• Journal of Microbiology and Biotechnology
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• v.33 no.10
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• pp.1351-1360
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• 2023

Endocrine-disrupting chemicals (EDCs) are compounds that disturb hormonal homeostasis by binding to receptors. EDCs are metabolized through hepatic enzymes, causing altered transcriptional activities of hormone receptors, and thus necessitating the exploration of the potential endocrine-disrupting activities of EDC-derived metabolites. Accordingly, we have developed an integrative workflow for evaluating the post-metabolic activity of potential hazardous compounds. The system facilitates the identification of metabolites that exert hormonal disruption through the integrative application of an MS/MS similarity network and predictive biotransformation based on known hepatic enzymatic reactions. As proof-of-concept, the transcriptional activities of 13 chemicals were evaluated by applying the in vitro metabolic module (S9 fraction). Identified among the tested chemicals were three thyroid hormone receptor (THR) agonistic compounds that showed increased transcriptional activities after phase I+II reactions (T3, 309.1 ± 17.3%; DITPA, 30.7 ± 1.8%; GC-1, 160.6 ± 8.6% to the corresponding parents). The metabolic profiles of these three compounds showed common biotransformation patterns, particularly in the phase II reactions (glucuronide conjugation, sulfation, GSH conjugation, and amino acid conjugation). Data-dependent exploration based on molecular network analysis of T3 profiles revealed that lipids and lipid-like molecules were the most enriched biotransformants. The subsequent subnetwork analysis proposed 14 additional features, including T4 in addition to 9 metabolized compounds that were annotated by prediction system based on possible hepatic enzymatic reaction. The other 10 THR agonistic negative compounds showed unique biotransformation patterns according to structural commonality, which corresponded to previous in vivo studies. Our evaluation system demonstrated highly predictive and accurate performance in determining the potential thyroid-disrupting activity of EDC-derived metabolites and for proposing novel biotransformants.

• Journal of Information Science Theory and Practice
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• v.12 no.2
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• pp.1-21
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• 2024

This study aims to develop a comprehensive technological framework anchored in a theoretical model to assess user satisfaction with university library websites (ULWs) in Myanmar. Adopting a quantitative approach, data were obtained via convenience sampling and subsequent inferential analysis. The target population for this study investigated users of various ULWs in Myanmar who were utilizing six university libraries. Of the collected responses, 273 valid surveys were analyzed using SPSS (version 25) and AMOS. Tools such as structural equation modeling and confirmatory factor analysis played pivotal roles in data interpretation and hypothesis validation. The proposed model highlights the significance of information quality, system quality, and librarian services in influencing both perceived usefulness (PU) and perceived ease of use (PEOU), culminating in user satisfaction. Notably, information quality and librarian services primarily impact PU, while system quality is more influential on PEOU. Interestingly, while PU has a direct bearing on user satisfaction, PEOU does not. Moreover, demographic elements such as age, gender, and education level introduce considerable differences in the utilization of ULW services. Drawing from the study's findings, recommendations are made for ULW managers in Myanmar to bolster services, aligning with user preferences. The resulting framework offers tangible benefits to Myanmar's educational sector, including academia, government entities, librarians, and policy framers. This pioneering research delves into the realm of ULWs in Myanmar's higher education sector. Practically, the research underscores the necessity for stakeholders, encompassing Myanmar's library experts and governing bodies, to elevate the standard of ULWs. Theoretically, a salient takeaway is the direct linkage between heightened usefulness and increased user satisfaction.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.629-643
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• 2023

The purpose of this study was to examine the effectiveness and efficiency of a policy by comparing and analyzing the impact of the rice market isolation system and production adjustment system (strategic crops direct payment system that induces the cultivation of other crops instead of rice) on rice supply, rice price, and government's financial expenditure. To achieve this purpose, a rice supply and demand forecasting and policy simulation model was developed in this study using a partial equilibrium model limited to a single item (rice), a dynamic equation model system, and a structural equation system that reflects the casual relationship between variables with economic theory. The rice policy analysis model used a recursive model and not a simultaneous equation model. The policy is distinct from that of previous studies, in which changes in government's policy affected the price of rice during harvest and the lean season before the next harvest, and price changes affected the supply and demand of rice according to the modeling, that is, a more specific policy effect analysis. The analysis showed that the market isolation system increased government's financial expenditure compared to the production adjustment system, suggesting low policy financial efficiency, low policy effectiveness on target, and increased harvest price. In particular, the market isolation system temporarily increased the price during harvest season but decreased the price during the lean season due to an increase in ending stock caused by increased production and government stock. Therefore, a decrease in price during the lean season may decrease annual farm-gate prices, and the reverse seasonal amplitude is expected to intensify.

