• Journal of Microbiology and Biotechnology
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• v.31 no.12
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• pp.1716-1721
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• 2021

Chikungunya fever is an arboviral disease caused by the Chikungunya virus (CHIKV). The disease has similar clinical manifestations with other acute febrile illnesses which complicates differential diagnosis in low-resource settings. We aimed to develop a rapid test for CHIKV detection based on the nucleic acid lateral flow immunoassay technology. The system consists of a primer set that recognizes the E1 region of the CHIKV genome and test strips in an enclosed cassette which are used to detect amplicons labeled with FITC/biotin. Amplification of the viral genome was done using open-source PCR, a low-cost open-source thermal cycler. Assay performance was evaluated using a panel of RNA isolated from patients' blood with confirmed CHIKV (n = 8) and dengue virus (n = 20) infection. The open-source PCR-NALFIA platform had a limit of detection of 10 RNA copies/ml. The assay had a sensitivity and specificity of 100% (95% CI: 67.56% - 100%) and 100% (95% CI: 83.89% - 100%), respectively, compared to reference standards of any positive virus culture on C6/36 cell lines and/or qRT-PCR. Further evaluation of its performance using a larger sample size may provide important data to extend its usefulness, especially its utilization in the peripheral healthcare facilities with scarce resources and outbreak situations.

• Research in Community and Public Health Nursing
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• v.32 no.4
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• pp.415-429
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• 2021

Purpose: The purpose of this study was to develop the Self-Care Non-adherence Risk Assessment Scale (SCNRAS) for patients with chronic illness in South Korea. Methods: This study was conducted from April to July, 2020 and utilized a convenience sampling method to recruit 336 patients with chronic illness from three hospitals located in South Korea. The content, factorial structure, item-convergent/discriminant validity, convergent validity, internal consistency reliability, and test-retest reliability of the scale were evaluated. The data were analyzed using exploratory and confirmatory factor analyses, Pearson's correlation coefficient, Cronbach's α, and intra-class correlation coefficient. Results: The exploratory and confirmatory factor analyses yielded six-factors. Convergent validity was demonstrated using measures of defining issues. Internal consistency reliability and test-retest reliability were found to be acceptable, as indicated by a Cronbach's α of .65~.81 and an intra-class correlation coefficient of .93~.98. The Self-Care Non-adherence Risk Assessment Scale for patients with chronic illness is a new instrument that comprehensively measures the knowledge, skill, physical function status, access to health care, social support, motivation, and confidence. It comprises 18 items scored on a 5-point Likert scale. The validity and reliability of the scale were verified. Conclusion: The scale developed through this study is expected to screen those who need nursing intervention early by predicting the self-care non-adherence risk group.

• Atmosphere
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• v.31 no.5
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• pp.489-510
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• 2021

In this paper, we propose an algorithm for detecting convective initiation (CI) using GEO-KOMPSAT-2A/advanced meteorological imager data. The algorithm identifies clouds that are likely to grow into convective clouds with radar reflectivity greater than 35 dBZ within the next two hours. This algorithm is developed using statistical and qualitative analysis of cloud characteristics, such as atmospheric instability, cloud top height, and phase, for convective clouds that occurred on the Korean Peninsula from June to September 2019. The CI algorithm consists of four steps: 1) convective cloud mask, 2) cloud object clustering and tracking, 3) interest field tests, and 4) post-processing tests to remove non-convective objects. Validation, performed using 14 CI events that occurred in the summer of 2020 in Korean Peninsula, shows a total probability of detection of 0.89, false-alarm ratio of 0.46, and mean lead-time of 39 minutes. This algorithm can be useful warnings of rapidly developing convective clouds in future by providing information about CI that is otherwise difficult to predict from radar or a numerical prediction model. This CI information will be provided in short-term forecasts to help predict severe weather events such as localized torrential rainfall and hail.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2276-2296
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• 2022

