• Fashion & Textile Research Journal
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• v.23 no.2
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• pp.200-211
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• 2021

This study examines the effects of fashion influencers' body types (realistic versus ideal body types) on self-expression, self-representation, and recommendation intentions, as mediated by familiarity toward influencers. Although fashion influencers lead to a positive consumer response compared to traditional advertisements, previous research on the effects of fashion influencers on consumers is limited. Thus, this study tests the role of consumers' socio-psychological aspects in understanding how and why fashion influencers affect consumers' behavioral intentions associated with self-expression, self-representation, and influencer recommendation. A total of 180 women in their 20s and 30s participated in the survey. The responses were collected after showing them stimuli featuring fashion influencers with either ideal or realistic body shapes. The data were analyzed using SPSS18.0 for descriptive statistics, and AMOS 18.0 for confirmatory factor analysis and structural equation modeling. The results showed that participants who were shown realistic body types perceived familiarity, which generated positive effects on self-expression, self-representation, and recommendation intentions. Hence, the effects of influencers' body types on recommendation intention are mediated by familiarity. Self-expression and self-representation intentions also increase influencer recommendation intention. Comparatively, participants who were shown ideal body types only induced higher self-representation intention, which increased their recommendation intention. The current findings can help fashion marketers select the appropriate influencers who fit their target customers as promotional models, as well as to induce changes in consumers' behavioral intention.

• Physical Therapy Korea
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• v.28 no.2
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• pp.123-131
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• 2021

Background: Only 2% of falls in older adults result in serious injuries (i.e., hip fracture). Therefore, it is important to differentiate injurious versus non-injurious falls, which is critical to develop effective interventions for injury prevention. Objects: The purpose of this study was to a. extract the best features of surface electromyography (sEMG) for classification of injurious falls, and b. find a best model provided by data mining techniques using the extracted features. Methods: Twenty young adults self-initiated falls and landed sideways. Falling trials were consisted of three initial fall directions (forward, sideways, or backward) and three knee positions at the time of hip impact (the impacting-side knee contacted the other knee ("knee together") or the mat ("knee on mat"), or neither the other knee nor the mat was contacted by the impacting-side knee ("free knee"). Falls involved "backward initial fall direction" or "free knee" were defined as "injurious falls" as suggested from previous studies. Nine features were extracted from sEMG signals of four hip muscles during a fall, including integral of absolute value (IAV), Wilson amplitude (WAMP), zero crossing (ZC), number of turns (NT), mean of amplitude (MA), root mean square (RMS), average amplitude change (AAC), difference absolute standard deviation value (DASDV). The decision tree and support vector machine (SVM) were used to classify the injurious falls. Results: For the initial fall direction, accuracy of the best model (SVM with a DASDV) was 48%. For the knee position, accuracy of the best model (SVM with an AAC) was 49%. Furthermore, there was no model that has sensitivity and specificity of 80% or greater. Conclusion: Our results suggest that the classification model built upon the sEMG features of the four hip muscles are not effective to classify injurious falls. Future studies should consider other data mining techniques with different muscles.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.103-110
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• 2021

In the development of a Risk Monitor probabilistic safety assessment (PSA) model from the basic PSA model of a nuclear power plant, the modeling of common-cause failure (CCF) is very important. At present, some approximate modeling methods are widely used, but there lacks criterion of modeling accuracy and error analysis. In this paper, aiming at ensuring the accuracy of risk assessment and minimizing the Risk Monitor PSA models size, we present three basic issues of CCF model resulted from the changes of a nuclear power plant configuration, put forward corresponding modeling methods, and derive accuracy criteria of CCF modeling based on minimum cut sets and risk indicators according to the requirements of risk monitoring. Finally, a nuclear power plant Risk Monitor PSA model is taken as an example to demonstrate the effectiveness of the proposed modeling method and accuracy criteria, and the application scope of the idea of this paper is also discussed.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2682-2695
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• 2021

