• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.12
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• pp.1923-1930
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• 2004

This paper presents digital microflow controllers(DMFC), where a fluidic digital-to-analog converter(DAC) is used to achieve high-linearity, fine-level flow control for applications to precision biomedical dosing systems. The fluidic DAC, composed of binary-weighted flow resistance, controls the flow-rate based on the ratio of the flow resistance to achieve high-precision flow-rate control. The binary-weighted flow resistance has been specified by a serial or a parallel connection of an identical flow resistor to improve the linearity of the flow-rate control, thereby making the flow-resistance ratio insensitive to the size uncertainty in flow resistors due to micromachining errors. We have designed and fabricated three different types of 4-digit DMFC: Prototype S and P are composed of the serial and the parallel combinations of an identical flow resistor, while Prototype V is based on the width-varied flow resistors. In the experimental study, we perform a static test for DMFC at the forward and backward flow conditions as well as a dynamic tests at pulsating flow conditions. The fabricated DMFC shows the nonlinearity of 5.0% and the flow-rate levels of 16(2$^{N}$) for the digital control of 4(N) valves. Among the 4-digit DMFC fabricated with micromachining errors, Prototypes S and P show 27.2% and 27.6% of the flow-rate deviation measured from Prototype V, respectively; thus verifying that Prototypes S and P are less sensitive to the micromachining error than Prototype V.V.

• Bulletin of the Korean Chemical Society
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• v.32 no.3
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• pp.977-980
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• 2011

A new analytical method for measurement of 3,4-dihydroxyphenylalanine (DOPA) in human urine was developed. DOPA from an aqueous solution was converted into an ethoxycarbonyl (EOC) derivative. A tertbutyldimethylsilyl (TBDMS) reaction under anhydrous conditions was then attempted for analysis by gas chromatography-mass spectrometry in selected ion monitoring mode. A new mass spectral data on DOPA as a tri-EOC/mono-TBDMS derivative was built. This method showed good linearity (r ${\geq}$ 0.999), precision (% relative standard deviation = 3.1-9.2), and accuracy (% relative error = -7.2-8.8), with a detection limit of 0.05 ng/mL. This selective and accurate method of DOPA analysis will be useful for biochemical monitoring of various neurological disorders including Parkinson's disease in biological fluids.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.3
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• pp.262-276
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• 2018

Models to predict Leaf Wetness Duration (LWD) were evaluated using the observed meteorological and dew data at the 11 citrus orchards in Jeju, South Korea from 2016 to 2017. The sensitivity and the prediction accuracy were evaluated with four models (i.e., Number of Hours of Relative Humidity (NHRH), Classification And Regression Tree/Stepwise Linear Discriminant (CART/SLD), Penman-Monteith (PM), Deep-learning Neural Network (DNN)). The sensitivity of models was evaluated with rainfall and seasonal changes. When the data in rainy days were excluded from the whole data set, the LWD models had smaller average error (Root Mean Square Error (RMSE) about 1.5hours). The seasonal error of the DNN model had the similar magnitude (RMSE about 3 hours) among all seasons excluding winter. The other models had the greatest error in summer (RMSE about 9.6 hours) and the lowest error in winter (RMSE about 3.3 hours). These models were also evaluated by the statistical error analysis method and the regression analysis method of mean squared deviation. The DNN model had the best performance by statistical error whereas the CART/SLD model had the worst prediction accuracy. The Mean Square Deviation (MSD) is a method of analyzing the linearity of a model with three components: squared bias (SB), nonunity slope (NU), and lack of correlation (LC). Better model performance was determined by lower SB and LC and higher NU. The results of MSD analysis indicated that the DNN model would provide the best performance and followed by the PM, the NHRH and the CART/SLD in order. This result suggested that the machine learning model would be useful to improve the accuracy of agricultural information using meteorological data.

• Bulletin of the Korean Chemical Society
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• v.32 no.7
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• pp.2418-2422
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• 2011

The enantiomeric separation of lactic acid for its absolute configuration has become important task for understanding its biological origin and metabolic process involved in the formation of lactic acid. It involves the conversion of enantiomers as diastereomeric O-pentafluoropropionylated (S)-(+)-3-methyl-2-butyl ester and the direct separation by gas chromatography-mass spectrometry on a achiral capillary column. The (R)- and (S)-lactic acids were completely separated with a high resolution of 1.9. The newly developed method showed good linearity (r ${\geq}$ 0.999), precision (% relative standard deviation = 3.4-6.2), and accuracy (% relative error = -7.7-1.4) with the detection limit of 0.011 ${\mu}g/mL$. When the method was applied to determine the absolute configuration of lactic acid in Lactobacillus delbrueckii subsp. lactis 304 (LAB 304), the composition (%) of (R)-lactic acid in the cell pellet and in the culture medium were $89.0{\pm}0.1$ and $78.2{\pm}0.4$, respectively. Thus, it was verified that the present method is useful for the identification and composition test of lactic enantiomers in microorganisms.

