• Asian Pacific Journal of Cancer Prevention
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• v.16 no.4
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• pp.1591-1597
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• 2015

Background: Korea has experienced rapid economic development in a very short period of time. A mixture of traditional and modern risk factors coexists and the rapid change in non-genetic factors interacts with genetic constituents. With consideration of these unique aspects of Korean society, a large-scale genomic cohort study-the Health Examinees (HEXA) Study-has been conducted to investigate epidemiologic characteristics, genomic features, and gene-environment interactions of major chronic diseases including cancer in the Korean population. Materials and Methods: Following a standardized study protocol, the subjects were prospectively recruited from 38 health examination centers and training hospitals throughout the country. An interview-based questionnaire survey was conducted to collect information on socio-demographic characteristics, medical history, medication usage, family history, lifestyle factors, diet, physical activity, and reproductive factors for women. Various biological specimens (i.e., plasma, serum, buffy coat, blood cells, genomic DNA, and urine) were collected for biorepository according to the standardized protocol. Skilled medical staff also performed physical examinations. Results: Between 2004 and 2013, a total of 167,169 subjects aged 40-69 years were recruited for the HEXA study. Participants are being followed up utilizing active and passive methods. The first wave of active follow-up began in 2012 and it will be continued until 2015. The principal purpose of passive follow-up is based on data linkages with the National Death Certificate, the National Cancer Registry, and the National Health Insurance Claim data. Conclusions: The HEXA study will render an opportunity to investigate biomarkers of early health index and the chronological changes associated with chronic diseases.

• The Korean Journal of Food And Nutrition
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• v.21 no.2
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• pp.121-126
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• 2008

In a previous study, a mulberry fruit extract(MFE) supplement exhibited anti-inflammatory activity and improved serum lipid profiles in arthritic rats. The objective of this study was to determine whether dietary MFE could ameliorate inflammatory parameters and serum lipid levels in humans. Twenty-six middle-aged subjects(mean body mass index=27 $kg/m^2$) consumed MFE(100 $m{\ell}/day)$ after lunch for 4 wks. Anthropometric measurements, serum oxidative stress markers and serum lipid profile analyses were performed at baseline and then at 4 wk following the study. There were no significant differences in anthropometric measurements, including BMI, WHR, and body fat composition. After the 4 wk-intervention, serum levels of C-reactive protein(CRP), ferric-reducing ability of plasma(FRAP), serum triglyceride(TG) and LDL-cholesterol had significantly decreased(p<0.05), whereas serum levels of HDL-cholesterol significantly(p<0.05) increased. These findings suggest the consumption of mulberry extract may be protective against inflammation and the atherosclerotic state in elderly obese men at high risk for cardiovascular disease(CVD).

• Earthquakes and Structures
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• v.13 no.5
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• pp.497-507
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• 2017

Flooding induced scour has been long recognized as a major hazard to river-crossing bridges. Many studies in recent years have attempted to evaluate the effects of scour on the seismic performance of bridges, and probabilistic frameworks are usually adopted. However, direct and straightforward insight about how foundation scour affects bridges as a type of soil-foundation-structure system is usually understated. In this paper, we provide a comprehensive review of applied methods centering around seismic assessment of scoured bridges considering soil-foundation-structure interaction. When introducing these applied analysis and modeling methods, a simple bridge model is provided to demonstrate the use of these methods as a case study. Particularly, we propose the use of nonlinear modal pushover analysis as a rapid technique to model scoured bridge systems, and numerical validation and application of this procedure are given using the simple bridge model. All methods reviewed in this paper can serve as baseline components for performing probabilistic vulnerability or risk assessment for any river-crossing bridge system subject to flood-induced scour and earthquakes.

