• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.20-29
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• 2002

The composite stock cutting problem is to allocate rectangular and/or irregular patterns onto a large composite stock sheet of finite dimensions in such a way that the resulting scrap will be minimized. In this paper, the distributed simulated annealing with the new cost error tolerant spatial decomposition is applied to the composite stock cutting problem in MPI environments. The cost error tolerant scheme relaxes synchronization and chooses small perturbations on states asynchronously in a dynamically changed stream length to keep the convergence property of the sequential annealing. This paper proposes the efficient data structures for representation of patterns and their affinity relations and also shows how to determine move generations, annealing parameters, and a cost function. The spatial decomposition method is addressed in detail. This paper identifies that the final quality is not degraded with almost linear speedup. Composite stock shapes are not constrained to convex polygons or even regular shapes, but the rotations are only allowed to 2 or 4 due to its composite nature.

• Journal of Microbiology
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• v.43 no.4
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• pp.375-380
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• 2005

Autonomous ultradian metabolic oscillation (T$\simeq$50 min) was detected in an aerobic chemostat culture of Saccharomyces cerevisiae. A pulse injection of GSH (a reduced form of glutathione) into the culture induced a perturbation in metabolic oscillation, with respiratory inhibition caused by $H_2S$ burst pro-duction. As the production of $H_2S$ in the culture was controlled by different amino acids, we attempted to characterize the effects of GSH on amino acid metabolism, particularly with regard to branched chain and sulfur-containing amino acids. During stable metabolic oscillation, concentrations of intra-cellular glutamate, aspartate, threonine, valine, leucine, isoleucine, and cysteine were observed to oscil-late with the same periods of dissolved $O_2$ oscillation, although the oscillation amplitudes and maximal phases were shown to differ. The methionine concentration was stably maintained at 0.05 mM. When GSH (100 $\mu$M) was injected into the culture, cellular levels of branched chain amino acids increased dramatically with continuous $H_2S$production, whereas the cysteine and methionine concentrations were noticeably reduced. These results indicate that GSH-dependent perturbation occurs as the result of the promotion of branched chain amino acid synthesis and an attenuation of cysteine and methionine synthesis, both of which activate the generation of $H_2S$. In a low sulfate medium containing 2.5 mM sulfate, the GSH injections did not result in perturbations of dissolved $O_2$ NAD(P)H redox oscillations without burst $H_2S$ production. This suggests that GSH-dependent perturbation is intimately linked with the metabolism of branched-chain amino acids and $H_2S$ generation, rather than with direct GSH-GSSG redox control.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.743-750
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• 2008

Asymmetric tip clearance in an axial compressor induces pressure and velocity redistributions along the circumferential direction in an axial compressor. This paper presents the mechanism of the flow redistribution due to the asymmetric tip clearance with a simple numerical modeling. The flow field of a rotor of an axial compressor is predicted when an asymmetric tip clearance occurs along the circumferential direction. The modeling results are supported by CFD results not only to validate the present modeling but also to investigate more detailed flow fields. Asymmetric tip clearance makes local flow area and resultant axial velocity vary along the circumferential direction. This flow redistribution 'seed' results in a different flow patterns according to the flow coefficient. Flow field redistribution patterns are largely dependent on the local tip clearance performance at low flow coefficients. However, the contribution of the main flow region becomes dominant while the tip clearance effect becomes weak as the flow coefficient increases. The flow field redistribution pattern becomes noticeably strong if a blockage effect is involved when the flow coefficient increases. The relative flow angle at the small clearance region decreases which result in a negative incidence angle at the high flow coefficient. It causes a recirculation region at the blade pressure surface which results in the flow blockage. It promotes the strength of the flow field redistribution at the rotor outlet. These flow pattern changes have an effect on the blade loading perturbations. The integration of blade loading perturbation from control volume analysis of the circumferential momentum leads to well-known Alford's force. Alford's force is always negative when the flow blockage effects are excluded. However when the flow blockage effect is incorporated into the modeling, main flow effects on the flow redistribution is also reflected on the Alford's force at the high flow coefficient. Alford's force steeply increases as the flow coefficient increases, because of the tip leakage suppression and strong flow redistribution. The predicted results are well agreed to CFD results by Kang and Kang(2006).

