• Journal of Nutrition and Health
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• v.56 no.6
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• pp.629-640
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• 2023

Purpose: Non-alcoholic fatty liver disease (NAFLD) is characterized by the accumulation of fat in the liver which is not a result of excessive alcohol consumption. Its global prevalence was estimated to be approximately 32% in the years 1994-2019. More than half of obese individuals and patients with diabetes are reported to have NAFLD as a comorbidity. This study aimed to investigate the impact of the autumn olive (Elaeagnus umbellata Thunb.) berry on insulin resistance and steatosis in rats fed a high-fructose diet. Methods: Six-week-old Wistar rats were divided into four groups. The control group received a diet consisting of 65% corn starch, while the fructose and experimental groups were fed a diet comprising 65% fructose (FRU) and an FRU diet containing 0.5% (low-dose autumn olive berry group; LAO) or 1.0% (high-dose autumn olive berry group; HAO) ethanol extract of autumn olive berry, respectively, for 10 weeks. Results: The HAO group exhibited significantly lower blood glucose levels compared to the fructose-fed group. Both the LAO and HAO groups showed a substantial reduction in serum insulin levels and insulin resistance when compared to the fructose-fed group. The consumption of LAO and HAO significantly ameliorated dyslipidemia and reduced the levels of triglycerides in the liver compared to the fructose-fed group. Additionally, the consumption of HAO resulted in lower serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities compared to the fructose group. The hepatic expression of the sterol regulatory element-binding protein-1c (SREBP-1c) and carbohydrate-responsive element-binding protein (ChREBP) was significantly reduced in the LAO and HAO groups compared to the fructose group. Conclusion: Autumn olive berries improved steatosis by ameliorating insulin resistance and down-regulating the lipogenesis proteins in rats fed on high fructose diet.

• Journal of Korean Elementary Science Education
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• v.42 no.4
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• pp.560-576
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• 2023

The purpose of this investigation is to: (1) to derive an improvement factor for inquiry-based simulated teaching-learning in pre-service teacher training programs, and pre-service teachers practice simulated teaching that reflect the improvement factor, (2) to analyze the difference in science intrinsic motivation according to science self-efficacy and inquiry-based simulated teaching-learning experience. To achieve these goals, we recruited five elementary and secondary teachers as experts to help us develop an improvement factor based on expert interviews. Subsequently, third-year pre-service teachers of a university of education participated in our analysis of differences in science intrinsic motivation, according to their level of science self-efficacy and experience with inquiry-based simulated teaching-learning. Our methodology involved applying the analytic hierarchy process to expert interviews to derive improvement factor for inquiry-based simulated teaching-learning, followed by a two-way ANOVA to identify significant differences in science intrinsic motivation between groups with varying levels of science self-efficacy. We also conducted post-analysis through MANOVA statements. The results of our study indicate that inquiry-based simulated teaching-learning can be improved through activities that foster digital literacy, ecological literacy, democratic citizenship, and scientific inquiry skills. Moreover, small group activities and student-centered teaching-learning approaches were found to be effective in developing core competencies and promoting science achievements. Specifically, pre-service teachers prepared a teaching-learning course plan and inquiry-based simulated teaching-learning in seventh-grade in the Earth and Space subject area. Pre-service teachers' science intrinsic motivation analyze significant differences in all levels of science self-efficacy before and after simulated teaching-learning and significant difference in the interaction effect between simulated teaching-learning and scientific self-efficacy. Particularly, group with low scientific self-efficacy, the difference in science intrinsic motivation according to simulated teaching-learning was most significant. Teachers' scientific self-efficacy and intrinsic motivation are needed to improve science achievement and affective domains of students in class. Therefore, this study contributes to suggest inquiry-based simulated teaching-learning reflecting school practices from the pre-service teacher curriculum.

• Information Systems Review
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• v.25 no.4
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• pp.131-159
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• 2023

