• Nutrition Research and Practice
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• v.15 no.1
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• pp.95-105
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• 2021

BACKGROUND/OBJECTIVES: The measurement of body composition, including muscle and fat mass, remains challenging in large epidemiological studies due to time constraint and cost when using accurate modalities. Therefore, this study aimed to develop and validate prediction equations according to sex to measure lean body mass (LBM), appendicular skeletal muscle mass (ASM), and body fat mass (BFM) using anthropometric measurement, serum creatinine level, and lifestyle factors as independent variables and dual-energy X-ray absorptiometry as the reference method. SUBJECTS/METHODS: A sample of the Korean general adult population (men: 7,599; women: 10,009) from the Korean National Health and Nutrition Examination Survey 2008-2011 was included in this study. The participants were divided into the derivation and validation groups via a random number generator (with a ratio of 70:30). The prediction equations were developed using a series of multivariable linear regressions and validated using the Bland-Altman plot and intraclass correlation coefficient (ICC). RESULTS: The initial and practical equations that included age, height, weight, and waist circumference had a different predictive ability for LBM (men: R2 = 0.85, standard error of estimate [SEE] = 2.7 kg; women: R2 = 0.78, SEE = 2.2 kg), ASM (men: R2 = 0.81, SEE = 1.6 kg; women: R2 = 0.71, SEE = 1.2 kg), and BFM (men: R2 = 0.74, SEE = 2.7 kg; women: R2 = 0.83, SEE = 2.2 kg) according to sex. Compared with the first prediction equation, the addition of other factors, including serum creatinine level, physical activity, smoking status, and alcohol use, resulted in an R2 that is higher by 0.01 and SEE that is lower by 0.1. CONCLUSIONS: All equations had low bias, moderate agreement based on the Bland-Altman plot, and high ICC, and this result showed that these equations can be further applied to other epidemiologic studies.

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.1
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• pp.67-74
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• 2022

To analyze the motion of aircraft through computing the dynamics equations, true airspeed is essential for obtaining aerodynamic loads. Although the airspeed is measured by on-board instruments such as pitot tubes, measurement data are difficult to obtain for commercial flights because they include sensitive data about the airline operations. One of the commonly available trajectory data, Automatic Dependent Surveillance-Broadcast data, provide aircraft's speed in the form of ground speed. The ground speed is a vector sum of the local wind velocity and the true airspeed. This paper present a method to estimate true airspeed by combining the trajectory, meteorological, and topology data available to the public. To integrate each data, we first matched the coordinate system and then unified the altitude reference to the mean sea level. We calculated the wind vector for all trajectory points by interpolating from the lower resolution grid of the meteorological data. Finally, we calculate the true airspeed from the ground speed and the wind vector. These processes were applied to several sample trajectories with corresponding meteorological data and the topology data, and the estimated true airspeeds are presented.

• Journal of Veterinary Science
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• v.23 no.4
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• pp.51.1-51.10
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• 2022

Background: Due to the unavailability of an effective vaccine or antiviral drug against the African swine fever virus (ASFV), rapid diagnosis methods are needed to prevent highly contagious African swine fever. Objectives: The objective of this study was to establish the ladder-shape melting temperature isothermal amplification (LMTIA) assay for the detection of ASFV. Methods: LMTIA primers were designed with the p72 gene of ASFV as the target, and plasmid pUC57 was used to clone the gene. The LMTIA reaction system was optimized with the plasmid as the positive control, and the performance of the LMTIA assay was compared with that of the commercial real-time polymerase chain reaction (PCR) kit in terms of sensitivity and detection rate using 200 serum samples. Results: Our results showed that the LMTIA assay could detect the 10⁴ dilution of DNA extracted from the positive reference serum sample, which was the same as that of the commercial real-time PCR kit. The coincidence rate between the two assays was 100%. Conclusions: The LMTIA assay had high sensitivity, good detection, and simple operation. Thus, it is suitable for facilitating preliminary and cost-effective surveillance for the prevention and control of ASFV.

