• Restorative Dentistry and Endodontics
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• v.25 no.3
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• pp.459-473
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• 2000

Dental caries is the most common disease in the maxillofacial area. There are many factors contributing to its development, but complete understanding and prevention is not fully known. Since the structure of the coronal and root portion of the tooth is different, the remineralization and demineralization process is also known to be different. In this study, by using a partially saturated buffer solution, we created artificial enamel and dentin caries and evaluated mineral loss. A remineralization solution with four different degrees of saturation (degree of saturation ; group 1, 0.268, group 2, 0.309, group 3, 0.339, group 4, 0.390, PH 4.3, F-2ppm) was used on a demineralized specimen. The mineral precipitating quantity and depth was evaluated by using microradiography. Using an atomic force microscope (AFM), hydroxyapatite crystals of normal, demineralized, and remineralized enamel and dentin were evaluated. The results were as follows: 1. As the degree of saturation of the remineralizing solution increased, the mineral precipitation in the enamel was increased. In group 4, mineral precipitation was limited near the surface. 2. As the degree of saturation of the remineralizing solution increased, the mineral precipitation in the dentin was decreased and it occurred in a deeper portion. In group 4, however, mineral precipitation occurred on the surface and its quantity increased. 3. There was a statistically significant interaction between enamel and dentin mineral content changes on specimens treated with remineralization and demineralization solution (demineralization r=0.44, remineralization r=0.44, p<0.05). 4. Demineralized hydroxyapatite crystals showed central and peripheral dissolving and widening of intercrystal spaces under the AFM. 5. In dentin remineralization small crystal precipitation occurred between the large crystals. We conclude that by adjusting acidulated buffer solution's degree of saturation, we can control enamel and dentin remineralization. In addition, the AFM is highly useful in evaluating changes in remineralized and demineralized hydroxyapatite crystals.

• Proceedings of the SCSK Conference
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• 2003.09a
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• pp.700-718
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• 2003

Fructan, a polysaccharide existing in plants or produced by microorganisms, is a sugar polymer of fructose with $\beta$-2,6 linkages. In this study, we investigated some cosmeceutical properties of Fructan such as moisturizing effect, cell proliferation effect, anti-inflammation effect and cell cytotoxicity. Zymomonas mobilis, a microorganism producing Fructan, was cultured in a medium containing 10％ sucrose and 2％ yeast extract as main components for 24 hours at 37$^{\circ}C$ and pH 7. Fructan was obtained by precipitation from the cultured medium by adding alcohol (alcohol ratio of 1:3) after removing the enzyme by centrifuging. Fructan exhibited almost same moisturizing effect as hyaluronic acid and cell proliferation effect on human fibroblast and keratinocyte as well. Moreover, on cell proliferation test on bio-artificial skin constructed by 3-dimensional(3-D) culture after inducing primary skin inflammation with 0.5％ sodium lauryl sulfate (SLS), the 3-D artificial skin treated with 0.01 mg/ml, 0.05mg/ml of Fructan exhibited higher cell proliferation than the 3-D artificial skin treated with SLS only. On anti-inflammation test on 3-D artificial skin evaluated by measuring secreted quantity of interleukin-1$\alpha$ (IL-1$\alpha$) which is a pre-inflammatory mediator induced by SLS, the quantity of IL-1$\alpha$on the 3-D artificial skin treated with 0.01 mg/ml, 0.05mg/ml of Fructan was less than the one on the 3-D artificial skin treated with SLS only. As a result of these studies, Fructan has anti-inflammation effect against inflammatory reaction by a skin irritant as well as cell proliferation effect in bio-artificial skin. Fructan was also evaluated as a safe material without any toxicity in safety tests using fibroblasts and animals.