Recently, amidst the backdrop of the COVID-19 pandemic shifting towards an endemic phase, there has been a rise in discussions and debates about the future of the metaverse. Simultaneously, major metaverse platforms like Roblox have been launching services integrated with generative AI, and Apple's mixed reality hardware, Vision Pro, has been announced, creating new expectations for the metaverse. In this situation where the outlook for the metaverse is divided, it is crucial to diagnose the metaverse from an ecosystem perspective, examine its key ecological features, driving forces for development, and future possibilities for advancement. This study utilized Wang's (2021) Information Ecology Theory (IET) framework, which is representative of ecosystem research in the field of Information Systems (IS), to derive the Metaverse Industrial Ecosystem (MIE). The analysis revealed that the MIE consists of four main domains: Tech Landscape, Category Ecosystem, Metaverse Platform, and Product/Service Ecosystem. It was found that the MIE exhibits characteristics such as digital connectivity, the integration of real and virtual worlds, value creation capabilities, and value sharing (Web 3.0). Furthermore, the interactions among the domains within the MIE and the four characteristics of the ecosystem were identified as driving forces for the development of the MIE at an ecosystem level. Additionally, the development of the MIE at an ecosystem level was categorized into three distinct stages: Narrow Ecosystem, Expanded Ecosystem, and Everywhere Ecosystem. It is anticipated that future advancements in related technologies and industries, such as robotics, AI, and 6G, will promote the transition from the current Expanded Ecosystem level of the MIE to an Everywhere Ecosystem level, where the connection between the real and virtual worlds is pervasive. This study provides several implications. Firstly, it offers a foundational theory and analytical framework for ecosystem research, addressing a gap in previous metaverse studies. It also presents various research topics within the metaverse domain. Additionally, it establishes an academic foundation that integrates concept definition research and impact studies, which are key areas in metaverse research. Lastly, referring to the developmental stages and conditions proposed in this study, businesses and governments can explore future metaverse markets and related technologies. They can also consider diverse metaverse business strategies. These implications are expected to guide the exploration of the emerging metaverse market and facilitate the evaluation of various metaverse business strategies.

• Journal of Venture Innovation
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• v.6 no.1
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• pp.75-93
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• 2023

As non-face-to-face contact was activated due to the progress of the 4th Industrial Revolution and COVID-19, the government's civil service was also rapidly reflecting this phenomenon. However, there were cases in which it was quite burdensome and rather uncomfortable for the elderly who were relatively alienated from the digital culture. Therefore, in this study, we tried to empirically analyze the factors that affect the use of government 24(a government civil integration service) by the elderly. For this purpose, the characteristics of the elderly and the characteristics of services were paid attention. As the characteristic factors of the elderly, cognitive characteristics, psychological characteristics, and physical characteristics were derived, and as service characteristics, usefulness, ease of use, security, and government support were derived when using government 24. The effect of these factors on the intention to use Government 24 was empirically analyzed. For empirical analysis, a survey was conducted targeting the elderly in their 60s and older, and 250 valid sample were used for analysis. The analysis results were as follows. Among the characteristics of the elderly, cognitive characteristics, psychological characteristics, and physical characteristics were all found to had a significant negative (-) effect on the intention to use Government 24. On the other hand, usefulness, ease of use, and government support were found to had a significant positive (+) effect on the intention to use government 24. On the other hand, security was not tested for a significant relationship with government 24 use intention. Among the variables that have a significant impact, the psychological characteristics of the elderly had the greatest impact on the intention to use Government 24. Usefulness, cognitive characteristics, physical characteristics, ease of use, and government support were in order. The fact that this study conducted an empirical analysis by combining the characteristics of the elderly and the characteristics of services was meaningful at the academic level. In addition, considering that psychological characteristics appeared to be the most important factor, it seemed necessary to consider these points to promote the use of Government 24 by the elderly.

• The Journal of Korean Academy of Sensory Integration
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• v.21 no.2
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• pp.69-83
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• 2023

Objective : This study sought to systematically examine the intervention effect of social stories when applied in relation to children with sleep disorders. Methods : Studies available in the SCOPUS, ScienceDirect, PsycArticles, and PubMed databases that were published from 2001 to 2022 were searched. The keywords used for the search were as follows: ("social story" OR "social stories") AND ("sleep" OR "sleep disorders" OR "sleep wake disorder bedtimes" OR "sleep initiation and maintenance disorders" OR "sleep wake disorder" OR "sleep arousal disorders"). Based on the selection criteria, six experimental studies were selected and analyzed. Results : The selected studies were two randomized controlled trials, three individual trials, and one case study. The subjects were mostly children diagnosed with autism spectrum disorder who were school-aged or adolescent. The intervention types were often complex interventions, including social stories and other interventions, while the durations of the interventions varied from one day to more than 40 days. The interventions had a positive effect on the subjects' sleep quality, with night wakings, sleep onset delay, and sleep anxiety all being improved. As standardized assessment tools to evaluate the effectiveness of social stories, the Child Sleep Habits Questionnaire and the Child Behavior Checklist were used in two papers each, and were the most commonly used. As non-standardized assessment tools, each of the four papers used turbulence and sleep diaries as assessment tools. Conclusion : The effect of social story mediation can be divided into sleep quality and sleep-related behavior. In terms of sleep quality, studies showing improvements in night wakings, sleep onset delay, and sleep anxiety accounted for a large proportion of the sample. The detailed effect area of sleep quality showed a significant improvement after the interventions in most studies, and in all six studies analyzed in the present study, the continuation of the effect after the intervention was confirmed via follow-up tests. Thus, the findings of this study are expected to be helpful when applying social stories in children with sleep disorders in clinical practice due to presenting the intervention effects, outcome evaluation tools, and intervention periods in children with sleep disorders in prior investigations involving social stories.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.157-172
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• 2023