• Health Policy and Management
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• v.32 no.2
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• pp.216-227
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• 2022

Background: Food insecurity may contribute to mental health indicators such as stress, anxiety, or depression. We investigated whether food insecurity was associated with mental health indicators and health-related quality of life (HRQoL) in a representative sample of the Korean population. Methods: This study enrolled 12,987 adults without a history of medically serious disease from the 2012, 2013, and 2015 Korea National Health and Nutrition Examination Survey. Household food security status was categorized as "food security," "mild food insecurity," and "moderate/severe food insecurity." The association between mental health and HRQoL was evaluated using a multivariate logistic regression model with food security as the reference group. Results: The adjusted odds ratio of adverse mental health or low HRQoL increased significantly in mild or moderate/severe food insecurity compared to food security. In the moderate/severe food insecurity group, it was 1.98% (95% confidence interval [CI], 1.31-2.99) higher for perceived stress, 3.58% (95% CI, 2.44-5.26) higher for depression symptoms, 4.16% (95% CI, 2.68-6.45) higher for suicidal ideation, and 2.81% (95% CI, 1.91-4.15) higher for quality of life. Conclusion: Food insecurity was strongly associated with negative mental health status and poor HRQoL. There is a need for a dietary support program that provides psychosocial support to those experiencing food insecurity.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.2
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• pp.218-223
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• 2022

Cholesterol is an essential component for maintaining health; however, excessive consumption can lead to diseases. Thus, continuous monitoring of cholesterol content is important in food research. The cholesterol analysis method used in Korea follows the Korean Food Standards Codex. As this method uses gas chromatography, derivatization of the sample is required, and analysis time is more than 30 min. Kim developed a new method using liquid chromatography; however saponification by the non-heat saponification method is insufficient. To address these limitations, a new cholesterol analysis method was developed and verified. The correlation coefficients for the cholesterol standard (STD) were maintained above 0.99. The limit of detection and limit of quantitation of cholesterol STD were 2.41 ㎍/mL and 7.31 ㎍/mL, respectively. The accuracies for cholesterol were 92.21-99.02%. The developed analytical method was also verified using three standard reference materials, and their accuracies were 93.71-97.09%. In addition, the cholesterol content of fishes was analyzed, and the values were compared with those recorded by the United States Department of Agriculture. Our results suggest that this method could be used as a new analytical method for cholesterol in seafood.

• Journal of the Korean Wood Science and Technology
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• v.32 no.5
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• pp.45-50
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• 2004

Currently, structural design of wood structure has been based on ASD (Allowable Structural Design) in Korea. However, the results from this method was known as greater than real value because variations of materials and various conditions were not considered sufficiently. So the study about the design method with probabilistic approach is being performed to overcome this problem. And the standard design method of RBD (Reliability Based Design) has been established and applied. In this study, to apply this method on the domestic wood, the distribution property of the lumber and Glulam was analyzed from the previous report and the basis of the standardized design method was established as soft conversion method from allowable stress used in ASD into reference resistance used in RBD. And through the additional study about the sample size as a important factor to effect on soft conversion, condition to be required in more accurate conversion was evaluated.

• Journal of Veterinary Science
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• v.24 no.1
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• pp.11.1-11.14
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• 2023