• Journal of Korean Academy of Nursing
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• v.34 no.1
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• pp.182-190
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• 2004

Purpose: This study was conducted to understand the health status and health behaviors of preschoolers to provide baseline data for developing health promotion programs. Method: Parents of children attending day-care centers were recruited for the study. Participating day-care centers were selected using a stratified sampling method. Data was collected from June to August 2002 using a questionnaire. Result: Among 754 preschoolers, 17.3% were overweight, while 18.2% were underweight. The most frequent infectious diseases that children have had previously were hand-foot-mouth disease (20.2%) and chicken pox (18.7%). Current health conditions that children have frequently are respiratory disease (28%) and atopic dermatitis (23.8%). Only 61% brush their teeth everyday at bedtime, 54.3% wash their hands every time after returning home, 8.8% wear bicycle helmets, 9.3% use a child car seat, and 8.1% eat fruits and vegetables five times a day. Children residing in the metropolitan area were more likely to have positive health behaviors, and children of parents with an advanced college level education were more likely to have positive health behaviors than those with only a high school level education. Conclusion: Based on the study results, health professionals could plan and develop health promotion programs to change unhealthy behaviors of preschoolers targeting high-risk groups.

• Nuclear Engineering and Technology
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• v.48 no.1
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• pp.114-128
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• 2016

The development of operational performance indicators is of utmost importance for nuclear power plants, since they measure, track, and trend plant operation. Leading indicators are ideal for reducing the likelihood of consequential events. This paper describes the operational data analysis of the information contained in the Corrective Action Program. The methodology considers human error and organizational factors because of their large contribution to consequential events. The results include a tool developed from the data to be used for the identification, prediction, and reduction of the likelihood of significant consequential events. This tool is based on the resilience curve that was built from the plant's operational data. The stress is described by the number of unresolved condition reports. The strain is represented by the number of preventive maintenance tasks and other periodic work activities (i.e., baseline activities), as well as, closing open corrective actions assigned to different departments to resolve the condition reports (i.e., corrective action workload). Beyond the identified resilience threshold, the stress exceeds the station's ability to operate successfully and there is an increased likelihood that a consequential event will occur. A performance indicator is proposed to reduce the likelihood of consequential events at nuclear power plants.

• Journal of Obesity & Metabolic Syndrome
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• v.27 no.4
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• pp.213-222
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• 2018

Bariatric surgery has evolved from a surgical measure for treating morbid obesity to an epochal remedy for treating metabolic syndrome as a whole, which is represented by type 2 diabetes mellitus. Numerous clinical trials have advocated bariatric or metabolic surgery over nonsurgical interventions because of markedly superior metabolic outcomes in morbidly obese patients who satisfy traditional criteria for bariatric surgery (body mass index [BMI] >$35kg/m^2$) and in less obese or simply overweight patients. Nevertheless, not all diabetes patients achieve the most desirable outcomes; i.e., diabetes remission after metabolic surgery. Thus, candidates for metabolic surgery should be carefully selected based on comprehensive preoperative assessments of the risk-benefit ratio. Predictors for diabetes remission after metabolic surgery may be classified into two groups based on mechanism of action. The first is indices for preserved pancreatic beta-cell function, including younger age, shorter duration of diabetes, and higher C-peptide level. The second is the potential for an insulin resistance reduction, including higher baseline BMI and visceral fat area. Several prediction models for diabetes remission have been suggested by merging these two to guide the joint decision-making process between clinicians and patients. Three such models, DiaRem, ABCD, and individualized metabolic surgery scores, provide an intuitive scoring system and have been validated in an independent external cohort and can be utilized in routine clinical practice. These prediction models need further validation in various ethnicities to ensure universal applicability.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.171-177
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• 2021

In terms of distribution planning, accurate electric load prediction is one of the most important factors. The future load prediction has manually been performed by calculating the maximum electric load considering loads transfer/switching and multiplying it with the load increase rate. In here, the risk of human error is inherent and thus an automated maximum electric load forecasting system is required. Although there are many existing methods and techniques to predict future electric loads, such as regression analysis, many of them have limitations in reflecting the nonlinear characteristics of the electric load and the complexity due to Photovoltaics (PVs), Electric Vehicles (EVs), and etc. This study, therefore, proposes a method of predicting future electric loads on distribution lines by using Machine Learning (ML) method that can reflect the characteristics of these nonlinearities. In addition, predictive models were developed based on actual data collected at KEPCO's existing distribution lines and the adequacy of developed models was verified as well. Also, as the distribution planning has a direct bearing on the investment, and amount of investment has a direct bearing on the maximum electric load, various baseline such as maximum, lowest, median value that can assesses the adequacy and accuracy of proposed ML based electric load prediction methods were suggested.