The recent Fourth Industrial Revolution is accelerating changes due to digital transformation. According to this trend, the existing start-up paradigm is changing, and new business models based on new technologies and creative ideas are emerging. In addition, the diversity of mentoring relationships and environments such as online mentoring, reverse mentoring, group mentoring, and multiple mentoring is also increasing. However, most mentors in their 50s and 60s, who are mainly active in the start-up field, have been able to help mentees a lot based on their own experience and expertise, but they are having difficulty responding to the changing environment due to a lack of understanding and experience of new technologies and environments. To cope with these changes well, mentors must constantly study, acquire and apply the latest technologies to improve their understanding of new technologies and the environment. In addition, it is necessary to have an understanding and respect for the diversity of mentoring relationships and environments, and to maximize the effectiveness of mentoring by actively utilizing them. Therefore, mentors should recognize that they directly affect the growth and development of mentees, constantly acquire new knowledge and skills to maintain and develop expertise, and actively deliver their knowledge and experiences to mentees. Therefore, in this study, was tried to empirically analyze the relationship between mentoring's influence on mentor's job satisfaction through mentor's personal learning and self-efficacy. The results of the empirical analysis were as follows. Among the functions of mentoring, career function and role modeling were found to have a positive effect on both personal learning and self-efficacy, which are parameters, and job satisfaction, which is a dependent variable. On the other hand, psychological and social functions have a positive effect on personal learning, but they do not have an effect on self-efficacy and job satisfaction. In addition, as a result of analyzing the mediating effect, all mediating effects were confirmed for career functions, and only the mediating effect of self-efficacy was confirmed for role modeling. Through this study, mentoring is an important factor in promoting job satisfaction, personal learning and self-efficacy, and this study can be said to be academically and practically meaningful in that it confirmed personal learning and self-efficacy as factors that increase mentor's job satisfaction, and the focus of mentoring research was shifted from mentee to mentor to study the impact of mentoring on mentors.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.157-175
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• 2022

At this moment, a paradigm shift is taking place across all sectors of society for the transition movements to the digital economy. Various movements are taking place in the global agricultural industry to achieve innovative growth using big data which is a key resource of the 4th industrial revolution. Although the government is making various attempts to promote the use of big data, the movement of the agricultural industry as a key player in the use of big data, is still insufficient. Therefore, in this study, effects of performance expectations, effort expectations, social impact, facilitation conditions, based on the Unified Theory of Acceptance and Use of Technology(UTAUT), and innovation tendencies on the acceptance intention of big data were analyzed using the economic and practical benefits that can be obtained from the use of big data for agricultural-related companies as moderating variables. 333 questionnaires collected from agricultural-related companies were used for empirical analysis. The analysis results using SPSS v22.0 and Process macro v3.4 were found to have a significant positive (+) effect on the intention to accept big data by effort expectations, social impact, facilitation conditions, and innovation tendencies. However, it was found that the effect of performance expectations on acceptance intention was insignificant, with social impact having the greatest influence on acceptance intention and innovation tendency the least. Moderating effects of economic benefit and practical benefit between effort expectation and acceptance intention, moderating effect of practical benefit between social impact and acceptance intention, and moderating effect of economic benefit and practical benefit between facilitation condition and acceptance intention were found to be significant. On the other hand, it was found that economic benefits and practical benefits did not moderate the magnitude of the influence of performance expectations and innovation tendency on acceptance intention. These results suggest the following implications. First, in order to promote the use of big data by companies, the government needs to establish a policy to support the use of big data tailored to companies. Significant results can only be achieved when corporate members form a correct understanding and consensus on the use of big data. Second, it is necessary to establish and implement a platform specialized for agricultural data which can support standardized linkage between diverse agricultural big data, and support for a unified path for data access. Building such a platform will be able to advance the industry by forming an independent cooperative relationship between companies. Finally, the limitations of this study and follow-up tasks are presented.

