• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.2
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• pp.51-58
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• 2019

Purpose In in-vitro laboratories of nuclear medicine department, when the reagent lot or reagent lot changes Comparability test or parallel test is performed to determine whether the results between lots are reliable. The most commonly used standard domestic laboratories is to obtain %difference from the difference in results between two lots of reagents, and then many laboratories are set the standard to less than 20% at low concentrations and less than 10% at medium and high concentrations. If the range is deviated from the standard, the test is considered failed and it is repeated until the result falls within the standard range. In this study, several tests are selected that are performed in nuclear medicine in-vitro laboratories to analyze parallel test results and to establish criteria for customized percent difference for each test. Materials and Methods From January to November 2018, the result of parallel test for reagent lot change is analyzed for 7 items including thyroid-stimulating hormone (TSH), free thyroxine (FT4), carcinoembryonic antigen (CEA), CA-125, prostate-specific antigen (PSA), HBs-Ab and Insulin. The RIA-MAT 280 system which adopted the principle of IRMA is used for TSH, FT4, CEA, CA-125 and PSA. TECAN automated dispensing equipment and GAMMA-10 is used to measure insulin test. For the test of HBs-Ab, HAMILTON automated dispensing equipment and Cobra Gamma ray measuring instrument are used. Separate reagent, customized calibrator and quality control materials are used in this experiment. Results 1. TSH [%diffrence Max / Mean / Median] (P-value by t-test > 0.05) C-1(low concentration) [14.8 / 4.4 / 3.7 / 0.0 ] C-2(middle concentration) [10.1 / 4.2 / 3.7 / 0.0] 2. FT4 [%diffrence Max / Mean / Median] (P-value by t-test > 0.05) C-1(low concentration) [10.0 / 4.2 / 3.9 / 0.0] C-2(high concentration) [9.6 / 3.3 / 3.1 / 0.0 ] 3. CA-125 [%diffrence Max / Mean / Median] (P-value by t-test > 0.05) C-1(middle concentration) [9.6 / 4.3 / 4.3 / 0.3] C-2(high concentration) [6.5 / 3.5 / 4.3 / 0.4] 4. CEA [%diffrence Max / Mean / median] (P-value by t-test > 0.05) C-1(low concentration) [9.8 / 4.2 / 3.0 / 0.0] C-2(middle concentration) [8.7 / 3.7 / 2.3 / 0.3] 5. PSA [%diffrence Max / Mean / Median] (P-value by t-test > 0.05) C-1(low concentration) [15.4 / 7.6 / 8.2 / 0.0] C-2(middle concentration) [8.8 / 4.5 / 4.8 / 0.9] 6. HBs-Ab [%diffrence Max / Mean / Median] (P-value by t-test > 0.05) C-1(middle concentration) [9.6 / 3.7 / 2.7 / 0.2] C-2(high concentration) [8.9 / 4.1 / 3.6 / 0.3] 7. Insulin [%diffrence Max / Mean / Median] (P-value by t-test > 0.05) C-1(middle concentration) [8.7 / 3.1 / 2.4 / 0.9] C-2(high concentration) [8.3 / 3.2 / 1.5 / 0.1] In some low concentration measurements, the percent difference is found above 10 to nearly 15 percent in result of target value calculated at a lower concentration. In addition, when the value is measured after Standard level 6, which is the highest value of reagents in the dispensing sequence, the result would have been affected by a hook effect. Overall, there was no significant difference in lot change of quality control material (p-value>0.05). Conclusion Variations between reagent lots are not large in immunoradiometric assays. It is likely that this is due to the selection of items that have relatively high detection rate in the immunoradiometric method and several remeasurements. In most test results, the difference was less than 10 percent, which was within the standard range. TSH control level 1 and PSA control level 1, which have low concentration target value, exceeded 10 percent more than twice, but it did not result in a value that was near 20 percent. As a result, it is required to perform a longer period of observation for more homogenized average results and to obtain laboratory-specific acceptance criteria for each item. Also, it is advised to study observations considering various variables.