• YAKHAK HOEJI
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• v.42 no.5
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• pp.473-479
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• 1998

Lovastatin (LOVA), a fungal metabolite isolated from cultures of Aspergillus terreus, is a competitive HMG-CoA reductase inhibitor used for the treatment of primary hyper cholesterolemia, and has also been shown to suppress growth in a variety of non-glioma tumor cell lines. A sensitive reversed-phase high-perfonnance liquid chromatographic method with ultraviolet (UV) absorbance detection has been developed to quantitate LOVA in human plasma and urine samples using liquid-liquid extraction procedure. Baseline separation of LOVA and internal standard, simvastatin was achieved on a Novapak $C_{18}$ analytical column with a mobile phase containing 0.025M $NaH_2PO_4$: CAN (35:65, v/v%), adjusted pH to 4.5. The flow rate was set at 1.5ml/min, and the column effluent was monitored by a UV detection at 238nm. The limit of quantification was determined to be 0.5${\mu}$g/ml while extraction efficiency of LOVA ranged from 73.4-82.9% at LOVA concentrations of 0.5 to 10${\mu}$g/ml. Good linearity with correlation coefficients greater than 0.999 was obtained in the range of LOVA concentrations from 0.5 to 10${\mu}$g/ml. The accuracy and the precision were proven excellent with relative standard deviation (RSD, %) and relative error (RE, %) of less than 4.2 and 4.0, respectively. Intraday precision, evaluated at five LOVA concentrations (0.5, 1, 2, 5, 10${\mu}$g/ml) and expressed as RSD ranged from 0-1.82% while the interday precision at the same concentrations ranged from 0.7-10.5%. The analytical method described was then successfully employed for the determination of LOVA concentrations in plasma samples obtained during a phase II clinical trial using high doses of LOVA (30-40mg/kg/day). This method could be further utilized for the ongoing pharmacolkinetic studies and therapeutic drug monitoring of the high-dose LOVA therapy in adenocarcinoma patients.

• YAKHAK HOEJI
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• v.56 no.4
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• pp.222-229
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• 2012

In order to determine acetylcholine and choline in the biological samples, the specific enzymes of acetylcholinesterase (AChE) and choline oxidase (ChO), which utilize acetylcholine and choline as substrates, were employed to convert substrates to $H_2O_2$. The produced $H_2O_2$ was coupled to 4-aminoantipyrine/phenol with peroxidase (PO) yielding quinoneimine dye which was measured at 508 nm. In the present enzymatic spectrophotometric analysis the product at the equilibrium state was measured considering accuracy, precision, time and cost of the analysis. The developed analytical method yielded good linearity (calibration curve; $A_{508}$=9534[acetylcholine]+0.009, correlation coefficient ($R^2$); 0.999) with detection limit of $1.11{\times}10^{-7}M$, reasonable precision (relative standard deviation; 0.10~1.62% at $2.5{\times}10^{-6}M{\sim}1.25{\times}10^{-4}M$) and accuracy (relative error; -0.24~0.97% at $4.13{\times}10^{-6}M{\sim}1.01{\times}10^{-4}M$) for acetylcholine chloride standard solution. The concentrations of acetylcholine and choline in human serum were found as $3.20{\times}10^{-5}M$ and $1.14{\times}10^{-4}M$, respectively. The brain tissues of Sprague-Dawley strain rat contained 9.82${\mu}g/g$ of acetylcholine and 6.53 ${\mu}g/g$ of choline in the cerebrum, while 7.37 ${\mu}g/g$ of acetylcholine and 5.34 ${\mu}g/g$ of choline in the cerebellum.

• Progress in Medical Physics
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• v.11 no.2
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• pp.123-130
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• 2000

