• Journal of Microbiology and Biotechnology
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• v.28 no.11
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• pp.1883-1895
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• 2018

Alcohol dependence is a global public health problem, yet the mechanisms of alcohol dependence are incompletely understood. The traditional view has been that ethanol alters various neurotransmitters and their receptors in the brain and causes the addiction. However, an increasing amount of experimental evidence suggests that gut microbiota also influence brain functions via gut-to-brain interactions, and may therefore induce the development of alcohol use disorders. In this study, a rat model of alcohol dependence and withdrawal was employed, the gut microbiota composition was analyzed by high-throughput 16S rRNA gene sequencing, and the metagenome function was predicted by PICRUSt software. The results suggested that chronic alcohol consumption did not significantly alter the diversity and richness of gut microbiota in the jejunum and colon, but rather markedly changed the microbiota composition structure in the colon. The phyla Bacteroidetes and eight genera including Bacteroidales S24-7, Ruminococcaceae, Parabacteroides, Butyricimonas, et al were drastically increased, however the genus Lactobacillus and gauvreauii in the colon were significantly decreased in the alcohol dependence group compared with the withdrawal and control groups. The microbial functional prediction analysis revealed that the proportions of amino acid metabolism, polyketide sugar unit biosynthesis and peroxisome were significantly increased in the AD group. This study demonstrated that chronic alcohol consumption has a dramatic effect on the microbiota composition structure in the colon but few effects on the jejunum. Inducement of colonic microbiota dysbiosis due to alcohol abuse seems to be a factor of alcohol dependence, which suggests that modulating colonic microbiota composition might be a potentially new target for treating alcohol addiction.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.78-85
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• 2012

This paper takes precautions proposals against prospective disasters from the space weather maximum in 2013. The space weather maximum could wreak havoc in this world. A geomagnetic space storm sparked by a solar eruption like the one that flared toward earth is bound to strike again and could wreak havoc across the modern world. Despite of the fact that not only researches by colleges and institutions current researches have been focusing on warning systems of space communication and the earth network systems, but also management and control systems are not situated for the space weather blasters. The purpose of the study is that the damage reduces methods implementation on the ultimate space weather communication systems by above lists proposed type analysis. In result, the implementation of the communication disaster management systems deals with the smart IT converged GIS analysis on the flare, solar proton event, geomagnetic storm to the effects of the geomagneticsphere, ionosphere and troposphere from solar maximum. This research can provide affective methods for the saving lives and property protections that implementation of the disaster prediction and disaster prevention systems adapts smart IT systems and converged high tech information systems using decision making support systems of the GIS methodology.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.3971-3977
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• 2016

Background: Breast cancer, the commonest cancer among women in the world, ranks top in India with an incidence rate of 1,45,000 new cases and mortality rate of 70,000 women every year. Chemotherapy outcome for breast cancer is hampered due to poor response and irreversible dose-dependent cardiotoxicity which is determined by genetic variations in drug metabolizing enzymes and transporters. Pregnane X receptor (PXR), a member of the nuclear receptor superfamily, induces expression of drug metabolizing enzymes (DMEs) and transporters leading to regulation of xenobiotic metabolism. Materials and Methods: A genomic region spanning PXR 3' UTR was amplified and sequenced using genomic DNA isolated from 96 South Indian breast cancer patients. Genetic variants observed in our study subjects were queried in miRSNP to establish SNPs that alter miRNA binding sites in PXR 3' UTR. In addition, enrichment analysis was carried out to understand the network of miRNAs and PXR in drug metabolism using DIANA miRpath and miRwalk pathway prediction tools. Results: In this study, we identified SNPs rs3732359, rs3732360, rs1054190, rs1054191 and rs6438550 in the PXR 3; UTR region. The SNPs rs3732360, rs1054190 and rs1054191 were located in the binding site of miR-500a-3p, miR-532-3p and miR-374a-3p resulting in the altered PXR level due to the deregulation of post-transcriptional control and this leads to poor treatment response and toxicity. Conclusions: Genetic variants identified in PXR 3' UTR and their effects on PXR levels through post-transcriptional regulation provide a genetic basis for interindividual variability in treatment response and toxicity associated with chemotherapy.