• Journal of Soil and Groundwater Environment
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• v.17 no.6
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• pp.1-8
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• 2012

This study is to suggest a few efficient ways of rainwater utilization, through monitoring and analyzing 143 rainwater storage systems and 110 artificial recharge systems, which are installed in the recommended facilities by law, among the rainwater harvesting systems in Jeju Island. In the case that catchment facilities are damaged, rainwater could be contaminated by leaves and debris so that the rates of rainwater usages come to be lower. It is possible that contaminated rainwater could contaminate artificial recharge wells or rainwater discharging out of the rainwater harvesting system could result in flood and damage for the downgradient area. For maintaining high quality of rainwater and increasing rainwater utilization rate, it is necessary to install screening facilities and purification plant functioning precipitation and filtration. Also, in order to efficiently preclude the overflowing rainwater exceeding storage capacity, it is recommended to associate rainwater storage tanks with artificial recharge well or infiltration trench facilities.

• Journal of Environmental Health Sciences
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• v.33 no.4
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• pp.299-305
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• 2007

Distribution of fecal pollution indicator bacteria and environmental parameter were investigated of urban artificial lakes. An average concentration of temperature, pH, SS, DO, $COD_{Mn}$, T-P, T-N, Turbidity, Chl-a were $21.5^{\circ}C$, 8.07, 116.70 mg/l, 8.66 mg/l, 2.24 mg/1, 0.52 mg/l, 1.71mg/l, 80.54 NTU, and 52.12 mg/l respectively. From the results of bivariate correlation analysis, fecal contamination indicator bacteria were found to be mutually correlated. And turbidity and suspended solid were correlated. From the results of principal component analysis, four factors were extracted. And four factors of variance explained up to 81.5 percentage. Factor 1 was pollution pattern by fecal contamination, factor 2 was physical pollution pattern by pollution source, factor 3 was natural pollution by precipitation, and factor 4 was artificial pollution pattern by organism.

• Journal of the Korean Ceramic Society
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• v.50 no.4
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• pp.275-279
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• 2013

The purpose of this study was to prepare calcium phosphate cement [CPC] for use in artificial bone. Nano-crystalline calcium phosphate [CaP] was precipitated at $37^{\circ}C$ using highly active $Ca(OH)_2$ in DI water and an aqueous solution of $H_3PO_4$. From the XRD measurements, the nano-CaP powder was close to apatitic TCP phase and the powders fired at $800^{\circ}C$ showed a critical ${\beta}$-TCP phase. A mixture of one mole $CaCO_3$ and two moles di-calcium phosphate was calcined at $1100^{\circ}C$ to make a reference ${\beta}$-TCP material. The nano-CaP powders were added to the normal ${\beta}$-TCP matrix and fired at $900^{\circ}C$ to make a ${\beta}$-TCP block. The sintered block showed improved mechanical strength, which was caused by the solid state interaction between nano-CaP and normal ${\beta}$-TCP.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.127-137
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• 2024

Physical models, which are often used for water resource management, are difficult to build and operate with input data and may involve the subjective views of users. In recent years, research using data-driven models such as machine learning has been actively conducted to compensate for these problems in the field of water resources, and in this study, an artificial neural network was used to simulate long-term rainfall runoff in the Osipcheon watershed in Samcheok-si, Gangwon-do. For this purpose, three input data groups (meteorological observations, daily precipitation and potential evapotranspiration, and daily precipitation - potential evapotranspiration) were constructed from meteorological data, and the results of training the LSTM (Long Short-term Memory) artificial neural network model were compared and analyzed. As a result, the performance of LSTM-Model 1 using only meteorological observations was the highest, and six LSTM-MLP ensemble models with MLP artificial neural networks were built to simulate long-term runoff in the Fifty Thousand Watershed. The comparison between the LSTM and LSTM-MLP models showed that both models had generally similar results, but the MAE, MSE, and RMSE of LSTM-MLP were reduced compared to LSTM, especially in the low-flow part. As the results of LSTM-MLP show an improvement in the low-flow part, it is judged that in the future, in addition to the LSTM-MLP model, various ensemble models such as CNN can be used to build physical models and create sulfur curves in large basins that take a long time to run and unmeasured basins that lack input data.