• Journal of environmental and Sanitary engineering
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• v.14 no.1
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• pp.17-23
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• 1999

This study was performed to survey the $SO_2$ level at several underground spaces connected to 5 subway stations (City Hall, Nam, Seoul stations, Hye Hwa and Ulchiro 1 Ga) in Seoul. The period of survey was from July to November, 1997.The results of the study were as follows; 1. The mean concentration of $SO_2$ was $0.057{\pm}0.015ppm$ in all subway stations. The highest $SO_2$ level among the five stations was $0.067{\pm}0.011 ppm$ at City Hall (P<0.01), and the highest with $0.071{\pm}0.013ppm$ at November (P<0.01).2. In underground shopping centers, the mean concentration of $SO_2$ was $0.112{\pm}0.059ppm$. 3. The mean concentration of $SO_2$ at evening with 0.057 pp and morning with 0.053 ppm were significantly higher than at noon with 0.043 ppm(P<0.05). 4. The $SO_2$ level of floor at Kang Nam station with 0.044 ppm was significantly higher than that of platform with 0.37 ppm(P<0.01). 5. For the City Hall stations, the line #1 and line #2 subway spaces show significantly different level of $SO_2$, 0.042ppm and 0.033 ppm respectively (P<0.05).

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.3
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• pp.300-309
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• 2008

Variations in PM10 concentration between 2000 and 2005 from 84 urban air monitoring stations operated by the government were analyzed. The K-means cluster analysis was attempted using annual average and the 99th percentile of daily averages as parameters. The results obtained by excluding Asian dust episode days were compared with those obtained by using all available data. In any cases, the cluster with the highest mean concentration was mostly composed of stations in Seoul and Gyeonggi. Annual average of the cluster with the highest mean concentration showed a distinct decreasing trend, but that excluding Asian dust episode days did not show such a trend. Without Asian dust episode days high concentrations of monthly averages in March and April were also not observed. The effect of Asian dust was more pronounced in the 99th percentile of daily averages. The 99th percentile of daily averages of the cluster with the highest mean concentration was the highest in June following downs in April and May.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.387-392
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• 1998

To establish a monthly data collection planning for the Ocean Scanning Multispectral Imager (OSMI), we have examined the global patterns of three impacting factors: pigment concentration, cloud cover, and sun glint. Other than satellite mission constraints (e.g., duty cycle), these three factors are considered critical for the OSMI data collection. The Nimbus-7 Coastal Zone Color Scanner (CZCS) monthly mean products and the International Satellite Cloud Climatology Project (ISCCP) monthly mean products (C2) were used for the analysis of pigment concentration and cloud cover distributions, respectively. And the monthly simulated patterns of sun glint were produced by performing the OSMI orbit prediction and the calculation of sun glint radiances at the top-of-atmosphere (TOA). Using monthly statistics (mean and/or standard deviation) of each factor in the above for a given 10$^{\circ}$ latitude by 10$^{\circ}$ longitude grid, we generated the priority map for each month. The priority maps of three factors for each month were subsequently superimposed to visualize the impact of three factors in all. The initial results illustrated that a large part of oceans in the summer hemisphere was classified into the low priority regions because of seasonal changes of clouds and sun illumination. Sensitivity tests were performed to see how cloud cover and sun glint affect the priority determined by pigment concentration distributions, and consequently to minimize their seasonal effects upon the data collection planning.

• The Journal of Korean Physical Therapy
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• v.14 no.2
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• pp.172-180
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• 2002

The purpose of this paper was to make an analysis of anaerobic power in professional female basketball players using the Wingate Test Method with bicycle ergometer. Twenty-three subjects(age $21.6\pm2.8years$, body height $178.0\pm7.4cm$, body weight $70.3\pm7.4kg$) were selected from professional female basketball team whose careers were over 10years and participated in this investigation. Each subject peformed a Wingate anaerobic power test to determine total work, peak power, mean power, fatigue index and blood lactate concentration. The following were obtained from result data analysis; 1. The Total Work of athletes was a $1128.7\pm120.6watt$ 2. The Peak Power of athletes was a $449.5\pm53.1watt$ 3. The Mean Power of athletes was a $369.1\pm39.4watt$ 4. The Fatigue Index of athletes was a $33.5\pm6.9\%$ 5. The blood lactate concentration was $1.85\pm0.85mM/L$ at the normal state and $3.16\pm1.53mM/L$ at the after Wingate test. The blood lactate concentration was $6.96\pm0.81mM/L$ after 3 minute and $6.95\pm1.05mM/L$ after 5 minutes.