The performance of an electrometer directly affects on the accuracy and precision in radiation dosimetry. This study is to list of the quality control for maintaining performance and to perform evaluation tests of an electrometer. Performance tests selected include proper polarizing voltages, warm-up and equalization time, leakages, long-term stability, linearity, and effect of ambient conditions. An electrometer connected with a rigid stem ionization chamber was evaluated with a Strontium-90 check device. Bias voltage was measured directly on the input socket. Equalization time is the time required for reaching threshold of charged state after the power is on or the bias voltage is changed. Pre- and post-signal leakages are defined as the accumulation of signal with no exposure and after exposure, respectively. Over three months period, the electrometer's long-term stability was measured by comparison of the temperature-pressure corrected readings. Linearity was expressed as the deviation of readings from multiple short exposures from one continuous exposure. Effect of ambient conditions was expressed as the zero drift of the electrometer over 17-34$^{\circ}C$ temperature ranges. For two nominal values, 300 and 500 volts, measured voltages were lower by 2.5 and 5.8%, respectively. The warm-up time, 20 minutes, was longer than the lamp time by 9 minutes and the equalization time was less than 1 minute. Without exposure, the zero-drift was 0.002 scale-unit in 15 minutes and the leakage after 10 minutes exposure was minimal. The IQ-4 was stable over 99.4% for three-month periods. Deviation from the linearity was 0.9% for measurement scale, 0.000-9.991. Over 17-34$^{\circ}C$ temperature range, the zero-drift was minimal, less than 0.2%. For a clinically-used electrometer, a list for the basic peformance evaluations is proposed. By running this program, the measurement error using an electrometer can be reduced and in turn the improvement in accuracy and precision of radiation dosimetry can be achieved.

• Analytical Science and Technology
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• v.31 no.6
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• pp.240-246
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• 2018

The present study analyzed standard samples of three types of aluminum matrix certified reference materials (CRM) using GD-MS. Calibration curves were constructed for 13 elements (Mg, Si, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ga, Sn, and Pb), with the slope representing the relative sensitivity factor (RSF). The x- and y-axes of the calibration curve represented ion beam ratio (IBR) and the authenticated value of the standard sample, respectively. In order to evaluate precision and linearity of the calibration curve, RSD and the coefficient of determination were calculated. Curve RSD for every element reflected high precision (within 10 %). For most elements, the coefficient of determination was ${\geq}0.99$, indicating excellent linearity. However, vanadium, nickel, and gallium curves exhibited relatively low linearity (0.90~0.95), likely due to their narrow concentration ranges. Standard RSF was calculated using the slope of the curve generated for three types of CRM. Despite vanadium, nickel, and gallium exhibiting low coefficients of determination, their standard RSF resembled that of the three types of CRM. Therefore, the RSF method may be used for element quantitation. Standard iron matrix samples were analyzed to verify the applicability of the aluminum matrix standard RSF, as well as to calculate the RSD-estimated error of the measured value relative to the actual standard value. Six elements (Al, Si, V, Cr, Mn, and Ni) exhibited an RSD of approximately 30 %, while the RSD of Cu was 77 %. In general, Cu isotopes are subject to interference: $^{63}Cu$ to $^{54}Fe^{2+}-^{36}Ar$ and $^{65}Cu$ to $^{56}Fe-Al^{3+}$ interference. Thus, the influence of these impurities may have contributed to the high RSD value observed for Cu. To reliably identify copper, the resolution should be set at ${\geq}8000$. However, high resolutions are inappropriate for analyzing trace elements, as it lowers ion permeability. In conclusion, quantitation of even relatively low amounts of six elements (Al, Si, V, Cr, Mn, and Ni) is possible using this method.

• Analytical Science and Technology
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• v.31 no.2
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• pp.96-105
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• 2018

This study aimed to improve the method for detecting eight secondary aliphatic amines (SAAs), so as to measure their concentrations in fresh water and tap water samples. NaOH (8 mL, 10 M) and benzenesulfonyl chloride (2 mL) were added to a water sample (200 mL), and the mixture was stirred at $80^{\circ}C$ for 30 min. An additional NaOH solution (10 mL) was added and the stirring was continued for another 30 min. The pH of the cooled mixture was adjusted to 5.5-6.0 by adding HCl (35 %), and the SAAs were extracted using dichloromethane (50 mL). This extraction was repeated once. The extract was then washed with $NaHCO_3$ (15 mL, 0.05 M) and dried over $Na_2SO_4$ (4 g). The extract was finally concentrated to 0.1 mL, of which $1{\mu}L$ was analyzed for SAAs by GC-MS. The linearity of the spike calibration curves was high ($r^2=0.9969-0.9996$). The detection limits of the method ranged from 0.01 to $0.20{\mu}g/L$, and its repeatability and reproducibility (expressed as relative standard deviation) were both less than 10 % (6.6-9.4 %). Its accuracy (measured in percentage error) ranged between 2.4 % and 6.1 %. The established method was applied to the analysis of five surface water and 82 tap water samples. Dimethylamine was the only SAA detected in all the water samples, and its average concentration was $0.79{\mu}g/L$ (range: $0.20-2.54{\mu}g/L$). Therefore, this study improved the analytical method for SAAs in surface water and tap water, and the regional and seasonal concentration distributions were obtained.