• Journal of Korea Water Resources Association
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• v.57 no.6
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• pp.371-383
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• 2024

The quantification methods and definitions of resilience vary and are studied across many fields. However, this diversity can lead to gaps in interpretation regarding the meaning and indicators of resilience, potentially having a negative impact on resilience assessments. Therefore, uniform standards for defining and quantifying resilience are essential. This study presented a definition of resilience and socio-structural evaluation methods of resilience through network analysis. Furthermore, through analyzing various definitions of resilience, the definition of resilience in the context of urban flooding was presented. Distinguishing between static and dynamic resilience, an evaluation method based on common attributes was proposed. Lastly, the economic effects of introducing resilience were analyzed using an inundation trace map. Future research on the secondary effects through standardized resilience assessments is expected to be widely utilized in decision-making stages within urban flood policies.

• Journal of Korean Association for Spatial Structures
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• v.24 no.3
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• pp.43-51
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• 2024

Dynamic responses of nuclear power plant structure subjected to earthquake loads should be carefully investigated for safety. Because nuclear power plant structure are usually constructed by material of reinforced concrete, the aging deterioration of R.C. have no small effect on structural behavior of nuclear power plant structure. Therefore, aging deterioration of R.C. nuclear power plant structure should be considered for exact prediction of seismic responses of the structure. In this study, a machine learning model for seismic response prediction of nuclear power plant structure was developed by considering aging deterioration. The OPR-1000 was selected as an example structure for numerical simulation. The OPR-1000 was originally designated as the Korean Standard Nuclear Power Plant (KSNP), and was re-designated as the OPR-1000 in 2005 for foreign sales. 500 artificial ground motions were generated based on site characteristics of Korea. Elastic modulus, damping ratio, poisson's ratio and density were selected to consider material property variation due to aging deterioration. Six machine learning algorithms such as, Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), eXtreme Gradient Boosting (XGBoost), were used t o construct seispic response prediction model. 13 intensity measures and 4 material properties were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks present good prediction performance considering aging deterioration.

• Journal of Platform Technology
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• v.11 no.6
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• pp.47-55
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• 2023

With the goal of ensuring the safety of wheelchair users, this study was conducted using finite element analysis, focusing on the development of a platform that can be used to evaluate safety during the design stage. Safety evaluation criteria for wheelchairs used in vehicles are defined in ANSI/RESNA WC19 and ISO 7176-19. Based on these standards, finite element analysis was performed to assess the sectional forces of each component of the wheelchair and sensitivity analysis was conducted based on the specifications. These results were used to derive equivalent composite loads for the wheelchair's main components, determine the necessary sectional specifications for these main components in the wheelchair design phase, and investigate the process of safety assessment verification. The study showed that member forces vary with changes in the cross-sectional values of the wheelchair frame's main components, with the front and rear lower members, as well as the rear upper and lower members, requiring the highest cross-sectional values for safety design. This study offers a proactive method for evaluating safety in the wheelchair design stage, and in future research, we plan to develop a safety evaluation platform based on these results.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.95-112
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• 2020

This paper is to investigate how cognitive bias of college students and entrepreneurs relates to perceived risks and entrepreneurial opportunities that represent uncertainty, and how various cognitive bias and entrepreneurial efficacy In the same way. The purpose of this study is to find improvement points of entrepreneurship education for college students and to suggest problems and improvement possibilities in the decision making process of current entrepreneurs. This empirical study is a necessary to improve the decision-making of individuals who want to start a business at the time when various attempts are made to activate the start-up business and increase the sustainability of the existing SME management. And understanding of the difference in opportunity evaluation, and suggests that it is necessary to provide good opportunities together with the upbringing of entrepreneurs. In order to achieve the purpose of the study, questionnaires were conducted for college students and entrepreneurs. A total of 363 questionnaire data were obtained and demonstrated through structural equation modeling. This study confirms that there is some relationship between perceived risk and cognitive bias. Overconfidence and control illusions among cognitive bias have a significant relationship between perceived risk and wealth. Especially, it is confirmed that control illusion of college students has a significant relationship with perceived risk. Second, cognitive bias demonstrated some significant relationship with opportunity evaluation. Although we did not find evidence that excess self-confidence is related to opportunity evaluation, we have verified that control illusions and current status bias are related to opportunity evaluation. Control illusions were significant in both college students and entrepreneurs. Third, perceived risk has a negative relationship with opportunity evaluation. All students, regardless of whether they are college students or entrepreneurs, judge opportunities positively if they perceive low risk. Fourth, it can be seen from the college students 'group that entrepreneurial efficacy has a moderating effect between perceived risk and opportunity evaluation, but no significant results were found in the entrepreneurs' group. Fifth, the college students and entrepreneurs have different cognitive bias, and they have proved that there is a different relationship between entrepreneurial opportunity evaluation and perceived risk. On the whole, there are various cognitive biases that are caused by time pressure or stress on college students and entrepreneurs who have to make judgments in uncertain opportunities, and in this respect, they can improve their judgment in the future. At the same time, university students can have a positive view of new opportunities based on high entrepreneurial efficacy, but if they fully understand the intrinsic risks of entrepreneurship through entrepreneurial education and fully understand the cognitive bias present in direct entrepreneurial experience, You will get a better opportunity assessment. This study has limitations in that it is based on the fact that university students and entrepreneurs are integrated, and that the survey respondents are selected by the limited random sampling method. It is necessary to conduct more systematic research based on more faithful data in the absence of the accumulation of entrepreneurial research data. Second, the translation tools used in the previous studies were translated and the meaning of the measurement tools might not be conveyed due to language differences. Therefore, it is necessary to construct a more precise scale for the accuracy of the study. Finally, complementary research should be done to identify what competitive opportunities are and what opportunities are appropriate for entrepreneurs.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.185-196
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• 2023