• Journal of the Korea Concrete Institute
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• v.18 no.5 s.95
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• pp.677-685
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• 2006

Control of the temperature difference across a section is an effective strategy to minimize the hydration-heat-induced cracks for the structures where internal restraint is dominant. The domestic code, however, overestimates probability of the crack occurrence judging from the foreign codes and construction experiences of real structures. Therefore, the background of the equation presented in the domestic code was investigated step by step to examine validity of the equation, and, as a result, it was found that the equation is established on a basis of simple elastic model where the change of elastic modulus in an early age is not considered. An advanced assessment strategy was proposed taking into account the hypoelastic model which corresponds to an incremental constitutive equation. The presented procedure resulted in an increased crack index, i.e. decreased crack risk, the value of which depends on various conditions of the mix and structures. Also, a prediction equation of the temperature difference was proposed which can readily consider the effect of the curing condition and ambient temperature in a hand calculation. For further study, the assessment equation may be more classified to strictly consider the characteristics of the mix and structures if the analytical and experimental data are accumulated.

• Korean Chemical Engineering Research
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• v.46 no.3
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• pp.486-491
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• 2008

This paper describes a model identification method that has been applied to a commercial 12-inch RTP (rapid thermal processing) equipment with an ultimate aim to develop a high-performance advanced controller. Seven thermocouples are attached on the wafer surface and twelve tungsten-halogen lamp groups are used to heat up the wafer. To obtain a MIMO balanced state space model, multiple SIMO (single-input multiple-output) identification with highorder ARX models have been conducted and the resulting models have been combined, transformed and reduced to a MIMO balanced state space model through a balanced truncation technique. The identification experiments were designed to minimize the wafer warpage and an output linearization block has been proposed for compensation of the nonlinearity from the radiation-dominant heat transfer. As a result from the identification at around 600, 700, and $800^{\circ}C$, respectively, it was found that $y=T(K)^2$ and the state dimension of 80-100 are most desirable. With this choice the root-mean-square value of the one-step-ahead temperature prediction error was found to be in the range of 0.125-0.135 K.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.523-535
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• 2017

Local intelligent services aim at controlling local services such as cooling or lightening services in a certain local area, using Internet-of-Things (IoT) sensor data in the area. As the IoT paradigm has evolved, local intelligent services have gained increasing attention. However, most of the local intelligent service mechanism proposed so far do not directly take the users' presence and service preference information into account for controlling local services. This study proposes an individual presence-and-preference-based local service system (IPP-LISS). We present a intelligent service control algorithm and implement a prototype system of IPP-LISS. Typically, the intelligence part of IPP-LISS including the prediction models, is generated on remote server in the cloud because of their compute-intense aspect. However, this can cause huge data traffic between IoT devices and servers in the cloud. The emerging mobile edge computing technology will be a promising solution of this challenge of IPP-LISS. In this paper, we implement IPP-LISS in the cloud, and then, based on the implementation result, we discuss applying the mobile edge computing technology to the IPP-LISS application.

