• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6249-6256
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• 2013

One-carbon metabolism plays an important role in colorectal carcinogenesis. Meta-analyses have suggested protective associations of folate and vitamin $B_6$ intakes with colorectal cancer primarily based on studies in Caucasians, and genetic polymorphisms pertaining to the folate metabolism have been a matter of interest. Less investigated are the roles of methionine synthase (MTR) and thymidylate synthetase (TS) polymorphisms in colorectal carcinogenesis. In a study of 816 cases and 815 community controls in Japan, we investigated associations of dietary intakes of folate, methionine, vitamin $B_2$, vitamin $B_6$, and vitamin $B_{12}$ with colorectal cancer risk. The associations with MTR 2756A>G, MTRR 66A>G, and TSER repeat polymorphism were examined in 685 cases and 778 controls. Methionine and vitamin $B_{12}$ intakes were inversely associated with colorectal cancer risk, but the associations were totally confounded by dietary calcium and n-3 fatty acids. The other nutrients showed no association with the risk even without adjustment for calcium and n-3 fatty acids. The TSER 2R allele was dose-dependently associated with an increased risk. The MTR and MTRR polymorphisms were unrelated to colorectal cancer risk. There was no measurable gene-gene or gene-nutrient interaction, but increased risk associated with the TSER 2R allele seemed to be confined to individuals with high folate status. This study does not support protective associations for folate and vitamin $B_6$. The TSER 2R allele may confer an increased risk of colorectal cancer. The role of the TSER polymorphism in colorectal carcinogenesis may differ by ethnicity.

• Korean Journal of Radiology
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• v.22 no.5
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• pp.770-781
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• 2021

Objective: Chemical exchange-dependent saturation transfer (CEST) MRI is sensitive for detecting solid-like proteins and may detect changes in the levels of mobile proteins and peptides in tissues. The objective of this study was to evaluate the characteristics of chemical exchange proton pools using the CEST MRI technique in patients with dementia. Materials and Methods: Our institutional review board approved this cross-sectional prospective study and informed consent was obtained from all participants. This study included 41 subjects (19 with dementia and 22 without dementia). Complete CEST data of the brain were obtained using a three-dimensional gradient and spin-echo sequence to map CEST indices, such as amide, amine, hydroxyl, and magnetization transfer ratio asymmetry (MTR_asym) values, using six-pool Lorentzian fitting. Statistical analyses of CEST indices were performed to evaluate group comparisons, their correlations with gray matter volume (GMV) and Mini-Mental State Examination (MMSE) scores, and receiver operating characteristic (ROC) curves. Results: Amine signals (0.029 for non-dementia, 0.046 for dementia, p = 0.011 at hippocampus) and MTR_asym values at 3 ppm (0.748 for non-dementia, 1.138 for dementia, p = 0.022 at hippocampus), and 3.5 ppm (0.463 for non-dementia, 0.875 for dementia, p = 0.029 at hippocampus) were significantly higher in the dementia group than in the non-dementia group. Most CEST indices were not significantly correlated with GMV; however, except amide, most indices were significantly correlated with the MMSE scores. The classification power of most CEST indices was lower than that of GMV but adding one of the CEST indices in GMV improved the classification between the subject groups. The largest improvement was seen in the MTR_asym values at 2 ppm in the anterior cingulate (area under the ROC curve = 0.981), with a sensitivity of 100 and a specificity of 90.91. Conclusion: CEST MRI potentially allows noninvasive image alterations in the Alzheimer's disease brain without injecting isotopes for monitoring different disease states and may provide a new imaging biomarker in the future.

• Nuclear Engineering and Technology
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• v.38 no.5
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• pp.417-422
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• 2006

The present paper describes the 45 MW High Flux Reactor (HFR) which is located in Petten, The Netherlands. This paper focuses on selected technical aspects of this reactor and on nuclear fuel irradiation experiments. These fuel experiments are mainly experiments on Light Water Reactor (LWR) and Very/High Temperature Reactor (V/HTR) fuels, but also on Fast Reactor (FR) fuels, transmutation fuels and Material Test Reactor (MTR) fuels.

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.1881-1895
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• 2020

The theoretical aspects behind the reactor depletion capability of the Monte Carlo code MCS developed at the Ulsan National Institute of Science and Technology (UNIST) and practical results of this depletion feature for a Material-Testing Reactor (MTR) with plate-type fuel are described in this paper. A verification of MCS results is first performed against MCNP6 to confirm the suitability of MCS for the criticality and depletion analysis of the MTR. Then, the dependence of the effective neutron multiplication factor to the number of axial and radial depletion cells adopted in the fuel plates is performed with MCS in order to determine the minimum spatial segmentation of the fuel plates. Monte Carlo depletion results with 37,800 depletion cells are provided by MCS within acceptable calculation time and memory usage. The results show that at least 7 axial meshes per fuel plate are required to reach the same precision as the reference calculation whereas no significant differences are observed when modeling 1 or 10 radial meshes per fuel plate. This study demonstrates that MCS can address the need for Monte Carlo codes capable of providing reference solutions to complex reactor depletion problems with refined meshes for fuel management and research reactor applications.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.11
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• pp.596-603
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• 2004

