• 약학회지
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• 제41권2호
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• pp.195-202
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• 1997

The purpose of this study was to determine pharmacokinetic parameters of vancomycin using two point calculation(TPC) and Bayesian methods in 16 Korean normal volunteers and 15 g astric cancer patients. Nonparametric expected maximum(NPEM) algorithm for calculation of population pharmacokinetic parameter was used, and these parameters were applied for clinical pharmacokinetic parameters by Bayesian analysis. Vancomycin was administered 1.0g every 12 hrs for 3 days by IV infusion over 60 minutes. The volume of distribution(Vd), elimination rate constant(Kel) and total body clearance(CLt) of vancomycin in normal volunteers using TPC method were $0.34{\pm}0.06 L/kg,\; 0.19{\pm}0.01 hr^{-1}$ and $4.08 {\pm} 0.93 L/hr$, respectively, The Vd, Kel and CLt of vancomycin in gastric cancer patients using TPC method were $0.46 {\pm} 0.06 L/kg, 0.17{\pm}0.02 hr^{-1}$ and $4.84 {\pm} 0.57 L/hr$ respectively. There were significant differences(p<0.05) in Vd. Kel and CLt between normal volunteers and gastric cancer patients. Polpulation pharmacokinetic parameter, the slope(KS) of the relationship beetween Kel versus creatinine Clearance, and the Vd were $0.00157{\pm}0.00029(hr{\cdot}mL/min/1.73m^2)^{-1},\; 0.631 {\pm} 0.0036 L/kg$ in gastric cancer patients using NPEM algorithm respectively. The Vd and Kel were $0.63{\pm}0.005 L/kg, 0.15 {\pm}0.027 hr^{-1}$ for gastric cancer patients using Bayesian method. There were significant differences(p<0.05) in vancomycin pharmacokinetics between Bayesian and TPC methods. It is considered that the population parameter in the patient population is necessary for effective Bayesian method in clinical pharmacy practise.

• Asian-Australasian Journal of Animal Sciences
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• 제26권9호
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• pp.1237-1246
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• 2013

The objective of this study was to estimate variance components and genetic parameters for lactation milk yield (LY), lactation length (LL), average milk yield per day (YD), initial milk yield (IY), peak milk yield (PY), days to peak (DP) and parameters (ln(a) and c) of the modified incomplete gamma function (MIG) in an Ethiopian multibreed dairy cattle population. The dataset was composed of 5,507 lactation records collected from 1,639 cows in three locations (Bako, Debre Zeit and Holetta) in Ethiopia from 1977 to 2010. Parameters for MIG were obtained from regression analysis of monthly test-day milk data on days in milk. The cows were purebred (Bos indicus) Boran (B) and Horro (H) and their crosses with different fractions of Friesian (F), Jersey (J) and Simmental (S). There were 23 breed groups (B, H, and their crossbreds with F, J, and S) in the population. Fixed and mixed models were used to analyse the data. The fixed model considered herd-year-season, parity and breed group as fixed effects, and residual as random. The single and two-traits mixed animal repeatability models, considered the fixed effects of herd-year-season and parity subclasses, breed as a function of cow H, F, J, and S breed fractions and general heterosis as a function of heterozygosity, and the random additive animal, permanent environment, and residual effects. For the analysis of LY, LL was added as a fixed covariate to all models. Variance components and genetic parameters were estimated using average information restricted maximum likelihood procedures. The results indicated that all traits were affected (p<0.001) by the considered fixed effects. High grade $B{\times}F$ cows (3/16B 13/16F) had the highest least squares means (LSM) for LY ($2,490{\pm}178.9kg$), IY ($10.5{\pm}0.8kg$), PY ($12.7{\pm}0.9kg$), YD ($7.6{\pm}0.55kg$) and LL ($361.4{\pm}31.2d$), while B cows had the lowest LSM values for these traits. The LSM of LY, IY, YD, and PY tended to increase from the first to the fifth parity. Single-trait analyses yielded low heritability ($0.03{\pm}0.03$ and $0.08{\pm}0.02$) and repeatability ($0.14{\pm}0.01$ to $0.24{\pm}0.02$) estimates for LL, DP and parameter c. Medium heritability ($0.21{\pm}0.03$ to $0.33{\pm}0.04$) and repeatability ($0.27{\pm}0.02$ to $0.53{\pm}0.01$) estimates were obtained for LY, IY, PY, YD and ln(a). Genetic correlations between LY, IY, PY, YD, ln(a), and LL ranged from 0.59 to 0.99. Spearman's rank correlations between sire estimated breeding values for LY, LL, IY, PY, YD, ln(a) and c were positive (0.67 to 0.99, p<0.001). These results suggested that selection for IY, PY, YD, or LY would genetically improve lactation milk yield in this Ethiopian dairy cattle population.