This paper aims to evaluate the structural dynamic responses and damage/failure of the nuclear fuel reprocessing plant under the free drop impact of spent fuel cask (SFC) and fuel assembly (FA) during the on-site transportation. At the present Part I of this paper, the large-scale SFC model free drop test and the corresponding numerical simulations are performed. Firstly, a composite target which is composed of the protective structure, i.e., a thin RC plate (representing the inverted U-shaped slab in the loading shaft) and/or an autoclaved aerated concrete (AAC) blocks sacrificial layer, as well as a thick RC plate (representing the bottom slab in the loading shaft) is designed and fabricated. Then, based on the large dropping tower, the free drop test of large-scale SFC model with the mass of 3 t is carried out from the height of 7 m-11 m. It indicates that the bottom slab in the loading shaft could not resist the free drop impact of SFC. The composite protective structure can effectively reduce the damage and vibrations of the bottom slab, and the inverted U-shaped slab could relieve the damage of the AAC blocks layer dramatically. Furthermore, based on the finite element (FE) program LS-DYNA, the corresponding refined numerical simulations are performed. By comparing the experimental and numerical damage and vibration accelerations of the composite structures, the present adopted numerical algorithms, constitutive models and parameters are validated, which will be applied in the further assessment of drop impact effects of full-scale SFC and FA on prototype nuclear fuel reprocessing plant in the next Part II of this paper.

• Journal of Korea Trade
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• v.24 no.6
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• pp.173-193
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• 2020

Purpose - This study aims to examine the effect of entrepreneurship of start-ups on export performance when the business closure rate is higher than business start-up rate in Korea. Thus, this study analyzes various factors for start-ups established within the past seven years and uses export performance as an indicator. Prior to analysis of factors, the study defines the concepts of start-up factors based on various studies. Design/methodology - In order to analyze the export performance of startups, this study conducted an empirical analysis using statistical analysis. Theories were established based on previous studies, and hypotheses and research models were designed based on the established theories. Subsequently, in order to verify the research hypothesis and research model, factor analysis such as validity and reliability, and structural equation modeling were analyzed. Findings - As a result of analysis based on previous studies, we found that there is a difference between theoretical and practical aspects. Whereas previous studies showed that market orientation, technology orientation, and social capital have a direct impact on export performance, the present study analyzed that there is no such impact, and that technology capabilities were important as a result of the unique traits of start-ups. Originality/value - Existing studies have limitations in understanding the overall characteristics of a company by using market orientation, technology orientation, and social capital as individual independent variables. In addition, the existing researches have been analyzed in relation to corporate performance, whereas this study has been limited to export performance, so it can be regarded as different from other studies.

• Journal of Korea Trade
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• v.25 no.1
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• pp.65-88
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• 2021

Purpose - This paper aims to examine the determinants of SWFs' investment in Asian countries and to identify consistent investment patterns of SWFs in specific target firms from Asia, particularly China and South Korea. Design/methodology - This study extends the Tobin's Q model to examine the relationship between SWF investments in target firms and their returns with other firm-level control variables. We collect consistent data on SWF investments and the matched firm-level data on target firms, which of observation is 1,512 firms (333 in South Korea and 1,179 in China) targeted by 20 SWF sources during 1997-2017. The panel random effect model is used to estimate the extended Tobin's Q model. The robustness of the estimations is tested by the simultaneous equation models and the panel GEE model. Findings - The evidence shows that sovereign wealth funds are more inclined to invest in the financial sector with a monopoly position and in large firms with higher growth opportunity and superior cash asset ratios in China. In contrast to their investments in China, sovereign wealth funds in South Korea prefer to invest in strategic sectors, such as energy and information technology, and in large firms with high performance and low leverage. Sovereign wealth funds' investments tend to significantly improve the target firm's performance measured by sales growth and returns in both Korea and China. Originality/value - The existing literature focuses on examining the determination of SWFs investment in the developed countries, such as Europe and the United States. Our paper contributes to the literature in three ways; first, we analyzes case studies of SWF investments in Asian markets, which are less developed and riskier. Second, we examine whether the determination of SWF investment in Asian target firms depends on the different time periods, on types of sources of SWFs, and on acquiring countries. Third, our research uses vast sample data on target firms in longer time periods (1997-2017) than other previous studies on the SWFs for Asian markets.

• Journal of Korea Trade
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• v.24 no.3
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• pp.20-36
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• 2020

Purpose - As the global product network expands through both internationalization and diversification of the multimodal transportation system, corporate strategies have shifted to emphasize the importance of a high value-added international logistics system. To guide policies and strategies to attract relevant industries, this study aims to analyze the location competitiveness of regional logistics distribution center to serve Northeast Asia. Design/methodology - Multi-criteria techniques are considered to offer a promising framework for evaluating decision-making factors. This paper employed an analytic hierarchy process to analyze the hierarchal structure of determinants for selecting the location of a regional logistics distribution center. Adopting both qualitative and quantitative evaluations, this study suggest political implications for a regional logistics distribution center development, such as the direction of political support, service differentiation and infrastructure development. Findings - This study developed a location competitiveness evaluation model, based on the case study of the major port-cities in Northeast Asia. Evaluation model incorporates five factors underpinning 17 components extracted using factor analysis. The results revealed that the logistics factor is the most significant factor for evaluating the competitiveness of a regional logistics distribution center. The remaining factors were market, costs, and services environment. Comparing qualitative and quantitative evaluations, results provide useful insights for a regional logistics distribution center development in Northeast Asia. Originality/value - This study revealed differences between qualitative and quantitative evaluations. The finding implies that prior works on evaluation models of competitiveness has not successfully measured the gap between quantitative data and expert' evaluations. To overcome this limitation, this paper considered both actual data such as actual distance, cost, the number of companies located, and expert opinions.