Background: Peripheral blood mononuclear cells (PBMCs) are commonly used to assess in vitro immune responses. However, PBMC isolation is a time-consuming procedure, introduces technical variability, and requires a relatively large volume of blood. By contrast, whole blood assay (WBA) is faster, cheaper, maintains more physiological conditions, and requires less sample volume, laboratory training, and equipment. Objectives: Herein, this study aimed to develop a porcine WBA for in vitro evaluation of immune responses. Methods: Heparinized whole blood (WB) was diluted (non-diluted, 1/2, 1/8, and 1/16) in RPMI-1640 media, followed by phorbol myristate acetate and ionomycin. After 24 h, cells were stained for interferon (IFN)-γ secreting T-cells followed by flow cytometry, and the supernatant was analyzed for tumor necrosis factor (TNF)-α. In addition, diluted WB was stimulated by lipopolysaccharide (LPS) and polyinosinic:polycytidylic acid (poly I:C), reference strain KCTC3557 (RS), field isolate (FI), of heat-killed (HK) Streptococcus suis, and porcine reproductive and respiratory syndrome virus (PRRSV). Results: The frequency of IFN-γ⁺CD3⁺ T-cells and concentration of TNF-α in the supernatant of WB increased with increasing dilution factor and were optimal at 1/8. WB TNF-α and interleukin (IL)-10 cytokine levels increased significantly following stimulation with LPS or poly I:C. Further, FI and RS induced IL-10 production in WB. Additionally, PRRSV strains increased the frequency of IFN-γ⁺ CD4^-CD8⁺ cells, and IFN-γ was non-significantly induced in the supernatant of re-stimulated samples. Conclusions: We propose that the WBA is a rapid, reliable, and simple method to evaluate immune responses and WB should be diluted to trigger immune cells.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.1015-1026
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• 2021

The objective of this study was to determine amino acid and protein contents of brown and milled non-glutinous rice of 13 cultivars in Korea. Protein contents of MRs (milled rices) were in order of Haepum (7.27%) > Hanareum No. 4 (7.14%) > Odae (6.84%). Protein contents of BRs (brown rices) were in order of Haepum (7.68%) > Odae (7.63%) > Hanareum No. 4 (7.60%). The amino acid content was the highest in Haepum (MR 5.76%, BR 6.49%), followed by Haedeul (MR 5.71%, BR 6.30%), and Odae (MR 5.63%, BR 6.29%). The essential amino acid contents of non-glutinous rices were in order of Haepum (MR 2.34%, BR 2.57%) > Haedeul (MR 2.31%, BR 2.48%) > Odae (MR 2.20%, BR 2.56%). The contents of amino acid and protein in BRs were considerably higher than those in MRs. Protein and most of amino acid contents were higher in Haepum than the other cultivars. The certificated reference material (CRM) 1849a (infant/adults nutritional formular) from National Institute of Standard and Technology (NIST) was used as the test sample to determine the precision and accuracy of the analytical method. The regression analyses revealed good correlations (correlation coefficient), greater than 0.99. The recovery values of the amino acids ranged from 93.17 to 99.59%. The limit of detection (LODs) ranged from 0.01 - 0.07 mg·100 g^-1 and the limit of quantitation (LOQs) ranged from 0.03 - 0.21 mg·100 g^-1 for all analytes.

• Smart Structures and Systems
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• v.31 no.5
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• pp.469-483
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• 2023

The dynamic characteristics of wind turbine blades are usually monitored by contact sensors with the disadvantages of high cost, difficult installation, easy damage to the structure, and difficult signal transmission. In view of the above problems, based on computer vision technology and the improved YOLOv5 (You Only Look Once v5) deep learning model, a non-contact dynamic characteristic monitoring method for wind turbine blade is proposed. First, the original YOLOv5l model of the CSP (Cross Stage Partial) structure is improved by introducing the CSP2_2 structure, which reduce the number of residual components to better the network training speed. On this basis, combined with the Deep sort algorithm, the accuracy of structural displacement monitoring is mended. Secondly, for the disadvantage that the deep learning sample dataset is difficult to collect, the blender software is used to model the wind turbine structure with conditions, illuminations and other practical engineering similar environments changed. In addition, incorporated with the image expansion technology, a modeling-based dataset augmentation method is proposed. Finally, the feasibility of the proposed algorithm is verified by experiments followed by the analytical procedure about the influence of YOLOv5 models, lighting conditions and angles on the recognition results. The results show that the improved YOLOv5 deep learning model not only perform well compared with many other YOLOv5 models, but also has high accuracy in vibration monitoring in different environments. The method can accurately identify the dynamic characteristics of wind turbine blades, and therefore can provide a reference for evaluating the condition of wind turbine blades.