• Nutrition Research and Practice
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• v.8 no.4
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• pp.469-475
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• 2014

BACKGROUND/OBJECTIVE: The goal of the present study was to investigate the effects of moderate caloric restriction on ${\beta}$-cell function and insulin sensitivity in middle-aged obese Korean women. SUBJECTS/METHODS: Fifty-seven obese pre-menopausal Korean women participated in a 12-week calorie restriction program. Data on total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), triglycerides (TG), and fasting serum levels of glucose, insulin, C-peptide, blood pressure, leptin and anthropometrics were collected. A dietary intake assessment was based on three days of food recording. Additionally, ${\beta}$-cell function [homeostasis model assessment of ${\beta}$-cell (HOMA-${\beta}$), insulinogenic index (ISI), C-peptide:glucose ratio, and area under curve insulin/glucose ($AUC_{ins/glu}$)] and insulin sensitivity [homeostasis model assessment for insulin resistance (HOMA-IR), Quantitative insulin-sensitivity check index (QUICKI) and Matsuda index (MI)] were recorded. RESULTS: When calories were reduced by an average of 422 kcal/day for 12 weeks, BMI (-2.7%), body fat mass (-10.2%), and waist circumference (-5%) all decreased significantly (P < 0.05). After calorie restriction, weight, body fat percentage, hip circumference, BP, TC, HDL-C, LDL-C, plasma glucose at fasting, insulin at fasting and 120 min, $AUC_{glu}$ and the insulin area under the curve all decreased significantly (all P < 0.05), while insulin sensitivity (HOMA-IR, QUICKI and Matsuda index) measured by OGTT improved significantly (P < 0.01). CONCLUSIONS: Moderate weight loss due to caloric restriction with reduction in insulin resistance improves glucose tolerance and insulin sensitivity in middle-aged obese women and thereby may help prevent the development of type 2 diabetes mellitus.

• Journal of the Korean Statistical Society
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• v.27 no.3
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• pp.349-358
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• 1998

Consider the AR(1) model $X_{t}$=$\beta$ $X_{t-1}$+$\varepsilon$$_{t}$ where $\beta$ < 1 is an unknown parameter to be estimated and {$\varepsilon$$_{t}$} denotes the independent and identically distributed error terms with unknown common distribution function F. In this paper, a strong representation for the least absolute deviation (LAD) estimate of $\beta$ in AR(1) models is obtained under some mild conditions on F. on F.F.

• Journal of Food Hygiene and Safety
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• v.19 no.1
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• pp.19-24
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• 2004

Dose-response models in microbial risk assessment can be divided into biologically plausible models and empirical models. Biologically plausible models are formed by the assumptions in dose distribution of microbes, host sensitivity to microbes, and minimal infectious dose of microbes : there are Exponential model and $\beta$-Poisson model, representatively. Empirical models are mainly used to express the toxicity of chemicals : there are Weibull-Gamma model etc. Deviance function (Y) is used to fit available data to dose-response models, and some dose-response models for food-borne pathogens are developed in humans and experimental animals.

• The Pure and Applied Mathematics
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• v.5 no.2
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• pp.123-132
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• 1998

Let F and G denote the distribution functions of the failure times and the censoring variables in a random censorship model. Susarla and Van Ryzin(1978) verified consistency of $F_{\alpha}$, he NPBE of F with respect to the Dirichlet process prior D($\alpha$), in which they assumed F and G are continuous. Assuming that A, the cumulative hazard function, is distributed according to a beta process with parameters c, $\alpha$, Hjort(1990) obtained the Bayes estimator $A_{c,\alpha}$ of A under a squared error loss function. By the theory of product-integral developed by Gill and Johansen(1990), the Bayes estimator $F_{c,\alpha}$ is recovered from $A_{c,\alpha}$. Continuity assumption on F and G is removed in our proof of the consistency of $A_{c,\alpha}$ and $F_{c,\alpha}$. Our result extends Susarla and Van Ryzin(1978) since a particular transform of a beta process is a Dirichlet process and the class of beta processes forms a much larger class than the class of Dirichlet processes.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.835-843
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• 2008

In this paper, we investigate a Bayesian inference for software reliability models based on mean value functions which take the form of the mixture of beta distribution functions. The posterior simulation via the Markov chain Monte Carlo approach is used to produce estimates of posterior properties. Its applicability is illustrated with two real data sets. We compute the predictive distribution and the marginal likelihood of various models to compare the performance of them. The model comparison results show that the model based on the beta-mixture performs better than other models.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.1
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• pp.51-58
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• 1991