• Journal of the Korean Magnetics Society
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• v.5 no.5
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• pp.366-371
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• 1995

High performance magnetic materials are characterized by the combination of outstanding magnetic properties and optimized microstructures, e.g., nanocrystalline composites of multilayers and small particle systems. The characteristic parameters of the hysteresis loops of these materials vary over more than a factor of $10^{6}$ with optimum values for the coercive field of several Tesla and permeabilities of $10^{6}$. Within the framework of the computational micromagnetism (nanomagnetism) using the finite element method the upper and lower bounds of the coercive field of different types of grain ensembles and multilayers have been determined. For the case of nanocrystalline composites the role of grain size, exchange and dipolar coupling between grains and the degree of grain alignment will be discusses in detail. It is shown that the largest coercivities are obtained for exchange decoupled grains, whereas remanence enhancing requires exchange coupled grains below 20 nm. For composite permanent magnets based on $Nd_{2}Fe_{14}B$ with an amount of ~ 50% soft $\alpha$-Fe-phase coercivities of ${\mu}_{0}H_{c}=0.75\;T$, a remanence of 1.5 T and an energy product of $400\;kJ/m^{3}$ is expected. In nanocrystalline systems the temperature dependence of the coercivity is well described by the relation ${\mu}_{0}H_{c}=(2\;K_{1}/M_{s}){\alpha}-N_{eff}{\mu}_{0}M_{s}$, where the microstructural parameters $\alpha$ and $N_{eff}$ take care of the short-range perturbations of the anisotropy and $N_{eff}$ is related to the long-range dipolar interactions. $N_{eff}$ is found to follow a logarithmic grain size size dependence ${\mu}_{0}H_{c}=(2\;K_{1}/M_{s}){\alpha}-N_{eff}(\beta1nD){\mu}_{0}M_{s}$. Several trends how to achieve the ideal situation $\alpha$->1 and $N_{eff}$->1->0 will be discussed.

• Nuclear Engineering and Technology
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• v.47 no.7
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• pp.838-848
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• 2015

One of the most important operations in nuclear power plants is load following, in which an imbalance of axial power distribution induces xenon oscillations. These oscillations must be maintained within acceptable limits otherwise the nuclear power plant could become unstable. Therefore, bounded xenon oscillation is considered to be a constraint for the load following operation. In this paper, the design of a sliding mode control (SMC), which is a robust nonlinear controller, is presented.SMCis ameansto control pressurized water nuclear reactor (PWR) power for the load following operation problem in a way that ensures xenon oscillations are kept bounded within acceptable limits. The proposed controller uses constant axial offset (AO) strategy to ensure xenon oscillations remain bounded. The constant AO is a robust state constraint for the load following problem. The reactor core is simulated based on the two-point nuclear reactor model with a three delayed neutron groups. The stability analysis is given by means of the Lyapunov approach, thus the control system is guaranteed to be stable within a large range. The employed method is easy to implement in practical applications and moreover, the SMC exhibits the desired dynamic properties during the entire output-tracking process independent of perturbations. Simulation results are presented to demonstrate the effectiveness of the proposed controller in terms of performance, robustness, and stability. Results show that the proposed controller for the load following operation is so effective that the xenon oscillations are kept bounded in the given region.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3275-3285
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• 2021

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.

• Biomolecules & Therapeutics
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• v.27 no.1
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• pp.48-53
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• 2019