• The Korean Journal of Physiology and Pharmacology
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• v.25 no.4
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• pp.375-383
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• 2021

The intestinal barrier function disrupted in sepsis, while little is known about the variation in different phases of sepsis. In this study, mouse models of sepsis were established by caecal ligation and puncture (CLP). The H&E staining of sections and serum diamine oxidase concentration were evaluated at different timepoint after CLP. TUNEL assay and EdU staining were performed to evaluate the apoptosis and proliferation of intestinal epithelium. Relative protein expression was assessed by Western blotting and serum concentrations of pro-inflammatory cytokines was measured by ELISA. The disruption of intestinal barrier worsened in the first 24 h after the onset of sepsis and gradually recovered over the next 24 h. The percentage of apoptotic cell increased in the first 24 h and dropped at 48 h, accompanied with the proliferative rate of intestinal epithelium inhibited in the first 6 h and regained in the later period. Furthermore, the activity of nuclear factor kappa B (NF-κB) presented similar trend with the intestinal barrier function, shared positive correction with apoptosis of intestinal epithelium. These findings reveal the conversion process of intestinal barrier function in sepsis and this process is closely correlated with the activity of NF-κB signaling.

• The Korean Journal of Physiology and Pharmacology
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• v.25 no.4
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• pp.333-339
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• 2021

Injection lipolysis or mesotherapy gained popularity for local fat dissolve as an alternative to surgical liposuction. Phosphatidylcholine (PPC) and aminophyl-line (AMPL) are commonly used compounds for mesotherapy, but their efficacy and safety as lipolytic agents have been controversial. Glycerophosphocholine (GPC) is a choline precursor structurally similar to PPC, and thus introduced in aesthetics as an alternative for PPC. This study aimed to evaluate the effects of GPC on adipocytes differentiation and lipolysis and compared those effects with PPC and AMPL using in vitro and in vivo models. Adipogenesis in 3T3-L1 was measured by Oil Red O staining. Lipolysis was assessed by measuring the amount of glycerol released in the culture media. To evaluate the lipolytic activity of GPC on a physiological condition, GPC was subcutaneously injected to one side of inguinal fat pads for 3 days. Lipolytic activity of GPC was assessed by hematoxylin and eosin staining in adipose tissue. GPC significantly suppressed adipocyte differentiation of 3T3-L1 in a concentration-dependent manner (22.3% inhibition at 4 mM of GPC compared to control). Moreover, when lipolysis was assessed by glycerol release in 3T3-L1 adipocytes, 6 mM of GPC stimulated glycerol release by two-fold over control. Subcutaneous injection of GPC into the inguinal fat pad of mice significantly reduced the mass of fat pad and the size of adipocytes of injected site, and these effects of GPC were more prominent over PPC and AMPL. Taken together, these results suggest that GPC is the potential therapeutic agent as a local fat reducer.

• Genomics & Informatics
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• v.19 no.1
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• pp.10.1-10.7
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• 2021

Although many models have been proposed to accurately predict the response of drugs in cell lines recent years, understanding the genome related to drug response is also the key for completing oncology precision medicine. In this paper, based on the cancer cell line gene expression and the drug response data, we established a reliable and accurate drug response prediction model and found predictor genes for some drugs of interest. To this end, we first performed pre-selection of genes based on the Pearson correlation coefficient and then used ElasticNet regression model for drug response prediction and fine gene selection. To find more reliable set of predictor genes, we performed regression twice for each drug, one with IC₅₀ and the other with area under the curve (AUC) (or activity area). For the 12 drugs we tested, the predictive performance in terms of Pearson correlation coefficient exceeded 0.6 and the highest one was 17-AAG for which Pearson correlation coefficient was 0.811 for IC₅₀ and 0.81 for AUC. We identify common predictor genes for IC₅₀ and AUC, with which the performance was similar to those with genes separately found for IC₅₀ and AUC, but with much smaller number of predictor genes. By using only common predictor genes, the highest performance was AZD6244 (0.8016 for IC₅₀, 0.7945 for AUC) with 321 predictor genes.