• Journal of Radiation Protection and Research
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• v.28 no.1
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• pp.43-50
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• 2003

This study describes a practical method for interpretation of bioassay results of inhaled uranium to assess the committed effective doses both for chronic and acute intake situations. Organs in the body were represented by a series of mathematical compartments for analysis of the behavior of uranium in the body according to the gastrointestinal track model, respiratory track model and biokinetic model recommended by the ICRP. An analytical solutions of the system of balance equations among the compartments were obtained using the Birchall's algorithm, and the urinary excretion function and the lung retention function of uranium were obtained. An initial or total intakes by intake modes were calculated by applying excretion and retention functions to the urinary uranium concentration and the lung burden measured with a lung counter. The dose coefficients given in ICRP 78 are used to estimate the committed effective doses from the calculated intakes.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.2 no.2
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• pp.113-124
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• 2004

A computer software program, called BIDAS (BIoassay Data Analysis Software) is developed to interpret the bioassay measurement data in terms of intakes and the committed effective dose using the human respiratory tract model (HRTM), gastrointestinal tract (GI-tract) model and biokinetic models currently recommended by the International Commission on Radiological Protection (ICRP) to describe the behavior of the radioactive materials within the body. The program consists of three modules; first, a database module to manage the bioassay data, second, another databasee module to store the predicted bioassay quantities of each radionuclide and finally, a computational module to estimate the intake and committed effective dose calculated with the bioassay quantity measurement values from either an acute or chronic exposure of the radionuclies within the body. This paper describes the features of the program as well as the quality assurance check results of the BIDAS software program.

• Journal of Radiation Protection and Research
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• v.40 no.4
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• pp.216-222
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• 2015

Facilities processing raw materials containing naturally occurring radioactive materials (NORM) may give rise to enhanced radiation dose to workers due to chronic inhalation of airborne particulates. Internal radiation dose due to particulate inhalation varies depending on particulate properties, including size, shape, density, and absorption type. The objective of the present study was to assess inhalation dose sensitivity to physicochemical properties of airborne particulates. Committed effective doses to workers resulting from inhalation of airborne particulates were calculated based on International Commission on Radiological Protection 66 human respiratory tract model. Inhalation dose generally increased with decreasing particulate size. Committed effective doses due to inhalation of $0.01{\mu}m$ sized particulates were higher than doses due to $100{\mu}m$ sized particulates by factors of about 100 and 50 for $^{238}U$ and $^{230}Th$, respectively. Inhalation dose increased with decreasing shape factor. Shape factors of 1 and 2 resulted in dose difference by about 18 %. Inhalation dose increased with particulate mass density. Particulate mass densities of $11g{\cdot}cm^{-3}$ and $0.7g{\cdot}cm^{-3}$ resulted in dose difference by about 60 %. For $^{238}U$, inhalation doses were higher for absorption type of S, M, and F in that sequence. Committed effective dose for absorption type S of $^{238}U$ was about 9 times higher than dose for absorption F. For $^{230}Th$, inhalation doses were higher for absorption type of F, M, and S in that sequence. Committed effective dose for absorption type F of $^{230}Th$ was about 16 times higher than dose for absorption S. Consequently, use of default values for particulate properties without consideration of site specific physiochemical properties may potentially skew radiation dose estimates to unrealistic values up to 1-2 orders of magnitude. For this reason, it is highly recommended to consider site specific working materials and conditions and use the site specific particulate properties to accurately access radiation dose to workers at NORM processing facilities.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1711-1720
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• 2020

