• Korean Journal of Social Welfare Studies
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• v.44 no.3
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• pp.301-322
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• 2013

By analyzing wave 1~11 (1998~2008) of Korean Labor and Income Panel Study(KLIPS) database, this study examines the effects of household characteristics and poverty duration on poverty exit. A special concern is to decide whether the decrease of poverty exit rates comes from true duration dependency or from the sample heterogeneity as poverty duration progresses. I also analyzed how the effects of independent variables are changed when unobserved heterogeneity is controlled. The results show that duration dependency disappears after controlling observed household characteristics and unobserved individual heterogeneity. This finding confirms that the apparent relationship between poverty exit rate and poverty duration is in fact a spurious association due to the sample heterogeneity rather than true duration dependency. In addition, the effects of household characteristics on poverty exit rate become more stronger when unobserved heterogeneity is controlled. Socioeconomic factors affecting poverty exit rates are such as householders' age, education, household composition, number of family members, labor force participation, and work status.

• Journal of Korean Society on Water Environment
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• v.31 no.6
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• pp.610-618
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• 2015

This study was conducted to find out the influence of sample size (accumulated survey areas) on the seven biological indices of benthic macroinvertebrates. BMI, the index similar to Zeilika-Marvan’s saprobic index, tended to be independent on the variations of sample size. The other indices (Shannon-Weaver’s diversity, Margalef’s richness, Menhinick’s richness, Pielou’s evenness, and Lenat’s EPT index) showed the considerable variations along with the increase of sample size and environmental conditions. To get the appropriate index values, it should be sampled at least 6 replicates more based on 30×30cm Surber sampler. In addition, the habitat heterogeneity index of benthic macroinvertebrates suggested in this study, it will be able to be used for evaluating the heterogeneity of habitats.

• Applied Microscopy
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• v.42 no.1
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• pp.49-52
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• 2012

For TEM study of biological samples or polymers that are contained in organic structure, it is often required that the sample is prepared by using ultramicrotome and stained with proper agents to increase the contrast of organic structure. In this study, we investigated an efficient TEM sample preparation method for ductile heterogeneity material by using ultramicrotomy. Cryo-ultramicrotomy is a suitable method that is capable of rendering sample hardness for various ductile materials. However, it has several factors to consider, such as experimental cost, working time and finding the optimal staining conditions. To satisfy these considerations, we prepared TEM sample by using ultramicrotome without cryofunction, and secured the sample hardness by applying the staining process prior to ultrathin sectioning. The cross-linked polyethylene structure in the sample was stained with the 2% $RuO_4$ solution in a sealed test tube for 24 hours at $4^{\circ}C$. After the sample staining, ultrathin sections of sample were prepared using ultramicrotome. As a result, it was revealed that the difficulties associated with staining of ultrathin sections prepared by low-temperature conditions were improved. In addition, appropriate staining depth of sample could be selected for sectioning process. The quality of TEM sample obtained by using this method was better than that of cryo-ultramicroscopy. Finally, it is expected that our method could be effectively applied in TEM sample preparation for a variety of nano-bio convergence materials.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.7
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• pp.1045-1054
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• 2012

The phylogenetic diversity of the bacteria in hot composting samples collected from three spatial locations was investigated by molecular tools in order to determine the influence of gradient effect on bacterial communities during the thermophilic phase of composting swine manure with rice straw. Total microbial DNA was extracted and bacterial near full-length 16S rRNA genes were subsequently amplified, cloned, restriction fragment length polymorphism-screened and sequenced. The superstratum sample had the highest microbial diversity among the three samples which was possibly related to the surrounding conditions of the sample resulting from the location. The results showed that the sequences related to Bacillus sp. were most common in the composts. In superstratum sample, 45 clones (33%) and 36 clones (27%) were affiliated with the Bacillus sp. and Clostridium sp., respectively; 74 clones (58%) were affiliated with the Clostridium sp. in the middle-level sample; 52 clones (40%) and 29 clones (23%) were affiliated with the Clostridium sp. and Bacillus sp. in substrate sample, respectively. It indicated that the microbial diversity and community in the samples were different for each sampling site, and different locations of the same pile often contained distinct and different microbial communities.

• Journal of Soil and Groundwater Environment
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• v.16 no.6
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• pp.1-9
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• 2011

A bibliographical review of Gy sampling theory for particulate materials was conducted to provide readers with useful means to reduce errors in soil contamination investigation. According to the Gy theory, the errors caused by the heterogeneous nature of soil include; the fundamental error (FE) caused by physical and chemical constitutional heterogeneity, the grouping and segregation error (GE) aroused from gravitational force, long-range heterogeneous fluctuation error ($CE_2$), the periodic heterogeneity fluctuation error ($CE_3$), and the materialization error (ME) generated during physical process of sample treatment. However, the accurate estimation of $CE_2$ and $CE_3$ cannot be estimated easily and only increasing sampling locations can reduce the magnitude of the errors. In addition, incremental sampling is the only method to reduce GE while grab sampling should be avoided as it introduces uncertainty and errors to the sampling process. Correct preparation and operation of sampling tools are important factors in reducing the incremental delimitation error (DE) and extraction error (EE) which are resulted from physical processes in the sampling. Therefore, Gy sampling theory can be used efficiently in planning a strategy for soil investigations of non-volatile and non-reactive samples.

