A study of regressive correlation between results from ion-selective microelectrodes and those from the standard analytical procedure showed that analyses of $K^+$, $Na^+$, $Ca^{2+}$, and $NO_3{^-}$ showed the excellent consistency between two methods. However, the response for $NH_4{^+}$ suffered the severe interference from $K^+$. In addition, the selectivity for $Mg^{2+}$ over $Ca^{2+}$ was not sufficient enough since available ionophores developed so far do not provide such a high selectivity for $Mg^{2+}$. Therefore, as an agricultural on-site diagnostic instrument, the device in development requires further research on $NH_4{^+}$ analysis in the soil sample, development of $Mg^{2+}$-selective ionophore, and more detailed study focused on potassium, one of the most important plant nutrients.
Because the growth of paddy rice is affected by meteorological factors, the selection of appropriate meteorological variables is essential to build a rice yield prediction model. This paper examines the suitability of multiple meteorological datasets for the rice yield modeling in South Korea, 1996-2019, and a hindcast experiment for rice yield using a machine learning method by considering the nonlinear relationships between meteorological variables and the rice yield. In addition to the ASOS in-situ observations, we used CRU-JRA ver. 2.1 and ERA5 reanalysis. From the multiple meteorological datasets, we extracted the four common variables (air temperature, relative humidity, solar radiation, and precipitation) and analyzed the characteristics of each data and the associations with rice yields. CRU-JRA ver. 2.1 showed an overall agreement with the other datasets. While relative humidity had a rare relationship with rice yields, solar radiation showed a somewhat high correlation with rice yields. Using the air temperature, solar radiation, and precipitation of July, August, and September, we built a random forest model for the hindcast experiments of rice yields. The model with CRU-JRA ver. 2.1 showed the best performance with a correlation coefficient of 0.772. The solar radiation in the prediction model had the most significant importance among the variables, which is in accordance with the generic agricultural knowledge. This paper has an implication for selecting from multiple meteorological datasets for rice yield modeling.
Kim, Yeon-Mee;An, Seung-Man;Moon, Soo-Young;Kim, Hyeon-Soo;Jang, Dae-Hee
Journal of the Korean Institute of Landscape Architecture
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v.40
no.6
/
pp.148-160
/
2012
The main purpose of this paper is to deliver a climate analysis and evaluation method based on GIS by using airborne LiDAR data and Biotop type map and to provide spatial information of climate analysis and evaluation based on Biotop type Map. At first stage, the area, slope, slope length, surface, wind corridor function and width, and obstacle factors were analyzed to obtain cold/fresh air production and wind corridor evaluation. In addition, climate evaluation was derived from those two results in the second stage. Airborne LiDAR data are useful in wind corridor analysis during the study. Correlation analysis results show that ColdAir_GRD grade was highly correlated with Surface_GRD (-0.967461139) and WindCorridor_ GRD was highly correlated with Function_GRD (-0.883883476) and Obstacle_GRD (-0.834057656). Climate Evaluation GRID was highly correlated with WindCorridor_GRD (0.927554516) than ColdAir_GRD (0.855051646). Visual validations of climate analysis and evaluation results were performed by using aerial ortho-photo image, which shows that the climate evaluation results were well related with in-situ condition. At the end, we applied climate analysis and evaluation by using Biotop map and airborne LiDAR data in Gwangmyung-Shiheung City, candidate for the Bogeumjari Housing District. The results show that the aerial percentile of the 1st Grade is 18.5%, 2nd Grade is 18.2%, 3rd Grade is 30.7%, 4th Grade is 25.2%, and 5th Grade is 7.4%. This study process provided both the spatial analysis and evaluation of climate information and statistics on behalf of each Biotop type.
An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (Rrs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This Rrs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of Rrs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ Rrs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for Rrs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying Rrs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.
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