Particulate matter (PM) that has been artificially generated during the recent of rapid industrialization and urbanization moves and disperses according to weather conditions, and adversely affects the human skin and respiratory systems. The purpose of this study is to predict the PM10 concentration in Seoul using meteorological factors as input dataset for multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) models, and compared and evaluated the performance of the models. First, the PM10 concentration data obtained at 39 air quality monitoring sites (AQMS) in Seoul were divided into training and validation dataset (8:2 ratio). The nine meteorological factors (mean, maximum, and minimum temperature, precipitation, average and maximum wind speed, wind direction, yellow dust, and relative humidity), obtained by the automatic weather system (AWS), were composed to input dataset of models. The coefficients of determination (R2) between the observed PM10 concentration and that predicted by the MLR, SVM, and RF models was 0.260, 0.772, and 0.793, respectively, and the RF model best predicted the PM10 concentration. Among the AQMS used for model validation, Gwanak-gu and Gangnam-daero AQMS are relatively close to AWS, and the SVM and RF models were highly accurate according to the model validations. The Jongno-gu AQMS is relatively far from the AWS, but since PM10 concentration for the two adjacent AQMS were used for model training, both models presented high accuracy. By contrast, Yongsan-gu AQMS was relatively far from AQMS and AWS, both models performed poorly.

• Tuberculosis and Respiratory Diseases
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• v.53 no.5
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• pp.497-509
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• 2002

Background : The mechanisms through which cellular activation results in intracellular mycobacterial killing is only partially understood. However, in vitro studies of human immunity to Mycobacterium tuberculosis have been largely modeled on the work reported by Crowle, which is complicated by several factors. The whole blood culture is simple and allows the simultaneous analysis of the relationship between bacterial killing and the effect of effector cells and humoral factors. In this study, we attempted to determine the extent to which M. tuberculosis is killed in a human whole blood culture and to explore the role of the host and microbial factor in this process. Methods : The PPD positive subject were compared to the umbilical cord blood and patients with tuberculosis, diabetes and lung cancer. The culture is performed using heparinized whole blood diluted with a culture medium and infected with a low number of M. avium or M. tuberculosis $H_{37}Ra$ for 4 days by rotating the culture in a $37^{\circ}C$, 5% $CO_2$ incubator. In some experiments, methlprednisolone- or pentoxifyline were used to inhibit the immune response. To assess the role of the T-cell subsets, CD4+, CD8+ T-cells or both were removed from the blood using magnetic beads. The ${\Delta}$ log killing ratio was defined using a CFU assay as the difference in the log number of viable organisms in the completed culture compared to the inoculum. Results : 1. A trend was noted toward the improved killing of mycobacteria in PPD+ subjects comparing to the umbilical cord blood but there was no specific difference in the patients with tuberculosis, diabetes and lung cancer. 2. Methylprednisolone and pentoxifyline adversely affected the killing in the PPD+ subjects umbilical cord blood and patients with tuberculosis. 3. The deletion of CD4+ or CD8+ T-lymphocytes adversely affected the killing of M. avium and M. tuberculosis $H_{37}Ra$ by PPD+ subjects. Deletion of both cell types had an additive effect, particularly in M. tuberculosis $H_{37}Ra$. 4. A significantly improved mycobacterial killing was noted after chemotherapy in patients with tuberculosis and the ${\Delta}$ logKR continuously decreased in a 3 and 4 days of whole blood culture. Conclusion : The in vitro bactericidal assay by human whole blood culture model was settled using a CFU assay. However, the host immunity to M. tuberculosis was not apparent in the human whole blood culture bactericidal assay, and patients with tuberculosis showed markedly improved bacterial killing after anti-tuberculous chemotherapy compared to before. The simplicity of a whole blood culture facilitates its inclusion in a clinical trial and it may have a potential role as a surrogate marker in a TB vaccine trial.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.285-292
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• 2023

Recently, the impact of fine dust on health has become a major topic. Fine dust is dangerous because it can penetrate the body and affect the respiratory system, without being filtered out by the mucous membrane in the nose. Since fine dust is directly related to the industry, it is practically impossible to completely remove it. Therefore, if the concentration of fine dust can be predicted in advance, pre-emptive measures can be taken to minimize its impact on the human body. Fine dust can travel over 600km in a day, so it not only affects neighboring areas, but also distant regions. In this paper, wind direction and speed data and a time series prediction model were used to predict the concentration of fine dust in Seoul, and the correlation between the concentration of fine dust in Seoul and the concentration in each region was confirmed. In addition, predictions were made using the concentration of fine dust in each region and in Seoul. The lowest MAE (mean absolute error) in the prediction results was 12.13, which was about 15.17% better than the MAE of 14.3 presented in previous studies.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• Tuberculosis and Respiratory Diseases
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• v.53 no.1
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• pp.5-16
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• 2002