• Genomics & Informatics
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• v.17 no.1
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• pp.2.1-2.12
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• 2019

Chronic obstructive pulmonary disease (COPD) is a type of progressive lung disease, featured by airflow obstruction. Recently, a comprehensive analysis of the transcriptome in lung tissue of COPD patients was performed, but the heterogeneity of the sample was not seriously considered in characterizing the mechanistic dysregulation of COPD. Here, we established a new transcriptome analysis pipeline using a deconvolution process to reduce the heterogeneity and clearly identified that these transcriptome data originated from the mild or moderate stage of COPD patients. Differentially expressed or co-expressed genes in the protein interaction subnetworks were linked with mitochondrial dysfunction and the immune response, as expected. Computational protein localization prediction revealed that 19 proteins showing changes in subcellular localization were mostly related to mitochondria, suggesting that mislocalization of mitochondria-targeting proteins plays an important role in COPD pathology. Our extensive evaluation of COPD transcriptome data could provide guidelines for analyzing heterogeneous gene expression profiles and classifying potential candidate genes that are responsible for the pathogenesis of COPD.

• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.301-309
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• 2017

It is often possible to test for differences in population means when two or more samples are extracted from each N population. However, it is not possible to test for the mean difference if one sample is extracted from each population since a sample mean does not exist. But, by dividing a group of samples extracted one by one into two groups and generating a sample mean, we can identify a heterogeneity that may exist within the group by comparing the differences of the groups' mean. Therefore, we propose a minimum combination t-test method that can test the mean difference by the number of combinations that can be divided into two groups. In this paper, we proposed a method to test differences between means to check heterogeneity in a group of extracted samples. We verified the performance of the method by simulation study and obtained the results through real data analysis.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.15-23
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• 2021

This study investigates the presence of the day-of-the-week anomaly in exchange rate for 30 developing countries with free floating exchange rate regimes using daily data from January 2, 2011 to December 31, 2019. First, we apply the GARCH panel to estimate the intraday effect for all the sampled countries. Second, we run poolability test to check whether the coefficients of the GARCH panel are the same for all countries sampled. The result of poolability test rejects the homogeneity assumption. This implies that our sample countries contain heterogeneity. Third, we apply mean-group estimation by averaging the coefficients for all individual GARCH estimations. Fourth, we divided our sample of developing countries into three groups based on capital restriction index for the reason that the effect of monetary policy on the exchange rate depends on the degree of capital account liberalization. The empirical evidence for the return equation suggests that Mondays are connected with lower volatility whereas Thursdays experiences higher return compared to Tuesdays. The lowest estimated coefficient for full sample, group 1 and group 2, is Friday, but for group 2 is Thursday. We find similar result for the volatility equations, which show that Monday returns are lower compared to Tuesday.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.8
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• pp.3691-3698
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• 2014

Background: Published studies on the association between the Ras Association Domain Family 1 isoform A (RASSF1A) Ala133Ser polymorphism and cancer susceptibility have yielded conflicting results. Thus, a meta-analysis was here performed to assess the possible association. Materials and Methods: All eligible case-control studies published up to November 2013 on the association between RASSF1A Ala133Ser polymorphism and cancer susceptibility were identified by searching PubMed, Web of Science, Science Direct and hand search. Bothfixed-effect and random-effect models were used to calculate pooled odds ratios (ORs) with 95% confidence intervals (CIs) by using the Comprehensive Meta-Analysis software version 2.2. Results: A total of 10 studies including 4,572 cancer cases and 4,320 controls were included in the meta-analysis. Overall, significantly increased cancer risk was associated with the variant Ser133 when all studies were pooled (Ser vs Ala: OR=1.51, 95% CI=1.08-2.12, $P_{heterogeneity}{\leq}0.001$; Ser/Ser+Ala/Ser vs Ala/Ala: OR=1.55, 95% CI=1.08-2.22, $P_{heterogeneity}{\leq}0.001$). Moreover, in subgroup analyses by cancer types, a significant association between RASSF1A Ala133Ser polymorphism and lung cancer risk was found (Ser vs Ala: OR=2.27, 95% CI=1.29-4.02, $P_{heterogeneity}$=0.61; Ser/Ser+Ala/Ser vs Ala/Ala: OR=2.42, 95% CI=1.33-4.42, $P_{heterogeneity}=0.75$). In addition, in subgroup analyses by ethnicity, it was found that the RASSF1A Ala133Ser polymorphism was associated with overall cancer risk in Asians (Ser vs Ala: OR=1.37, 95% CI=1.06-1.77, $P_{heterogeneity}=0.06$) and Caucasians (Ser/Ser+Ala/Ser vs Ala/Ala: OR=2.21, 95% CI=1.01-4.82, $P_{heterogeneity}{\leq}0.001$). Conclusions: This meta-analysis suggests, for the first time, that RASSF1A Ala133Ser polymorphism may contribute to cancer susceptibility, especially for lung cancer. Besides, additional well-designed studies with larger sample size focusing on different ethnicities and cancer types are needed to confirm these findings.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.331-348
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• 2019

Understanding the tumor heterogeneity due to differences in the growth pattern of metastatic tumors and rate of change is important for understanding the sensitivity of tumor cells to drugs and finding appropriate therapies. It is often possible to test for differences in population means using t-test or ANOVA when the group of N samples is distinct. However, these statistical methods can not be used unless the groups are distinguished as the data covered in this paper. Statistical methods have been studied to test heterogeneity between samples. The minimum combination t-test method is one of them. In this paper, we propose a maximum combinatorial t-test method that takes into account combinations that bisect data at different ratios. Also we propose a method based on the idea that examining the heterogeneity of a sample is equivalent to testing whether the number of optimal clusters is one in the cluster analysis. We verified that the proposed methods, maximum combination t-test method and gap statistic, have better type-I error and power than the previously proposed method based on simulation study and obtained the results through real data analysis.