• Journal of The Korean Association For Science Education
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• v.19 no.2
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• pp.217-228
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• 1999

The purpose of this study was to investigate the effects of the constructivist instructional model on the acquisition of atmospheric pressure conceptions and learning motivation. The step of constructivist instruction was prediction and explanation-experiment and observation-discussion-application. The control group consisted of two classes of students who participated in the teacher-centered instruction. The experimental group consisted of two classes of students who participated in the constructivist instruction. To examine students' preconceptions before the instructions, a preconceptions test was administered. After the instructions, students' acquisition of atmospheric pressure conceptions and learning motivation were measured with a researcher-made post-conceptions test and The Course Interest Survey. The results from this study were as follows: First, the constructivist instruction is more effective method in acquisition of atmospheric pressure conceptions and learning motivation than the teacher-centered instruction. Therefore, in order to increase the acquisition of science conceptions and to decrease the science misconceptions, we need to use the constructivist instructional model which make learners self check their own preconceptions of science. Second, the constructivist instruction is more effective than teacher-centered instruction in three elements of learning motivation. So, we need to develop the effective ARCS(attention, relevance, confidence, satisfaction) strategies in order to use the constructivist instructional model and to verify it's effectiveness. Third, to improve teaching and learning methods, educational researchers should carry out studies using many points of view than studies biased constructivism or objectivism. In this respect, we need to contrive how to integrate constructive view points and objective view points.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.2
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• pp.113-128
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• 1990

In recent years, various types of coastal protection scheme have been studied around the coastal region. Among them, so-called zonal protection systems are being watched with interest from various points of view. In this paper, wave overtopping rate from overflowing the vertical seawall is investigated by conducting two dimensional model on the horizontal bed experiment. Hereafter this system is referred to as a artificial reef system. One is the foundation to control wave height near the surfzone and the other is function to prevent coastal disaster by suppressing net overtopping rate. The main results obtained in this study are summarized as follows. 1) Wave attenuation taken place on the artificial reef can be predicted numerically by using energy dispersion model due to wave breaking proposed by Battjes. 2) To evaluate the wave overtopping rate from a vertical seadike on various coastal constructions by weir model, a numerical procedure for prediction of overtopping is confirmed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1413-1424
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• 2013

Recently, the frequency of severe storms increases in Korea. Severe storms occurring in a short time cause huge losses of both life and property. A considerable research has been performed for the flood control system development based on an accurate stream discharge prediction. A physical model is mainly used for flood forecasting and warning. Physical rainfall-runoff models used for the conventional flood forecasting process require extensive information and data, and include uncertainties which can possibly accumulate errors during modelling processes. ANFIS, a data driven model combining neural network and fuzzy technique, can decrease the amount of physical data required for the construction of a conventional physical models and easily construct and evaluate a flood forecasting model by utilizing only rainfall and water level data. A data driven model, however, has a disadvantage that it does not provide the mathematical and physical correlations between input and output data of the model. The characteristics of a data driven model according to functional options and input data such as the change of clustering radius and training data length used in the ANFIS model were analyzed in this study. In addition, the applicability of ANFIS was evaluated through comparison with the results of HEC-HMS which is widely used for rainfall-runoff model in Korea. The neuro-fuzzy technique was applied to a Cheongmicheon Basin in the South Han River using the observed precipitation and stream level data from 2007 to 2011.

• Journal of the Korean Society of Radiology
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• v.11 no.4
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• pp.205-212
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• 2017

Chronic diffuse hepatopathy is one of the important clinical tasks to reduce mortality and morbidity due to liver cirrhosis, liver failure, and liver cancer. The purpose of this study was to evaluate the criteria for predicting liver and chronic liver disease using Fibroscan based on ultrasound diagnosis. Serum and liver stiffness measurement(kPa) were analyzed in 280 patients and cut-off values of liver stiffness measurement for predicting fatty liver and chronic diffuse hepatopathy were determined using ROC curve analysis. Bilirubin and PT(prothrombin time) were not related to disease prediction(p=0.243, p=0.115). Serum glucose and triglyceride levels were significantly higher in the liver (p<0.05). The cut-off value for predicting chronic diffuse hepatopathy was determined as 10.3 kPa(AUC 0.98, sensitivity 94.94%, specificity 94.93%) in the order of control group, fatty liver and chronic diffuse hepatopathy. Therefore, it will be used as a primary tool for the diagnosis of chronic liver disease patients with quantitative evaluation.