This study validates the applicability of the CUPID code for simulating subcooled wall boiling under high-pressure conditions against number of DEBORA tests. In addition, a new numerical technique in which the interfacial momentum non-drag forces are calculated at the cell faces rather than the center is presented. This method reduced the numerical instability often triggered by calculating these terms at the cell center. Simulation results showed good agreement against the experimental data except for the bubble sizes in the bulk. Thus, a new model to calculate the Sauter mean diameter is proposed. Next, the effect of the relationship between the bubble departure diameter (D_dep) and the nucleation site density (N) on the performance of the Wall Heat Flux Partitioning (WHFP) model is investigated. Three correlations for D_dep and two for N are grouped into six combinations. Results by the different combinations show that despite the significant difference in the calculated D_dep, most combinations reasonably predict vapor distribution and liquid temperature. Analysis of the axial propagations of wall boiling parameters shows that the N term stabilizes the inconsistences in D_dep values by following a behavior reflective of D_dep to keep the total energy balance. Moreover, ratio of the heat flux components vary widely along the flow depending on the combinations. These results suggest that separate validation of D_dep correlations may be insufficient since its performance relies on the accompanying N correlations.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2367-2375
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• 2022

In this work, we propose a new mechanistic model for the treatment of helium behaviour at the grain boundaries in oxide nuclear fuel. The model provides a rate-theory description of helium inter-granular behaviour, considering diffusion towards grain edges, trapping in lenticular bubbles, and thermal resolution. It is paired with a rate-theory description of helium intra-granular behaviour that includes diffusion towards grain boundaries, trapping in spherical bubbles, and thermal re-solution. The proposed model has been implemented in the meso-scale software designed for coupling with fuel performance codes SCIANTIX. It is validated against thermal desorption experiments performed on doped UO₂ samples annealed at different temperatures. The overall agreement of the new model with the experimental data is improved, both in terms of integral helium release and of the helium release rate. By considering the contribution of helium at the grain boundaries in the new model, it is possible to represent the kinetics of helium release rate at high temperature. Given the uncertainties involved in the initial conditions for the inter-granular part of the model and the uncertainties associated to some model parameters for which limited lower-length scale information is available, such as the helium diffusivity at the grain boundaries, the results are complemented by a dedicated uncertainty analysis. This assessment demonstrates that the initial conditions, chosen in a reasonable range, have limited impact on the results, and confirms that it is possible to achieve satisfying results using sound values for the uncertain physical parameters.

• Geomechanics and Engineering
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• v.30 no.4
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• pp.373-382
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• 2022

Unsaturated soil at high suctions is widespread. Many civil engineering projects are related to the hydro-mechanical behavior of unsaturated soils at high suctions, particularly in arid and semiarid areas. To investigate water retention behaviors of nine clayey soils (one is classified as fat clay and the others are classified as lean clay according to the unified soil classification system), the high suction (3.29-286.7 MPa) was imposed on the specimens at zero net stress by the vapor equilibrium technique. In this paper, the effect of void ratio on the water retention behavior at high suction was discussed in detail. Validation data showed that soil types, i.e., different mineralogical compositions, are critical in the soil water retention behavior at a high suction range. Second, the hysteresis behavior at a high suction range is mainly related to the clay content and the specific surface area. And the mechanism of water retention and hysteresis behavior at high suctions was discussed. Moreover, the maximum suction is not a unique value, and it is crucial to determine the maximum suction value accurately, especially for the shear strength prediction at high suctions. If the soil consists of hydrophilic minerals such as montmorillonite and illite, the maximum suction will be lower than 10⁶ kPa. Finally, using the area of hysteresis to quantify the degree of hysteresis at a high suction range is proposed. There was a good correlation between the area of hydraulic hysteresis and the specific surface area.

• Journal of Radiation Protection and Research
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• v.47 no.2
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• pp.77-85
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• 2022