• Clinical and Experimental Reproductive Medicine
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• v.49 no.2
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• pp.127-134
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• 2022

Objective: This study aimed to investigate the impact of hyperandrogenism (HA) on the outcomes of ovulation induction (OI) using gonadotropin and intrauterine insemination (IUI) in patients with polycystic ovary syndrome (PCOS). Methods: This was a retrospective cohort study including 415 patients undergoing OI using gonadotropin and IUI treatment between January 2018 and December 2020 at a single infertility center. Baseline characteristics, clinical and laboratory parameters, and pregnancy outcomes were investigated. Results: Among the study population, there were 105 hyperandrogenic (25.3%) and 310 non-hyperandrogenic patients (74.7%). The live birth rate was lower in the HA group than in the non-HA group, but this difference did not reach statistical significance due to the limited sample size (14.3% vs. 21.0%, relative risk=0.68; 95% CI, 0.41-1.14, p=0.153). No predictive factors for live birth were identified through logistic regression analysis. Conclusion: HA did not negatively affect the outcomes of OI using gonadotropin and IUI cycles in Vietnamese women with PCOS. The result may not be applicable elsewhere due to the large variation in the characteristics of women with PCOS across races and populations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3230-3255
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• 2022

Causality mining in NLP is a significant area of interest, which benefits in many daily life applications, including decision making, business risk management, question answering, future event prediction, scenario generation, and information retrieval. Mining those causalities was a challenging and open problem for the prior non-statistical and statistical techniques using web sources that required hand-crafted linguistics patterns for feature engineering, which were subject to domain knowledge and required much human effort. Those studies overlooked implicit, ambiguous, and heterogeneous causality and focused on explicit causality mining. In contrast to statistical and non-statistical approaches, we present Bidirectional Encoder Representations from Transformers (BERT) integrated with Multi-level Feature Networks (MFN) for causality recognition, called BERT+MFN for causality recognition in noisy and informal web datasets without human-designed features. In our model, MFN consists of a three-column knowledge-oriented network (TC-KN), bi-LSTM, and Relation Network (RN) that mine causality information at the segment level. BERT captures semantic features at the word level. We perform experiments on Alternative Lexicalization (AltLexes) datasets. The experimental outcomes show that our model outperforms baseline causality and text mining techniques.

• Journal of Dental Anesthesia and Pain Medicine
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• v.22 no.3
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• pp.175-186
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• 2022

This study aimed to systematically review the effectiveness of methylene blue (MB) photosensitizers in the management of symptomatic oral lichen planus (OLP). Electronic online databases and manual searches were performed for randomized controlled trials (RCTs) published in English between January 2010 and February 2022. RCTs comparing photodynamic therapy (PDT) and corticosteroid therapy at baseline and follow-up period were identified. The Cochrane risk of bias tool was used to assess the quality of the included studies. A meta-analysis was performed regarding visual analog scale (VAS) scores, Thongprasom sign scores, lesion size, response to treatment, and exacerbation of lesions after therapy. The clinical severity was analyzed qualitatively. Five RCTs consisting of 180 samples fulfilled the inclusion and exclusion criteria. All parameters of VAS score, Thongprasom sign score, lesion size, and response to treatment were statistically non-significant. Our results indicate that both MB-PDT and corticosteroid therapy are effective for the management of OLP. Moreover, MB-PDT is an effective alternative treatment option for OLP when corticosteroids are contraindicated. However, conclusive evidence cannot be ascertained owing to the heterogeneity among the studies.