• 한국인구학
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• 제30권3호
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• pp.1-31
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• 2007

한 중 일 3국은 순차적으로 경제발전을 이룩하는 한편 세계적으로 유례없이 급속한 인구 변천과정을 겪고 있다. 출산율 및 사망율의 저하는 인구의 고령화로 귀결되는데 이들 3국은 노인인구의 증가, 구조적 관성, 비노인인구의 감소 등에 따라 향후 반세기이내에 지구상에서 가장 고령화된 나라가 될 전망이다. 본 연구는 한 중 일 3국의 경우 인구의 고령화에 따른 유효(나이별 소비율의 차이를 고려한)부양부담이 어떻게 변동하고 있으며 이 경로는 유효부양부담을 최소화하는 적정인구경로에서 얼마나 떨어져 있는가를 논하고 있다. 그리고 인구정책을 출산장려정책으로 전환하고 그 결과 출산율이 정지인구수준으로 당장 회복된다고 할 때 인구부양구조는 장기적으로 어떻게 변할 것인지를 논하고, 그 대안 혹은 보완책으로 유효부양부담과 관련된 여타 파라메타의 값에 변화를 줄 수 있는 정책은 얼마나 효과가 있을지를 논하고 있다.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.220-225
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• 2021

Human population growth rate is an important parameter for real-world planning. Common approaches rely upon fixed parameters like human population, mortality rate, fertility rate, which is collected historically to determine the region's population growth rate. Literature does not provide a solution for areas with no historical knowledge. In such areas, machine learning can solve the problem, but a multitude of machine learning algorithm makes it difficult to determine the best approach. Further, the missing feature is a common real-world problem. Thus, it is essential to compare and select the machine learning techniques which provide the best and most robust in the presence of missing features. This study compares 17 machine learning techniques (base learners and ensemble learners) performance in predicting the human population growth rate of the country. Among the 17 machine learning techniques, random forest outperformed all the other techniques both in predictive performance and robustness towards missing features. Thus, the study successfully demonstrates and compares machine learning techniques to predict the human population growth rate in settings where historical data and feature information is not available. Further, the study provides the best machine learning algorithm for performing population growth rate prediction.

• 한국환경과학회지
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• 제28권1호
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• pp.19-35
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• 2019

This study investigates the performance of four Bayesian methods, Random Walk Metropolis (RWM), Hit-And-Run Metropolis (HARM), Adaptive Mixture Metropolis (AMM), and Population Monte Carlo (PMC), for estimating the parameters and uncertainties of probability rainfall distribution, and the results are compared with those of conventional parameter estimation methods; namely, the Method Of Moment (MOM), Maximum Likelihood Method (MLM), and Probability Weighted Method (PWM). As a result, Bayesian methods yield similar or slightly better results in parameter estimations compared with conventional methods. In particular, PMC can reduce parameter uncertainty greatly compared with RWM, HARM, and AMM methods although the Bayesian methods produce similar results in parameter estimations. Overall, the Bayesian methods produce better accuracy for scale parameters compared with the conventional methods and this characteristic improves the accuracy of probability rainfall. Therefore, Bayesian methods can be effective tools for estimating the parameters and uncertainties of probability rainfall distribution in hydrological practices, flood risk assessment, and decision-making support.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.18-21
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• 1995

In this paper we describe a new method for multimodal function optimization using genetic algorithms(GAs). We propose adaptation rules for GA parameters such as population size, crossover probability and mutation probability. In the self organizing genetic algorithm(SOGA), SOGA parameters change according to the adaptation rules. Thus, we do not have to set the parameters manually. We discuss about SOGA and those of other approaches for adapting operator probabilities in GAs. The validity of the proposed algorithm will be verified in a simulation example of system identification.

• Annals of Laboratory Medicine
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• 제38권6호
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• pp.503-511
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• 2018

Background: Sampling a healthy reference population to generate reference intervals (RIs) for complete blood count (CBC) parameters is not common for pediatric and geriatric ages. We established age- and sex-specific RIs for CBC parameters across pediatric, adult, and geriatric ages using secondary data, evaluating patterns of changes in CBC parameters. Methods: The reference population comprised 804,623 health examinees (66,611 aged 3-17 years; 564,280 aged 18-59 years; 173,732 aged 60-99 years), and, we excluded 22,766 examinees after outlier testing. The CBC parameters (red blood cell [RBC], white blood cell [WBC], and platelet parameters) from 781,857 examinees were studied. We determined statistically significant partitions of age and sex, and calculated RIs according to the CLSI C28-A3 guidelines. Results: RBC parameters increased with age until adulthood and decreased with age in males, but increased before puberty and then decreased with age in females. WBC and platelet counts were the highest in early childhood and decreased with age. Sex differences in each age group were noted: WBC count was higher in males than in females during adulthood, but platelet count was higher in females than in males from puberty onwards (P <0.001). Neutrophil count was the lowest in early childhood and increased with age. Lymphocyte count decreased with age after peaking in early childhood. Eosinophil count was the highest in childhood and higher in males than in females. Monocyte count was higher in males than in females (P <0.001). Conclusions: We provide comprehensive age- and sex-specific RIs for CBC parameters, which show dynamic changes with both age and sex.

