• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.367-373
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• 2023

Aircrews and passengers are exposed to radiation from cosmic rays and secondary scattered rays generated by reactions with air or aircraft. For aircrews, radiation safety management is based on the exposure dose calculated using a space-weather environment simulation. However, the exposure dose varies depending on solar activity, altitude, flight path, etc., so measuring by route is more suggestive than the calculation. In this study, we developed an instrument to measure the cosmic radiation dose using a general-purpose Si sensor and a multichannel analyzer. The dose calculation applied the algorithm of CRaTER (Cosmic Ray Telescope for the Effects of Radiation), a space radiation measuring device of NASA. Energy and dose calibration was performed with Cs-137 662 keV gamma rays at a standard calibration facility, and good dose rate dependence was confirmed in the experimental range. Using the instrument, the dose was directly measured on the international line between Dubai and Incheon in May 2023, and it was similar to the result calculated by KREAM (Korean Radiation Exposure Assessment Model for Aviation Route Dose) within 12%. It was confirmed that the dose increased as the altitude and latitude increased, consistent with the calculation results by KREAM. Some limitations require more verification experiments. However, we confirmed it has sufficient utilization potential as a cost-effective measuring instrument for monitoring exposure dose inside or on personal aircraft.

• Biomolecules & Therapeutics
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• v.27 no.2
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• pp.193-200
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• 2019

Ceramide metabolism is known to be an essential etiology for various diseases, such as atopic dermatitis and Gaucher disease. Glucosylceramide synthase (GCS) is a key enzyme for the synthesis of glucosylceramide (GlcCer), which is a main ceramide metabolism pathway in mammalian cells. In this article, we developed a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to determine GCS activity using synthetic non-natural sphingolipid C8-ceramide as a substrate. The reaction products, C8-GlcCer for GCS, could be separated on a C18 column by reverse-phase high-performance liquid chromatography (HPLC). Quantification was conducted using the multiple reaction monitoring (MRM) mode to monitor the precursor-to-product ion transitions of m/z $588.6{\rightarrow}264.4$ for C8-GlcCer at positive ionization mode. The calibration curve was established over the range of 0.625-160 ng/mL, and the correlation coefficient was larger than 0.999. This method was successfully applied to detect GCS in the human hepatocellular carcinoma cell line (HepG2 cells) and mouse peripheral blood mononuclear cells. We also evaluated the inhibition degree of a known GCS inhibitor 1-phenyl-2-decanoylamino-3-morpholino-1-propanol (PDMP) on GCS enzymatic activity and proved that this method could be successfully applied to GCS inhibitor screening of preventive and therapeutic drugs for ceramide metabolism diseases, such as atopic dermatitis and Gaucher disease.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.103-112
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• 2009

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this paper, principal component-based Auto-Associative support vector regression (PCSVR) was proposed for the sensor signal validation of the NPP. It utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and AASVR because it easily represents complicated processes that are difficult to model with analytical and mechanistic models. With the use of real plant startup data from the Kori Nuclear Power Plant Unit 3, SVR hyperparameters were optimized by the response surface methodology (RSM). Moreover the statistical techniques are integrated with PCSVR for the failure detection. The residuals between the estimated signals and the measured signals are tested by the Shewhart Control Chart, Exponentially Weighted Moving Average (EWMA), Cumulative Sum (CUSUM) and generalized likelihood ratio test (GLRT) to detect whether the sensors are failed or not. This study shows the GLRT can be a candidate for the detection of sensor drift.