Background: After the Fukushima Daiichi Nuclear Power Station (FDNPS) accident, a model was developed to estimate the external exposure doses for residents who were expected to return to their homes after evacuation orders were lifted. However, the model's accuracy and uncertainties in parameters used to estimate external doses have not been evaluated. Materials and Methods: The model estimates effective doses based on the integrated ambient dose equivalent (H^*(10)) and life patterns, considering a dose reduction factor to estimate the indoor H^*(10) and a conversion factor from H^*(10) to the effective dose. Because personal dose equivalent (H_p(10)) has been reported to agree well with the effective dose after the FDNPS accident, this study validates the model's accuracy by comparing the estimated effective doses with H_p(10). The H_p(10) and life pattern data were collected for 36 adult participants who lived or worked near the FDNPS in 2019. Results and Discussion: The estimated effective doses correlated significantly with H_p(10); however, the estimated effective doses were lower than H_p(10) for indoor sites. A comparison with the measured indoor H^*(10) showed that the estimated indoor H^*(10) was not underestimated. However, the H_p(10) to H^*(10) ratio indoors, which corresponds to the practical conversion factor from H^*(10) to the effective dose, was significantly larger than the same ratio outdoors, meaning that the conversion factor of 0.6 is not appropriate for indoors due to the changes in irradiation geometry and gamma spectra. This could have led to a lower effective dose than H_p(10). Conclusion: The estimated effective doses correlated significantly with H_p(10), demonstrating the model's applicability for effective dose estimation. However, the lower value of the effective dose indoors could be because the conversion factor did not reflect the actual environment.

• Genomics & Informatics
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• v.19 no.4
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• pp.37.1-37.7
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• 2021

Genome-wide association studies (GWASs) facilitated the discovery of countless disease-associated variants. However, GWASs have mostly been conducted in European ancestry samples. Recent studies have reported that these European-based association results may reduce disease prediction accuracy when applied in non-Europeans. Therefore, previously reported variants should be validated in non-European populations to establish reliable scientific evidence for precision medicine. In this study, we validated known associations with type 2 diabetes (T2D) and related metabolic traits in 125,850 samples from a Korean population genotyped by the Korea Biobank Array (KBA). At the end of December 2020, there were 8,823 variants associated with glycemic traits, lipids, liver enzymes, and T2D in the GWAS catalog. Considering the availability of imputed datasets in the KBA genome data, publicly available East Asian T2D summary statistics, and the linkage disequilibrium among the variants (r² < 0.2), 2,900 independent variants were selected for further analysis. Among these, 1,837 variants (63.3%) were statistically significant (p ≤ 0.05). Most of the non-replicated variants (n = 1,063) showed insufficient statistical power and decreased minor allele frequencies compared with the replicated variants. Moreover, most of known variants showed <10% genetic heritability. These results could provide valuable scientific evidence for future study designs, the current power of GWASs, and future applications in precision medicine in the Korean population.

• Atmosphere
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• v.31 no.5
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• pp.473-488
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• 2021

A new physical/statistical diagnostic downscale model has been developed for use to improve near-surface air temperature forecasts. The model includes a series of physical and statistical correction methods that account for un-resolved topographic and land-use effects as well as statistical bias errors in a low-resolution atmospheric model. Operational temperature forecasts of the Local Data Assimilation and Prediction System (LDAPS) were downscaled at 100 m resolution for three months, which were used to validate the model's physical and statistical correction methods and to compare its performance with the forecasts of the Korea Meteorological Administration Post-processing (KMAP) system. The validation results showed positive impacts of the un-resolved topographic and urban effects (topographic height correction, valley cold air pool effect, mountain internal boundary layer formation effect, urban land-use effect) in complex terrain areas. In addition, the statistical bias correction of the LDAPS model were efficient in reducing forecast errors of the near-surface temperatures. The new high-resolution downscale model showed better agreement against Korean 584 meteorological monitoring stations than the KMAP, supporting the importance of the new physical and statistical correction methods. The new physical/statistical diagnostic downscale model can be a useful tool in improving near-surface temperature forecasts and diagnostics over complex terrain areas.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.5
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• pp.161-168
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• 2021

Cracks affect the robustness of infrastructures such as buildings, bridge, pavement, and pipelines. This paper presents an automated crack detection system which detect cracks in diverse surfaces. We first constructed the combined crack dataset, consists of multiple crack datasets in diverse domains presented in prior studies. Then, state-of-the-art deep learning models in computer vision tasks including VGG, ResNet, WideResNet, ResNeXt, DenseNet, and EfficientNet, were used to validate the performance of crack detection. We divided the combined dataset into train (80%) and test set (20%) to evaluate the employed models. DenseNet121 showed the highest accuracy at 96.20% with relatively low number of parameters compared to other models. Based on the validation procedures of the advanced deep learning models in crack detection task, we shed light on the cost-effective automated crack detection system which can be applied to different surfaces and structures with low computing resources.