• Health Policy and Management
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• v.34 no.2
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• pp.196-210
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• 2024

Background: In January 2018, revised elderly fixed outpatient copayment for the elderly were implemented. When people ages 65 years and older receive outpatient treatment at clinic-level medical institutions (clinic, dental clinic, Korean medicine clinic), with medical expenses exceeding 15,000 won but not exceeding 25,000 won, their copayment rates have decreased differentially from 30%. This study aimed to examine the changes of health utilization of elderly after revised elderly fixed outpatient copayment. Methods: We used Korea health panel data from 2016 to 2018. The time period is divided into before and after the revised elderly fixed outpatient copayment. We conducted Poisson segmented regression to estimate the changes in outpatient utilization and inpatient utilization and conducted segmented regression to estimate the changes in medical expenses. Results: Immediately after the revised policy, the number of clinic and Korean medicine outpatient visits of medical expenses under 15,000 won decreased. But the number of clinic outpatient visits in the range of 15,000 to 20,000 won and Korean medicine clinic in the range of 20,000 to 25,000 won increased. Copayment in outpatient temporarily decreased. The inpatient admission rates and total medical expenses temporarily decreased but increased again. Conclusion: We confirmed the temporary increase in outpatient utilization in the medical expense segment with reduced copayment rates. And a temporary decrease in medical expenses followed by an increase again. To reduce the burden of medical expense among elderly in the long run, efforts to establish chronic disease management policies aimed at preventing disease occurrence and deterioration in advance need to continue.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.215-235
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• 2024

As artificial intelligence (AI) technology is recognized as a key technology that will determine future national competitiveness, competition for AI technology and industry promotion policies in major countries is intensifying. This study aims to present implications for domestic policy making by analyzing the policies of major countries on the start-up of AI companies, which are the basis of the AI industry ecosystem. The top four countries and the EU for the number of new investment attraction companies in the 2023 AI Index announced by the HAI Research Institute at Stanford University in the United States were selected, The United States enacted the National AI Initiative Act (NAIIA) in 2021. Through this law, The US Government is promoting continued leadership in the United States in AI R&D, developing reliable AI systems in the public and private sectors, building an AI system ecosystem across society, and strengthening DB management and access to AI policies conducted by all federal agencies. In the 14th Five-Year (2021-2025) Plan and 2035 Long-term Goals held in 2021, China has specified AI as the first of the seven strategic high-tech technologies, and is developing policies aimed at becoming the No. 1 AI global powerhouse by 2030. The UK is investing in innovative R&D companies through the 'Future Fund Breakthrough' in 2021, and is expanding related investments by preparing national strategies to leap forward as AI leaders, such as the implementation plan of the national AI strategy in 2022. Israel is supporting technology investment in start-up companies centered on the Innovation Agency, and the Innovation Agency is leading mid- to long-term investments of 2 to 15 years and regulatory reforms for new technologies. The EU is strengthening its digital innovation hub network and creating the InvestEU (European Strategic Investment Fund) and AI investment fund to support the use of AI by SMEs. This study aims to contribute to analyzing the policies of major foreign countries in making AI company start-up policies and providing a basis for Korea's strategy search. The limitations of the study are the limitations of the countries to be analyzed and the failure to attempt comparative analysis of the policy environments of the countries under the same conditions.

• The Journal of Korean Academy of Prosthodontics
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• v.62 no.2
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• pp.95-103
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• 2024

Purpose. With the advancement of digital technology, 3D printing is being utilized in the fabrication of denture base. Nevertheless, increasing microbial adhesion to the surface of denture base has been reported as the disadvantage of 3D-printed denture base. The purpose of this study is to investigate the antifungal properties and flexural strength of 3D-printed denture base resin according to the different contents of titanium dioxide nanoparticles. Materials and methods. Titanium dioxide nanoparticles were mixed with the 3D printing resin at the ratios of 0.5, 1, 1.5, and 2 wt%. Twenty specimens per each group were printed in the form of cylindrical shape (diameter: 20 mm, height: 3 mm) to evaluate antifungal properties. Ten specimens from each group underwent polishing using autogrinder, while the remaining ten specimens did not. Candida albicans in hyphae form was inoculated onto each specimen, optical density and colony-forming unit were analyzed. The surface of the specimen was observed using scanning electron microscopy. To evaluate the flexural strength, twenty specimens per each group were 3D printed in the form of rectangular prism shape (length: 64 mm, height: 10 mm, width: 3 mm) and three-point bending tests were conducted using universal testing machine according to ISO 20795-1. Results. Colony-forming unit of C.albicans and optical density of culture medium showed no difference between non-polished groups, but decreased in the polished groups at concentration of 1, 1.5, 2 wt% titanium dioxide nanoparticles. Flexural strength increased with titanium dioxide nanoparticle at concentration of 0.5, 1, 1.5 wt%, but decreased at 2 wt% compared to 1.5 wt%. Conclusion. When 1.5 wt% of titanium dioxide nanoparticles were added to the 3D-printed denture base resin with polishing, antifungal properties were increased.