• Quantitative Bio-Science
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• v.37 no.2
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• pp.73-79
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• 2018

As high frequency (HF, for short) time series is now prevalent in the presence of real time big data, volatility computations based on traditional ARCH/GARCH models need to be further developed to suit the high frequency characteristics. This article reviews realized volatilities (RV) and multivariate GARCH (MGARCH) to deal with high frequency volatility computations. As a (functional) infinite dimensional models, the fARCH and fGARCH are introduced to accommodate ultra high frequency (UHF) volatilities. The fARCH and fGARCH models are developed in the recent literature by Hormann et al. [1] and Aue et al. [2], respectively, and our discussions are mainly based on these two key articles. Real data applications to domestic UHF financial time series are illustrated.

• Quantitative Bio-Science
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• v.37 no.2
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• pp.81-89
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• 2018

It is commonplace that high false detection rates interfere with immediate vision-based fire monitoring system. To circumvent this challenge, we propose a fire detection algorithm that can accommodate color variations of RGB in temporal domain, aiming at reducing false detection rates. Despite interrupting images (e.g., background noise and sudden intervention), the proposed method is proved robust in capturing distinguishable features of fire in temporal domain. In numerical studies, we carried out extensive real data experiments related to fire detection using 24 video sequences, implicating that the propose algorithm is found outstanding as an effective decision rule for fire detection (e.g., false detection rate <10%).

• Quantitative Bio-Science
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• v.37 no.2
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• pp.91-101
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• 2018

This study has analyzed applicable characteristics on big data of the meteorology and climate depending on press releases in the media. As a result, more than half of them were conducted by governmental departments and institutions (26.9%) and meteorological administration (25.0%). Most articles were written by journalists, especially the highest portion stems from straight articles focusing on delivering simple information. For each field, the number of cases had listed in order of rank to be exposed to the media; information service, business management, farming, livestock, and fishing industries, and disaster management, but others did rank far behind; insurance, construction, hydrology and energy. Application of big data about meteorology and climate differed depending on the seasonal change, it was directly related to temperature information during spring, to weather phenomenon such as monsoon and heat wave during summer, to meteorology and climate information during fall, and to weather phenomenon such as cold wave and heavy snow during winter.

• Quantitative Bio-Science
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• v.37 no.2
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• pp.113-124
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• 2018

Pim kinases are important targets for cancer therapies because they are mainly responsible for cancer metastasis and overall therapeutic treatment responses. Because of their unusual structural feature in the hinge region of the ATP-binding site, new binding motifs have been discovered and used for the development of Pim kinases inhibitors. The results of a screening of 5-membered heteroaromatic compounds and the effects of structural modifications on the inhibition of Pim kinases' activities showed the potential scaffold for Pim inhibitors. 1,3,4-Oxadiazole-2(3H)-thione was found as a new scaffold for Pim kinase inhibitors.

• Quantitative Bio-Science
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• v.36 no.1
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• pp.23-31
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• 2017

Datasets from DNA microarray experiments, which are in the form of large matrices of expression levels of genes, often have missing values. However, the existing statistical methods including the principle components analysis (PCA) and Hotelling's t-test are not directly applicable for the datasets having missing values due to the fact that they assume the observed dataset is complete in general. Many methods have been proposed in previous literature to impute the missing in the observed data. Troyanskaya et al. [1] study the k-nearest neighbor (kNN) imputation, Kim et al. [2] propose the local least squares (LLS) method and Rubin [3] propose the multiple imputation (MI) for missing values. To identify differentially expressed genes, we propose a new testing procedure when the missing exists in the observed data. The proposed procedure uses the Stouffer's z-scores and combines the test results of individual imputed samples, which are dependent to each other. We numerically show that the proposed test procedure based on MI performs better than the existing test procedures based on single imputation (SI) by comparing their ROC curves. We apply the proposed method to analyzing a public microarray data.

• Quantitative Bio-Science
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• v.37 no.2
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• pp.133-141
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• 2018

Graphical lasso is one of the most popular methods to estimate a sparse precision matrix, which is an inverse of a covariance matrix. The objective function of graphical lasso imposes an ${\ell}_1$-penalty on the (vectorized) precision matrix, where a tuning parameter controls the strength of the penalization. The selection of the tuning parameter is practically and theoretically important since the performance of the estimation depends on an appropriate choice of tuning parameter. While information criteria (e.g. AIC, BIC, or extended BIC) have been widely used, they require an asymptotically unbiased estimator to select optimal tuning parameter. Thus, the biasedness of the ${\ell}_1$-regularized estimate in the graphical lasso may lead to a suboptimal tuning. In this paper, we propose a two-staged bias-correction procedure for the graphical lasso, where the first stage runs the usual graphical lasso and the second stage reruns the procedure with an additional constraint that zero estimates at the first stage remain zero. Our simulation and real data example show that the proposed bias correction improved on both edge recovery and estimation error compared to the single-staged graphical lasso.

• Quantitative Bio-Science
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• v.37 no.2
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• pp.103-111
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• 2018

This study was performed to investigate the cytoprotective effects of Stachys riederi var. japonica ethanol extract (SREE) to control oxidative stress induced by UVA-irradiation by examining antioxidant capacity and gene expression of cytochrome c using human dermal fibroblasts. The total polyphenolics and flavonoids in the SREE were 41.2 and 25.4 mg/g, respectively. At concentrations of 500 and $1000{\mu}g/mL$, the electron-donating ability of SREE was 48.6% and 82.0%, respectively, and the 2,2'-azino-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging activity was 62.3% and 78.8%, respectively. These findings showed that SREE has a fairly good antioxidant capacity. As determined by an MTT assay, the maximum permissible level for treating SREE to human dermal fibroblasts was shown to be over $200{\mu}g/mL$. SREE ($200{\mu}g/mL$) significantly decreased cytochrome c mRNA and protein expression by 31.1% (p<0.001) and 38.8% (p<0.01), respectively. These findings suggest that SREE may protect human skin cells against mitochondrial-dependent apoptosis. Therefore, SREE seems to be a natural antioxidant to protect cells against oxidative stress induced by UVA-irradiation.

• Quantitative Bio-Science
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• v.37 no.2
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• pp.125-132
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• 2018

In this study, noble strains of lactic acid bacteria were isolated and identified by genetic analysis of 16s rRNA. Also, pH-dependent growth curve, cholesterol assimilation ability and sugar production efficiency were measured. Lactic acid bacteria were identified to inhabit in the milks from various animals. Results of sequence analysis showed that there were differences in 16S rRNA sequence among strains and part of gene deletion was also recognized. Growth rates were varied, too, depending on the pH of the medium. Lactobacillus rhamnosus LOCK908 isolated from cow milk showed the highest growth rate and high cholesterol assimilation ability. Results of sugar fermentation tests were relatively consistent with the sequencing results. So, we propose newly isolated Lactobacillus rhamnosus LOCK908 as useful candidate for a starter of fermented beverage and probiotics. Results of this study will contribute to the isolation and identification of noble Lactic acid bacteria and to the public health.