This paper proposes an expert system based on the pattern recognition method which can enhance the accuracy and effectiveness of real-time bus reconfiguration strategy for the transfer of faulted load when a main transformer fault occurs in the automated substation. The minimum distance classification method is adopted as the pattern recognition method of expert system. The training pattern set is designed MTr by MTr to minimize the searching time for target load pattern which is similar to the real-time load pattern. But the control pattern set, which is required to determine the corresponding bus reconfiguration strategy to these trained load pattern set is designed as one table by considering the efficiency of knowledge base design because its size is small. The training load pattern generator based on load level and the training load pattern generator based on load profile are designed, which are can reduce the size of each training pattern set from max L/sup (m+f)/ to the size of effective level. Here, L is the number of load level, m and f are the number of main transformers and the number of feeders. The one reduces the number of trained load pattern by setting the sawmiller patterns to a same pattern, the other reduces by considering only load pattern while the given period. And control pattern generator based on exhaustive search method with breadth-limit is designed, which generates the corresponding bus reconfiguration strategy to these trained load pattern set. The inference engine of the expert system and the substation database and knowledge base is implemented in MFC function of Visual C++ Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and pattern recognition solution based on diversity event simulations for typical distribution substation.

• Journal of Korean Society on Water Environment
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• v.21 no.2
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• pp.169-175
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• 2005

This study was carried out to investigate the effects of irrigation water pollution on the yield and grain quality of rice. It acquires fundamental data to set up water quality standards for irrigation and produce agricultural safety products. The correlations of BOD, T-N, T-P, pH, ECw of the irrigation water with yield, grain appearance quality, and the protein content were evaluated. The field and pot experiments were conducted by using Japonica of Oryza sativa L. during 2 years. BOD concentration in irrigation water effects strongly on grain appearance quality and yield of rice. T-N in irrigation water has strong effect on the yield, appearance, and quality of rice. T-P concentration in irrigation water have not any correlation with yield and quality of rice. pH showed strongly negative correlation with maturity ratio(MTR), 1000 grain weight(TGW), and yield of rice(YLD) as r=-0.803~-0.828(p<0.001) and have no effect on the appearance quality of rice. $EC_w$ indicating salt content showed strongly negative correlation with MTR, TGW, number of grains per panicles(NGP), and number of panicles per unit area(NPM) as r=-0.759~-0.798, and with YLD as -0.753.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.5
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• pp.543-548
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• 2014

Multiple-model based speech recognition framework (MMSR) has been known to be very successful in speech recognition. Since it uses multiple hidden Markov modes (HMMs) that corresponds to various noise types and signal-to-noise ratio (SNR) values, the selected acoustic model can have a close match with the test noisy speech. However, since the number of HMM sets is limited in practical use, the acoustic mismatch still remains as a problem. In this study, we experimentally determined the optimal SNR mapping between the test noisy speech and the HMM set to mitigate the mismatch between them. Improved performance was obtained by employing the SNR mapping instead of using the estimated SNR from the test noisy speech. When we applied the proposed method to the MMSR, the experimental results on the Aurora 2 database show that the relative word error rate reduction of 6.3% and 9.4% was achieved compared to a conventional MMSR and multi-condition training (MTR), respectively.

• Proceedings of the KIEE Conference
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• 2001.11a
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• pp.198-200
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• 2001

In this paper, we describe the developed learning tool of expert system for preventive diagnosis of substation power equipments. The expert system was programmed by using the diagnosis methods as like gas analysis in oil and partial discharge, hottest temperature, the current of OLTC driving meter, the current of fan and pump in MTr and driving coil current in GCB and leakage current in LA. The learning tool is composed of the expert system and the explanation of diagnosed examples and the applied rules and it well worked according to the rule.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.350-353
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• 1991

This study develops an expert system which solves the problems of the MTr/feeder overloads and the feeder constraints in automated radial distribution systems. Then, the objective is to perform the network reconfiguration by switching the tie and sectionalizing switches which eliminates the system violation, while achieving the load balance of the MTrs/feeders. To reduce the search space, an expert system based on heuristic rules is presented, and implemented in AI language Prolog. This system adopts the best-first tree search technique. The computational results are also prepared to show the performance of the heuristic algorithm developed.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.366-367
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• 2011

The DC distribution system iis a new promising topologies in a field of future smart distribution system. This system has high efficiency and reliability. So it is expected that there would be an increase in the installation of DC distribution systems. In this paper, the parameter of the DC/DC converter impact on customer's the power quailty in the DC distribution system when the fault occurred. For the analysis, DC network to be modeled using PSCAD/EMTDC. The fault is occurred at phase A in secondary side of MTR which is AC system. Then compared voltage and power at the customer side by varying the capacity of capcitor in the DC/DC converter.