• Journal of Korean Society of Forest Science
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• v.113 no.1
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• pp.66-72
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• 2024

Determining the nutrient stoichiometry in plant organs is critical for understanding nutrient uptake and cycling in forest ecosystems. This study evaluated nutrient concentrations and stoichiometry in various plant organs (stem, bark, branches, and foliage) of species found in four warm-temperate forests in southern Korea. Cryptomeria japonica D. Don (CJ), Quercus serrata Thunb. (QS), evergreen broadleaved tree species (EB), and bamboo spp. (BB) were destructively sampled to measure nutrient (C, N, and P) concentrations in the plant organs. The mean C concentration in the stem was significantly higher in CJ than in QS, BB, or EB, whereas the C concentration in the foliage was the lowest in BB. The mean foliar N and P concentrations were higher in BB than in EB or CJ. The mean stem C:N and C:P ratios were highest in CJ but were lowest in the foliage of BB. Overall, stems of all species showed a strong positive correlation between C concentration and dry weight, but a negative correlation between N and dry weight. The N and P concentrations of foliage and bark were strongly correlated, whereas those of the stem and branches were poorly correlated. Positive correlations were detected between the C:N and C:P ratios in bark and foliage. These results indicate the existence of intraspecific differences in nutrient requirements in warm-temperate forest species and add to the understanding of nutrient uptake and storage patterns in the organs of species growing in warm-temperate forests.

• Korean Journal of Veterinary Research
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• v.14 no.2
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• pp.179-184
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• 1974

The blood picture of 85 healthy race horses in Korea was investigated. The ranges and mean values of erythrocyte, hemoglobin, hematocrit value, mean corpuscular volume, mean corpuscular hemoglobin concentration, and total white blood cell count in the blood picture were determine. The respective mean value and standard deviation and age differences were as follows: 1. The erythrobyte count was shown as range of 6.20 to $11.32{\times}10^6/mm^3$ with mean of $8.61{\pm}1.92{\times}10^6/mm^3$(SD). The leucocyte count was shown as range 5.0 to $18.0{\times}10^3/mm^3$ with mean of $8.25{\pm}1.51{\times}10^3/mm^3$(SD). There were not significant. differences in age, 2. The mean value of hemoglobin was shown $13.9{\pm}1.7g/100ml(SD)$ ranging 9.8 to 16.8g/100ml. The mean value of hematocrit was shown $40.9{\pm}3.94ml/100ml(SD)$ ranging 26 to 54. There were not significant differences in age. 3. The mean corpuscular hemoglobin was shown as range of 11.8 to 22.2pg with mean of $16.9{\pm}4.69$(SD). The mean corpuscular volume was shown as range of 34.5 to $71.3cu{\mu}$ with mean of $49.0{\pm}7.32cu{\mu}$(SD). The mean corpuscular hemoglobin concentration was shown as range of 30.6 to 39.4 g/100 ml with mean of $34.6{\pm}2.36$(SD). There were not significant differences in age. 4. The correlation among erythrocyte count, hemoglobin and hematocrit value were observed as follows: Erythrocyte count and hemoglobin (+0.328), rythrocyte count and hematocrit vague (+0.319). A linear regression equation was shown as follows: Erythrocyte count and hemoglobin (Y=0.336x+10.977), erythrocyte count and hematocrit value (Y=0.655x+35.274). 5. The high correlation between hemoglobin and hematocrit vague was observed (r= +0.836). A linear regression equation was shown: (Y=1.948x+13.895).