Reactive oxygen species (ROS) are widely generated in biological processes such as normal metabolism and response to xenobiotic exposure. While ROS can be beneficial or harmful to cells and tissues, generation of ROS by diverse anti-cancer drugs or phytochemicals plays an important role in the induction of apoptosis. We recently identified a derivative of naphthalene, MS-5, that induces apoptosis of an ovarian cell, CAOV-3. Interestingly, MS-5 induced apoptosis by down-regulating the ROS. Cell viability was evaluated by water-soluble tetrazolium salt (WST-1) assay. Apoptosis was evaluated by flow cytometry analysis. Intracellular ROS ($H_2O_2$), mitochondrial superoxide, mitochondrial membrane potential (MMP) and effect on cycle were determined by flow cytometry. Protein expression was assessed by western blotting. The level of ATP was measured using ATP Colorimetric/Fluorometric Assay kit. MS-5 inhibited growth of ovarian cancer cell lines, CAOV-3, in a concentration- and time-dependent manner. MS-5 also induced G1 cell cycle arrest in CAOV-3 cells, while MS-5 decreased intracellular ROS generation. In addition, cells treated with MS-5 showed the decrease in MMP and ATP production. In this study, we found that treatment with MS-5 in CAOV-3 cells induced apoptosis but decreased ROS level. We suspect that MS-5 might interfere with the minimum requirements of ROS for survival. These perturbations appear to be concentration-dependent, suggesting that MS-5 may induce apoptosis by interfering with ROS generation. We propose that MS-5 may be a potent therapeutic agent for inducing apoptosis in ovarian cancer cell through regulation of ROS.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.585-590
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• 2018

GPS satellite orbits could be estimated precisely using GPS dynamics as well as GPS observations. Most of the perturbations are available to be generated using satellite position, velocity, well known model equations and coefficients. However, who wants to calculate solar radiation pressure (SRP) should choose a SRP model and estimate the coefficients of a SRP model. The accuracy of SRP model depends on the model characteristics. Therefore this paper has estimated coefficients of SRP models using CODE precise orbit product and compared the accuracy of orbit propagator depending on SRP model. The results show that the extended CODE orbit model (ECOM) and the reduced ECOM achieved cm level fitting orbit for the CODE 1-day orbit. Also orbit propagation model without SRP model consideration could get tens of meter orbits compared to CODE orbits.

• Journal of Ginseng Research
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• v.43 no.4
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• pp.654-665
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• 2019

Background: Panax ginseng Meyer has widely been used as a traditional herbal medicine because of its diverse health benefits. Amounts of ginseng compounds, mainly ginsenosides, vary according to seasons, varieties, geographical regions, and age of ginseng plants. However, no study has comprehensively determined perturbations of various metabolites in ginseng plants including roots and leaves as they grow. Methods: Nuclear magnetic resonance ($^1H$ NMR)-based metabolomics was applied to better understand the metabolic physiology of ginseng plants and their association with climate through global profiling of ginseng metabolites in roots and leaves during whole growing periods. Results: The results revealed that all metabolites including carbohydrates, amino acids, organic acids, and ginsenosides in ginseng roots and leaves were clearly dependent on growing seasons from March to October. In particular, ginsenosides, arginine, sterols, fatty acids, and uracil diphosphate glucose-sugars were markedly synthesized from March until May, together with accelerated sucrose catabolism, possibly associated with climatic changes such as sun exposure time and rainfall. Conclusion: This study highlights the intrinsic metabolic characteristics of ginseng plants and their associations with climate changes during their growth. It provides important information not only for better understanding of the metabolic phenotype of ginseng but also for quality improvement of ginseng through modification of cultivation.

• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1540-1553
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• 2019

A nuclear power plant (NPP) is a highly complex system-of-systems as manifested through its internal systems interdependence. The negative impact of such interdependence was demonstrated through the 2011 Fukushima Daiichi nuclear disaster. As such, there is a critical need for new strategies to overcome the limitations of current risk assessment techniques (e.g. the use of static event and fault tree schemes), particularly through simulation of the nonlinear dynamic feedback mechanisms between the different NPP systems/components. As the first and key step towards developing an integrated NPP dynamic probabilistic risk assessment platform that can account for such feedback mechanisms, the current study adopts a system dynamics simulation approach to model the thermal dynamic processes in: the reactor core; the secondary coolant system; and the pressurized water reactor. The reactor core and secondary coolant system parameters used to develop system dynamics models are based on those of the Palo Verde Nuclear Generating Station. These three system dynamics models are subsequently validated, using results from published work, under different system perturbations including the change in reactivity, the steam valve coefficient, the primary coolant flow, and others. Moving forward, the developed system dynamics models can be integrated with other interacting processes within a NPP to form the basis of a dynamic system-level (systemic) risk assessment tool.