• 유기물자원화
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• 제8권2호
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• pp.85-92
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• 2000

자연간석지 토양을 인공간석지에 인공간석지 토양을 자연간석지에 이식하고, 이식토양의 물리화학적 및 생물학적 특성의 변화를 추적하였다. 또한 실트함량과 유기물함량이 미생물현존량에 미치는 영향에 관해서 실내실험을 통하여 검토하였다. 자연간석지 토양을 인공간석지에 인공간석지 토양을 자연간석지에 이식한 결과, 실트함량, 유기물함량, 미생물현존량 및 토양중의 산화환원전위층은 시간의 경과와 함께 이식한 간석지의 토양구조와 동일하게 변이해 가는 것을 알았다. 또한 이식 토양중의 실트함량, 미생물현존량 및 유기물함량과는 높은 상관관계를 나타내었다. 실트함량 및 유기물함량의 증감과 함께 미생물현존량이 비례해서 증감하는 것을 알았다. 또한 실내실험 결과에서도 실트함량이나 유기물함량의 증가와 함께 미생물현존량이 증가하였다. 또한 그 원인은 실트함량이 증가함에 따른 결과라는 것을 알 수 있었다.

• 한국임상약학회지
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• 제26권4호
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• pp.312-317
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• 2016

Objective: Midazolam is mainly metabolized by cytochrome P450 (CYP) 3A. Inhibition or induction of CYP3A can affect the pharmacological activity of midazolam. The aims of this study were to develop a population pharmacokinetic (PK) model and evaluate the effect of CYP3A-mediated interactions among ketoconazole, rifampicin, and midazolam. Methods: Three-treatment, three-period, crossover study was conducted in 24 healthy male subjects. Each subject received 1 mg midazolam (control), 1 mg midazolam after pretreatment with 400 mg ketoconazole once daily for 4 days (CYP3A inhibition phase), and 2.5 mg midazolam after pretreatment with 600 mg rifampicin once daily for 10 days (CYP3A induction phase). The population PK analysis was performed using a nonlinear mixed effect model ($NONMEM^{(R)}$ 7.2) based on plasma midazolam concentrations. The PK model was developed, and the first-order conditional estimation with interaction was applied for the model run. A three-compartment model with first-order elimination described the PK. The influence of ketoconazole and rifampicin, CYP3A5 genotype, and demographic characteristics on PK parameters was examined. Goodness-of-fit (GOF) diagnostics and visual predictive checks, as well as bootstrap were used to evaluate the adequacy of the model fit and predictions. Results: Twenty-four subjects contributed to 900 midazolam concentrations. The final parameter estimates (% relative standard error, RSE) were as follows; clearance (CL), 31.8 L/h (6.0%); inter-compartmental clearance (Q) 2, 36.4 L/h (9.7%); Q3, 7.37 L/h (12.0%), volume of distribution (V) 1, 70.7 L (3.6%), V2, 32.9 L (8.8%); and V3, 44.4 L (6.7%). The midazolam CL decreased and increased to 32.5 and 199.9% in the inhibition and induction phases, respectively, compared to that in control phase. Conclusion: A PK model for midazolam co-treatment with ketoconazole and rifampicin was developed using data of healthy volunteers, and the subject's CYP3A status influenced the midazolam PK parameters. Therefore, a population PK model with enzyme-mediated drug interactions may be useful for quantitatively predicting PK alterations.

• 한국임상약학회지
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• 제18권1호
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• pp.60-67
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• 2008

This study aimed to compare a microparticle enzyme immunoassay (MEIA) with a liquid chromatography-tandem mass spectrometry (LC/MS/MS) technique for the measurement of tacrolimus concentrations in adult liver transplant recipients, to investigate how the assay choice influenced the population pharmacokinetics of tacrolimus and to identify patient characteristics that affected pharmacokinetic parameters in each assay. Tacrolimus concentrations from 29 liver (n=52 paired-samples) transplant recipients measured by both MEIA and LC/MS/MS were used to evaluate the performance of these methods in the clinical setting. Tacrolimus pharmacokinetics was studied independently using MEIA and LC/MS/MS data in 70 adult patients using a population approach performed with NONMEM. Patient characteristics which influenced pharmacokinetic parameters in each assay were compared. The relation between LC/MS/MS and MEIA measurements was best described by the regression equation MEIA=1.465*LC/MS/MS-1.336 (r=0.91). Multiple linear regression analysis showed significant inverse relationships between assay difference and hematocrit (Hct) (p<0.025) in liver graft recipients. In MEIA, the population estimate of tacrolimus CL/F and apparent volume of distribution (Vd/F) were found to be 10.1 L/h and 226 L, and in LC/MS/MS, 13 L/h and 305 L respectively. Neither patient's age, weight, gender, grafted hepatic weight, albumin concentration, nor markers of liver function influenced tacrolimus CL/F The final model of CL/F was found to be 10.1+(Hct/Hct mean)$^{12.0}$ in MEIA and 13+(1+Hct/578) in LC/MS/MS indicating that CL/F was influenced by hematocrit.