• Journal of Environmental Impact Assessment
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• v.16 no.6
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• pp.533-542
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• 2007

The general characteristics of fine particle and meteorological analysis of high $PM_{10}$ concentration day which was over $100{\mu}g/m^3$ in busan were investigated for period of 2002 to 2006. Annual mean concentration including Asian dust day was $68.7{\mu}g/m^3$ in 2002, $54.6{\mu}g/m^3$ in 2003, $60.4{\mu}g/m^3$ in 2004, $58.3{\mu}g/m^3$ in 2005 and $58.8{\mu}g/m^3$ in 2006, respectively. Seasonal mean concentration was $73.4{\mu}g/m^3$ in Springtime, $56.8{\mu}g/m^3$ in Summertime, $55.5{\mu}g/m^3$ in Wintertime and $54.4{\mu}g/m^3$ in Falltime, respectively. Mean concentration for land use was 69.2 $37.0{\mu}g/m^3$ in industrial area, 64.2 $35.5{\mu}g/m^3$ in rural area, 62.6 $34.4{\mu}g/m^3$ in commercial area and 55.3 $33.8{\mu}g/m^3$ in residential area, respectively. Frequency of synoptic pattern for high $PM_{10}$ concentration day was 18 days(16.7%) in I type, 27 days(25.0%) in II type, 10 days(9.3%) in III type, 5 days(4.6%) in IV type, 13 days(12.0%) in V type and 29 days (26.9%) in VI type, respectively. Frequency of long range transport sector for high $PM_{10}$ concentration day was 9 days(8.3%) in I type, 64 days(59.5%) in II type, 34 days(31.5%) in III type, 1 days in IV type, 0 days, respectively.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.635-651
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• 2012

To produce a level-3 monthly composite image from daily level-2 Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-a concentration data set in the East Sea, we applied four average methods such as the simple average method, the geometric mean method, the maximum likelihood average method, and the weighted averaging method. Prior to performing each averaging method, we classified all pixels into normal pixels and abnormal speckles with anomalously high chlorophyll-a concentrations to eliminate speckles from the following procedure for composite methods. As a result, all composite maps did not contain the erratic effect of speckles. The geometric mean method tended to underestimate chlorophyll-a concentration values all the time as compared with other methods. The weighted averaging method was quite similar to the simple average method, however, it had a tendency to be overestimated at high-value range of chlorophyll-a concentration. Maximum likelihood method was almost similar to the simple average method by demonstrating small variance and high correlation (r=0.9962) of the differences between the two. However, it still had the disadvantage that it was very sensitive in the presence of speckles within a bin. The geometric mean was most significantly deviated from the remaining methods regardless of the magnitude of chlorophyll-a concentration values. Its bias error tended to be large when the standard deviation within a bin increased with less uniformity. It was more biased when data uniformity became small. All the methods exhibited large errors as chlorophyll-a concentration values dominantly scatter in terms of time and space. This study emphasizes the importance of the speckle removal process and proper selection of average methods to reduce composite errors for diverse scientific applications of satellite-derived chlorophyll-a concentration data.

• Journal of Veterinary Clinics
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• v.18 no.4
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• pp.334-340
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• 2001

This study was conducted to investigate changes in blood properties of high potassium (HK) phenotype Jindo dogs (15kg$\pm$2kg) after daily oral administration with water celery extracts (10 ml/kg) for 7 days. Blood samples were collected for three days in a row before administration of water celery extracts. After water celery extracts administration, blood samples were collected at 3h, 6h, 9h and then on daily basis until day 10 post administration (PA). At day 15, final sample was collected. Blood samples were analyzed on the basis of red blood cell (RBC), white blood cell (WBC), packed cell volume (PCV), hemoglobin (Hb) concentration, mean corpuscular volume(MCV), mean corpuscular hemoglobin concentration(MCHC), gluthathione concentration(GSH) and met-hemoglobin(Met-Hb) concentration. The significant changes (p<0.01, p<0.05) of RBCs were shown at 3 h to day 5, and days 7 and 9 after administration. PCV values were decreased form 3 h to day 10 after administration. Mean Hb concentration showed significant increase as 3 h to day 3, and day 6 to day 9 after administration. The significant changes (p<0.05) of WBCs were shown at 9 h and day 1 after administration. The increased numbers of MCV were detected at days 6 to 9 after administration (p<0.05, p<0.01). The significant changes of MCHC were shown at 9h and day 1 after administration. The significant increases (p<0.01, p<0.05) of GSH concentration were detected at days 1, 6 and 7 after administration. In Met-Hb concentration, the significant increases (p<0.05) occurred at only 9h and day 7 after administration, The significant increases (p<0.01, p<0.05) of reticulocyte were detected at days 2, 4, 5, 6 and 7. Data from blood samples collected at day 15 after administration showed that all of blood analysis results returned to normal level, compared to controls.