This paper presents a single-echelon, single item, stochastic lead time and static demand inventory model for situations in which, during the stockout period, a fraction ${\beta}$ of the demand is backordered and the remaining fraction $(1-{\beta})$ is lost. In this situations, an objective function representing the average annual cost of inventory system is obtained by defining a time-proportional backorder cost and a fixed penalty cost per unit lost. The optimal operating policy variables minimizing the average annual cost are calculated iteratively. At the extremet ${\beta}=1$, the model presented reduces to the usual backorder case. A numerical example is solved to illustrate the algorithm developed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.78-82
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• 2022

Phenology determines the timing of crop development, and the timing of phenological events is strongly influenced by the temperature during the growing season. In process-based model, leaf area is simulated dynamically by coupling of morphology and phenology module. Therefore, the prediction of leaf appearance rate and final leaf number affects the performance of whole crop model. The dataset for the model equation was collected from SPA R chambers with five different temperature treatments. Beta distribution function (proposed by Yan and Hunt (1999)) was used for describing the leaf appearance rate as a function of temperature. The optimum temperature and the critical value were estimated to be 26.0℃ and 35.3℃, respectively. For evaluation of the model, the accumulated number of onion leaves observed in a temperature gradient chamber was compared with model estimates. The model estimate is the result of accumulating the daily increase in the number of onion leaves obtained by inputting the daily mean temperature during the growing season into the temperature model. In this study, the coefficient of determination (R²) and RMSE value of the model were 0.95 and 0.89, respectively.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.65-71
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• 2019

The propose of this study has been conducted to examine expression of c-Myc and Thymosin-${\beta}4$ in liver cirrhosis model from liver fibrosis and For the method of study, the experiment was conducted in 2 groups; liver cirrhosis model experiment group due to liver fibrosis and control group with distilled water. This study outcome showed that liver cirrhosis model experiment group had significantly higher expression of c-Myc and Thymosin-${\beta}4$. with changes to hepatic tissue of special staining and electron microscopy. In conclusion, in clinical tests regarding liver function, molecular evaluation of c-Myc and Thymosin-${\beta}4$ and their expression along with serological change and histological assessment can be utilized as a reference for diagnosing liver disease for prevention and diagnosis of the disease, Based on this research in the future, we will carry out an in-depth study by adding the types of experimental groups and related genes.

• Nutrition Research and Practice
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• v.10 no.3
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• pp.274-281
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• 2016

BACKGROUND/OBJECTIVES: The accumulation of amyloid-${\beta}$ ($A{\beta}$) in the brain is a hallmark of Alzheimer's disease (AD) and plays a key role in cognitive dysfunction. Perilla frutescens var. japonica extract (PFE) and its major compound, rosmarinic acid (RA), have shown antioxidant and anti-inflammatory activities. We investigated whether administration of PFE and RA contributes to cognitive improvement in an $A{\beta}_{25-35}$-injected mouse model. MATERIALS/METHODS: Male ICR mice were intracerebroventricularly injected with aggregated $A{\beta}_{25-35}$ to induce AD. $A{\beta}_{25-35}$-injected mice were fed PFE (50 mg/kg/day) or RA (0.25 mg/kg/day) for 14 days and examined for learning and memory ability through the T-maze, object recognition, and Morris water maze test. RESULTS: Our present study demonstrated that PFE and RA administration significantly enhanced cognition function and object discrimination, which were impaired by $A{\beta}_{25-35}$, in the T-maze and object recognition tests, respectively. In addition, oral administration of PFE and RA decreased the time to reach the platform and increased the number of crossings over the removed platform when compared with the $A{\beta}_{25-35}$-induced control group in the Morris water maze test. Furthermore, PFE and RA significantly decreased the levels of nitric oxide (NO) and malondialdehyde (MDA) in the brain, kidney, and liver. In particular, PFE markedly attenuated oxidative stress by inhibiting production of NO and MDA in the $A{\beta}_{25-35}$-injected mouse brain. CONCLUSIONS: These results suggest that PFE and its active compound RA have beneficial effects on cognitive improvement and may help prevent AD induced by $A{\beta}$.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.161-168
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• 2004

A single-index model is useful in fields which employ multidimensional regression models. Many methods have been developed in parametric and nonparametric approaches. In this paper, posterior inference is considered and a wavelet series is thought of as a function approximated to a true function in the single-index model. The posterior inference needs a prior distribution for each parameter estimated. A prior distribution of each coefficient of the wavelet series is proposed as a hierarchical distribution. A direction $\beta$ is assumed with a unit vector and affects estimate of the true function. Because of the constraint of the direction, a transformation, a spherical polar coordinate $\theta$, of the direction is required. Since the posterior distribution of the direction is unknown, we apply a Metropolis-Hastings algorithm to generate random samples of the direction. Through a Monte Carlo simulation we investigate estimates of the true function and the direction.