Background : Though mononuclear phagocytes serve as the final effectors in killing intracellular Mycobacterium tuberculosis, the bacilli readily survive in the intracellular environment of resting cells. The mechanisms through which cellular activation results in the intracellular killing is unclear. In this study, we sought to explore an in vitro model of a low-level infection of human mononuclear phagocytes with MAC and $H_{37}Ra$ and determine the extent of the lymphocyte dependent cytotoxicity of human monocytes and alveolar macrophages. Materials and Methods : The peripheral monocytes were prepared using the Ficoll gradient method from PPD positive healthy people and tuberculosis patients. The alveolar macrophages were prepared from PPD positive healthy people via a bronchoalveolar lavage. The human mononuclear phagocytes were infected at a low infection rate (bacilli:phagocyte 1:10) with MAC(Mycobacterium avium) and Mycobacterium tuberculosis $H_{37}Ra$. Non-adherent cells(lymphocyte) were added at a 10:1 ratio. After 1,4, and 7 days culture in $37^{\circ}C$, 5% CO2 incubator, the cells were harvested and inoculated in a 7H10/OADC agar plate for the CFU assay. The bacilli were calculated with the CFU/$1{\times}10^6$ of the cells and the cytotoxicity was expressed as the log killing ratio. Results : The intracellular killing of MAC and $H_{37}Ra$ within the monocyte was greater in patients with tuberculosis compared to the PPD positive controls (p<0.05). Intracellular killing of MAC and $H_{37}Ra$ within the alveolar macrophage appeared to be greater than that within the monocytes of the PPD positive controls. There was significant lymphocyte dependent inhibition of intracellular growth of the mycobacteria within the monocytes in both the controls and tuberculosis patients and within the macrophages in the controls(p<0.05). There was no specific difference in the virulence between the MAC and the $H_{37}Ra$. Conclusion : This study is an in vitro model of a low-level infection with MAC and $H_{37}Ra$ of human mononuclear phagocytes. The intracellular cytotoxicity of the mycobacteria within the phagocytic cells was significantly lymphocyte dependent. During the 7 days culture after the intracellular phagocytosis, the actual confinement of the mycobacteria was observed within the monocytes of tuberculosis patients and the alveolar macrophages of the controls as in the case of adding lymphocytes.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.63-75
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• 2023

Due to the development of industry, interest in air pollutants has increased. Air pollutants have affected various fields such as environmental pollution and global warming. Among them, environmental diseases are one of the fields affected by air pollutants. Air pollutants can affect the human body's skin or respiratory tract due to their small molecular size. As a result, various studies on air pollutants and environmental diseases have been conducted. Asthma, part of an environmental disease, can be life-threatening if symptoms worsen and cause asthma attacks, and in the case of adult asthma, it is difficult to cure once it occurs. Factors that worsen asthma include particulate matter and air pollution. Asthma is an increasing prevalence worldwide. In this paper, we study how air pollutants correlate with the number of emergency room admissions in asthma patients and predict the number of future asthma emergency patients using highly correlated air pollutants. Air pollutants used concentrations of five pollutants: sulfur dioxide(SO₂), carbon monoxide(CO), ozone(O₃), nitrogen dioxide(NO₂), and fine dust(PM₁₀), and environmental diseases used data on the number of hospitalizations of asthma patients in the emergency room. Data on the number of emergency patients of air pollutants and asthma were used for a total of 5 years from January 1, 2013 to December 31, 2017. The model made predictions using two models, Informer and LTSF-Linear, and performance indicators of MAE, MAPE, and RMSE were used to measure the performance of the model. The results were compared by making predictions for both cases including and not including the number of emergency patients. This paper presents air pollutants that improve the model's performance in predicting the number of asthma emergency patients using Informer and LTSF-Linear models.