• Journal of the Korean earth science society
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• v.28 no.2
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• pp.214-226
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• 2007

Because precipitation is influenced by various atmospheric variables, it is highly nonlinear. Although precipitation predicted by a dynamic model can be corrected by using a nonlinear Artificial Neural Network, this approach has limits such as choices of the initial weight, local minima and the number of neurons, etc. In the present paper, we correct simulated precipitation by using a multiple linear regression (MLR) method, which is simple and widely used. First of all, Ensemble hindcast is conducted by the PNU/CME Coupled General Circulation Model (CGCM) (Park and Ahn, 2004) for the period from April to August in 1979-2005. MLR is applied to precipitation simulated by PNU/CME CGCM for the months of June (lead 2), July (lead 3), August (lead 4) and seasonal mean JJA (from June to August) of the Northeast Asian region including the Korean Peninsula $(110^{\circ}-145^{\circ}E,\;25-55^{\circ}N)$. We build the MLR model using a linear relationship between observed precipitation and the hindcasted results from the PNU/CME CGCM. The predictor variables selected from CGCM are precipitation, 500 hPa vertical velocity, 200 hPa divergence, surface air temperature and others. After performing a leave-oneout cross validation, the results are compared with the PNU/CME CGCM's. The results including Heidke skill scores demonstrate that the MLR corrected results have better forecasts than the direct CGCM result for rainfall.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1405-1423
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• 2021

Precipitation is one of the main factors that affect water and energy cycles, and its estimation plays a very important role in securing water resources and timely responding to water disasters. Satellite-based quantitative precipitation estimation (QPE) has the advantage of covering large areas at high spatiotemporal resolution. In this study, machine learning-based rainfall intensity models were developed using Himawari-8 Advanced Himawari Imager (AHI) water vapor channel (6.7 ㎛), infrared channel (10.8 ㎛), and weather radar Column Max (CMAX) composite data based on random forest (RF). The target variables were weather radar reflectivity (dBZ) and rainfall intensity (mm/hr) converted by the Z-R relationship. The results showed that the model which learned CMAX reflectivity produced the Critical Success Index (CSI) of 0.34 and the Mean-Absolute-Error (MAE) of 4.82 mm/hr. When compared to the GeoKompsat-2 and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN)-Cloud Classification System (CCS) rainfall intensity products, the accuracies improved by 21.73% and 10.81% for CSI, and 31.33% and 23.49% for MAE, respectively. The spatial distribution of the estimated rainfall intensity was much more similar to the radar data than the existing products.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2006.04a
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• pp.391-393
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• 2006

In this study, the performance of artificial neural network (ANN) models for estimating spatial distribution of water quality was evaluated using electric conductivity (EC) values in landfill site. For the ANN model development, feedforward neural networks and backpropagation algorithm with gradient descent method were used. In Test 1, the interpolation ability of the ANN model was evaluated. Results of the ANN model were more precise than those of the Kriging model. In Test 2, spatial distributions of EC values were predicted using precipitation data. Results seemed to be reasonable, however, they showed a limitation of ANN models in extrapolations.

• Journal of Pharmaceutical Investigation
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• v.24 no.4
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• pp.233-243
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• 1994

Precipitation was formed during the preparation of decoction from a mixture of Scutellariae Radix and Coptidis Rhizoma or Phellodendri Cortex according to the prescription of Hwang-ryean-hae-dog-tang. Baicalin and berberine were identified in coprecipitated product and these components were the active ingredients of two herbal medicine. The coprecipitated product was very slightly soluble in water and sparingly soluble in ethanol. The stoichiometric ratio of baicalin and berberine was found to be 1:1. The lipid-water partition coefficients of coprecipitated product were increased more than baicalin and berberine in chloroform, but were decreased in other organic solvents. The content of baicalin and berberine in coprecipitated product, determined by HPLC, were 23.08% and 26.75%, but the content of active ingredients in supernatant were 0.66% and 0.26%, respectively. The dissolution profile of baicalin of coprecipitated product was increased more than extract of Scutellariae Radix in artificial gastric juice, but was decreased in artificial intestinal juice. The dissolution rate of berberine of coprecipitated product was lower than extract of Coptidis Rhizoma in artificial gastric juice and intestinal juice commonly.