• Journal of Preventive Medicine and Public Health
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• v.57 no.3
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• pp.279-287
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• 2024

Objectives: This study validated the Vietnamese version of the Disaster Adaptation and Resilience Scale (DARS) for use in vulnerable communities in Vietnam. Methods: This was a cross-sectional study involving 595 adults from 2 identified communities. The original DARS assessment tool was translated, and the validity and reliability of the Vietnamese version of DARS (V-DARS) were assessed. The internal consistency of the overall scale and its subscales was evaluated using Cronbach's alpha and McDonald's omega reliability coefficients. Confirmatory factor analysis (CFA) was employed to evaluate its construct validity, building upon the factor structure identified in exploratory factor analysis (EFA). Construct validity was assessed based on convergent and discriminant validity. Results: Following the established criteria for EFA, 8 items were removed, resulting in a refined V-DARS structure comprising 35 items distributed across 5 distinct factors. Both alpha and omega reliability coefficients indicated strong internal consistency for the overall scale (α=0.963, ω=0.963) and for each of the 5 sub-scales (all>0.80). The CFA model also retained the 5-factor structure with 35 items. The model fit indices showed acceptable values (RMSEA: 0.072; CFI: 0.912; TLI: 0.904; chi-square test: <0.01). Additionally, the convergent and discriminant validity of the V-DARS were deemed appropriate and satisfactory for explaining the measurement structure. Conclusions: Our findings suggest that the V-DARS is a valid and reliable scale for use within vulnerable communities in Vietnam to assess adaptive responses to natural disasters. It may also be considered for use in other populations.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.847-860
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• 2022

Purpose: The purpose of this paper is to present a basic study on the development of a self-generation infrastructure for monitoring the health of harbour structures. Method: By developing a self-generation system and fiber optic sensors for seawater, the study provides basic research data on port structure health monitoring. Result: Through sunlight simulation analysis, 4-5 hours of sunlight can be secure in the domestic environment. Through this, the optical splitter (Introgate) that collects the raw data from the FBG sensor applicable to seawater, the MCU that calculates it, the IoT module with wireless communication functionality, the monitoring server and the supply system are set up. Conclusion: Monitoring port structures directly with fiber optic probes (FBG) and the possibility of using selfpowered systems were confirmed.

• The Korean Journal of Health Service Management
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• v.12 no.4
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• pp.139-154
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• 2018

Objectives: The aim of this study was to examine factors influencing health-related quality of life of waged workers. Methods: This study used data from the Seventh Korea National Health and Nutrition Examination Survey. Data were analyzed with the $x^2-test$, t-test, ANOVA, and multiple regression. Results: The significant predictors of health-related quality of life were depression, subjective health status, age, activity limitation, education, worker status, monthly income, drinking, smoking, physical injury, stress, and moderate physical activity. Conclusions: Personal health characteristics, psychological characteristics, socioeconomic characetrictics and working characetrictics affect health-related quality of life. Health-related quality of life is also affected by social structural problems such as socioeconomic factors and employment instabilitye. In addition to the development of health care programs to improve health-related quality of life of twaged workers, policy changes are needed to improve the social structure.

• Journal of Microbiology and Biotechnology
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• v.33 no.9
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• pp.1213-1227
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• 2023