This paper investigates the effects of entrepreneurs' cognitive biases on business opportunity evaluation, given their strong entrepreneurial spirit, which is characterized by innovation, proactivity, and risk-taking. When making decisions related to business activities, entrepreneurs typically make rational judgments based on their knowledge, experience, and the advice of external experts. However, in situations of extreme stress or when quick decisions are required, they often rely on heuristics based on their cognitive biases. In particular, we often see cases where entrepreneurs fail because they make decisions based on heuristics in the process of evaluating and selecting new business opportunities that are planned to guarantee the growth and sustainability of their companies. This study was conducted in response to the need for research to clarify the effects of entrepreneurs' cognitive biases on new business opportunity evaluation, given that the cognitive biases of entrepreneurs, which are formed by repeated successful experiences, can sometimes lead to business failure. Although there have been many studies on the effects of cognitive biases on entrepreneurship and opportunity evaluation among university students and general people who aspire to start a business, there have been few studies that have clarified the relationship between cognitive biases and social networks among entrepreneurs. In contrast to previous studies, this study conducted empirical surveys of entrepreneurs only, and also conducted research on the relationship with social networks. For the study, a survey was conducted using a parallel survey method using online mobile surveys and self-report questionnaires from 150 entrepreneurs of small and medium-sized enterprises. The results of the study showed that 'overconfidence' and 'illusion of control', among the independent variables of entrepreneurs' cognitive biases, had a statistically significant positive(+) effect on business opportunity evaluation. In addition, it was confirmed that the moderating variable, social network, moderates the effect of overconfidence on business opportunity evaluation. This study showed that entrepreneurs' cognitive biases play a role in the process of evaluating and selecting new business opportunities, and that social networks play a role in moderating the structural relationship between entrepreneurs' cognitive biases and business opportunity evaluation. This study is expected to be of great help not only to entrepreneurs, but also to entrepreneur education and policy making, by showing how entrepreneurs can use cognitive biases in a positive way and the influence of social networks.

• Journal of Korean Society of Steel Construction
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• v.16 no.2 s.69
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• pp.285-293
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• 2004

As a special infrastructure, it is important that the suspension bridges which were designed by using the cable are carefully maintained and safely inspected after their construction, more than what is done in other cases of bridge structures. However, the structural analysis for their design and maintenance has considered only the simplified geometric shape of the structure. Particularly, it is not easy to make the modeling analyze the bridge structure including detailed steel deck plates. In this paper, we evaluated the structural behaviors and performances of the completed earth-anchored suspension bridge that was in a completed state through both the tension of hanger member and their computational analysis. We considered the frame system and the detailed steel deck plates that were especially added into the modeling to take more precision analysis about it. We also applied hanger tensions converted by the natural frequency and the natural frequency of the bridge when in normal vibration. Results of the vehicle loading test were used in the analysis. We compared the results by using our modeling with the result of the loading test and the hanger tension. Our prediction on the behavior of the structure emulates the behavior of the real structure. In applying the data measured by the typhoon "Maemi" which arrived in-land last year, we confirmed our analysis model for the possibility of applying effectively into the preliminary design and maintenance plan.

• Journal of Navigation and Port Research
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• v.31 no.3 s.119
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• pp.235-245
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• 2007

Stiffened steel plates are basic structural members on the deck and bottom structure in ship, offshore. It has a number of one sided stiffeners in either one or both directions, the latter structure was called grillage structure. At the ship structural desgn stage, one of the major consideration is evaluation for ultimate strength of the hull girder. In general, it is accepted that hull girder strength can be represented by the local strength of the longitudinal stiffened panel. In case of considering hogging condition in a stormy sea, stiffened panel was acting on the bottom structure under axial compressive load induced hull girder bending moment, also simultaneously arising local bending moment induced lateral pressure load. In this paper, results of the structural analysis have been compared with another detailed FEA program and prediction from design guideline and a series analysis was conducted consideration of changing parameters for instance, analysis range, cross-section of stiffener, web height and amplitude of lateral pressure load subjected to combined load (axial compression and lateral pressure load). It has been found that finite element modeling is capable of predicting the behaviour and ultimate load capacity of a simply supported stiffened plate subjected to combined load of axial compression and lateral pressure load It is expected that these results will be used to examine the effect of interaction between lateral pressure and axial loads for the ultimate load-carrying capacity based on the Ultimate Limit State design guideline.