Fetal growth restriction (FGR) is a prevalent obstetric condition. This study aimed to investigate the role of Toll-like receptor 9 (TLR9) in regulating the inflammatory response and gut microbiota structure in FGR. An FGR animal model was established in rats, and ODN1668 and hydroxychloroquine (HCQ) were administered. Changes in gut microbiota structure were assessed using 16S rRNA sequencing, and fecal microbiota transplantation (FMT) was conducted. HTR-8/Svneo cells were treated with ODN1668 and HCQ to evaluate cell growth. Histopathological analysis was performed, and relative factor levels were measured. The results showed that FGR rats exhibited elevated levels of TLR9 and myeloid differentiating primary response gene 88 (MyD88). In vitro experiments demonstrated that TLR9 inhibited trophoblast cell proliferation and invasion. TLR9 upregulated lipopolysaccharide (LPS), LPS-binding protein (LBP), interleukin (IL)-1β and tumor necrosis factor (TNF)-α while downregulating IL-10. TLR9 activated the TARF3-TBK1-IRF3 signaling pathway. In vivo experiments showed HCQ reduced inflammation in FGR rats, and the relative cytokine expression followed a similar trend to that observed in vitro. TLR9 stimulated neutrophil activation. HCQ in FGR rats resulted in changes in the abundance of Eubacterium_coprostanoligenes_group at the family level and the abundance of Eubacterium_coprostanoligenes_group and Bacteroides at the genus level. TLR9 and associated inflammatory factors were correlated with Bacteroides, Prevotella, Streptococcus, and Prevotellaceae_Ga6A1_group. FMT from FGR rats interfered with the therapeutic effects of HCQ. In conclusion, our findings suggest that TLR9 regulates the inflammatory response and gut microbiota structure in FGR, providing new insights into the pathogenesis of FGR and suggesting potential therapeutic interventions.

• Journal of the Korean Society of Safety
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• v.36 no.3
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• pp.50-59
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• 2021

The main purpose of accident analysis is to identify the causal factors and the mechanisms of those factors leading to the accident. However, current accident analysis techniques focus only on finding the factors related to the accident without providing more insightful results, such as structures or mechanisms. For this reason, preventive actions for safety management are concentrated on the elimination of causal factors rather than blocking the connection or chain of accident processes. This greatly reduces the effectiveness of safety management in practice. In the present study, a technique to model the correlational structure of accident risk factors is proposed by using the co-occurrence keyword network analysis technique. To investigate the effectiveness of the proposed technique, a case study involving a portable ladder fall accident is conducted. The results indicate that the proposed technique can construct the correlational structure model of the risk factors of a portable ladder fall accident. This proves the effectiveness of the proposed technique in modeling the correlational structure of accident risk factors.

• Korea Journal of Hospital Management
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• v.2 no.1
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• pp.162-182
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• 1997

This study was carried out to assess the current status of hospital wage structure and to find out the characteristics and problems in the current hospital wage structure. so as to provide empirical data for establishing a rational wage structure. The data were collected from administrative personnels in charge of wage management in 31 hospitals by using a structured questionnaire through direct visiting and mailing in Pusan Metropolitan City. The major findings in this study were as follows: First, the hospital wage structure applied differently to the basic wages between doctors and the other employees. The wage structure for doctors included performance rate of 51.6%, followed by a synthesis rate of 29.0%, while the wage for the other employees had the synthesis rate of 74.2%, followed by the seniority rate of 12.9%. Second, the wage consisted of a basic wage for 57.5%. the allowance for 21.1% and monthly installed bonus for 21.4%, and the basic wage comprised 68.3% of the total wage for doctors, as compared to 51.9% for nurses and medical technicians and 52.4% for administrative and managerial personnel. The annual rate of the bonus was average 460%, and 96.8% of the hospital did not consider personnel preformance appraisal when paying the bonus. Third, 80.6% of the hospitals applied the legal rate to the retirement allowance while 19.4% applying cumulative rates more than the legal rate, and all of university hospitals applied cumulative rates. Retirement reserves were practiced only in 54.9% of the hospitals. Forth, many hospitals seemed to be interested in applying graded wage system according to performance, by showing that 42.9% of the hospitals were planning to apply it in the future, despite only 9.7% practicing it. Fifth, the wage structure appeared to be complicated due to various kinds of allowances. The kind of the allowances varied among hospitals, ranging from 2 to 26 kinds, and increased as the size of hospital was larger. Sixth, the opinions leading to improve the basic wage structure favored the seniority rate for 51.6% either to maintain the present seniority rate(16.1%) or to apply the incentive pay in addition to the senior rate(35.5%). and also favored the performance rate for 35.5%, followed by the job rate for 12.9%. In conclusion, the current hospital wage structure seemed to be too complicated to reflect personal ability, contribution and performance and to become a big barrier to inducing worker's motivation and to strengthening in competitveness. Therefore it is suggested that the current wage structure should be revised to the one emphasizing on job and ability base with considering characteristics and situation of the hospital, rather than seniority factors.

• Smart Structures and Systems
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• v.24 no.4
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• pp.507-524
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• 2019

A Bayesian dynamic linear model (BDLM) is presented for a data-driven analysis for response prediction and load effect separation of a revolving auditorium structure, where the main loads are self-weight and dead loads, temperature load, and audience load. Analyses are carried out based on the long-term monitoring data for static strains on several key members of the structure. Three improvements are introduced to the ordinary regression BDLM, which are a classificatory regression term to address the temporary audience load effect, improved inference for the variance of observation noise to be updated continuously, and component discount factors for effective load effect separation. The effects of those improvements are evaluated regarding the root mean square errors, standard deviations, and 95% confidence intervals of the predictions. Bayes factors are used for evaluating the probability distributions of the predictions, which are essential to structural condition assessments, such as outlier identification and reliability analysis. The performance of the present BDLM has been successfully verified based on the simulated data and the real data obtained from the structural health monitoring system installed on the revolving structure.

• Biomedical Science Letters
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• v.17 no.4
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• pp.321-328
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• 2011

This study divided a group of healthy adults aged 20 or older who had a health examination at J General Hospital in Gyeonggi Province into three groups according to the degrees of metabolic syndrome risk factors. They include the normal group (n=58), the pre-metabolic syndrome group (n=112) and the metabolic syndrome group (n=32). They were compared in exercise capacity and cardiac structure and function and impacts of exercise capacity on the cardiac diastolic function. All the groups took echocardiography to have their cardiac structures and functions examined and an exercise stress test to have their exercise capacity measured. The research findings were as follows: There were differences in exercise capacity, cardiac structure, and diastolic heart function among three groups. Between exercise capacity and diastolic heart function was found to be related. It turned out exercise capacity affected the cardiac diastolic functions. In conclusion, there were significant differences in exercise capacity between the normal group and the metabolic syndrome group and in the cardiac structure and function among the normal, metabolic syndrome, and pre-metabolic syndrome group. In addition, METs (metabolic equivalents) and heart rate recovery of exercise capacity turned out to affect cardiac diastolic functions.

• Smart Structures and Systems
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• v.19 no.6
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• pp.679-694
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• 2017

The complexity, enlargement and irregularity of structures and multi-directional dynamic loads acting on the structures can lead to unexpected structural behavior, such as torsion. Continuous torsion of the structure causes unexpected changes in the structure's stress distribution, reduces the performance of the structural members, and shortens the structure's lifespan. Therefore, a method of monitoring the torsional behavior is required to ensure structural safety. Structural torsion typically occurs accompanied by displacement, but no model has yet been developed to measure this type of structural response. This research proposes a model for measuring dynamic torsional response of structure accompanied by displacement and for identifying the torsional modal parameter using vision-based displacement measurement equipment, a motion capture system (MCS). In the present model, dynamic torsional responses including pure rotation and translation displacements are measured and used to calculate the torsional angle and displacements. To apply the proposed model, vibration tests for a shear-type structure were performed. The torsional responses were obtained from measured dynamic displacements. The torsional angle and displacements obtained by the proposed model using MCS were compared with the torsional response measured using laser displacement sensors (LDSs), which have been widely used for displacement measurement. In addition, torsional modal parameters were obtained using the dynamic torsional angle and displacements obtained from the tests.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.667-675
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• 2012

A damage estimation method for support structure of offshore wind turbine using modal parameters is presented for effective structural health monitoring. Natural frequencies and mode shapes for a support structure with monopile of an offshore wind turbine were calculated considering soil condition and added mass. A neural network was learned based on training patterns generated by the changes of natural frequency and mode shape due to various damages. Natural frequencies and mode shapes for 10 prospective damage cases were input to the trained neural network for damage estimation. The identified damage locations and severities agreed reasonably well with the accurate damages. Multi-damage cases could also be successfully estimated. Enhancement of estimation result using another parameters as input to neural network will be carried out by further study. Proposed method could be applied to other type of support structure of offshore wind turbine for structural health monitoring.