• Proceedings of the Korean Society of Crop Science Conference
• /
• 2022.10a
• /
• pp.33-33
• /
• 2022

Rice (Oryza sativa L.) is a widely studied domesticated model plant. Seed awning is an unfavorable trait during rice harvesting and processing. Hence, awn was one of the target characters selected during domestication. However, the genetic mechanisms underlying awn development in rice are not well understood. In this study, we analyzed the genes for awn development using a mapping population derived from a cross between the Korean indica cultivar 'Milyang23' and NIL4/9 (derived from a cross between 'Hwaseong' and O. minuta). Two quantitative trait loci (QTLs), qAwn4 and qAwn9 were mapped on chromosome 4 and 9, respectively, increased awn length in an additive manner. Through comparative sequencing analyses parental lines, LABA1 was determined as the causal gene underlying qAwn4. qAwn9 was mapped to a 199-kb physical region between markers RM24663 and RM24679. Within this interval, 27 annotated genes were identified, and five genes, including a basic leucine zipper transcription factor 76 (OsbZIP76), were considered candidate genes for qAwn9 based on their functional annotations and sequence variations. Haplotype analysis using the candidate genes revealed tropical japonica specific sequence variants in the qAwn9 region, which partly explains the non-detection of qAwn9 in previous studies that used progenies from interspecific crosses. This provides further evidence that OsbZIP76 is possibly a causal gene for qAwn9. The O. minuta qAwn9 allele was identified as a major QTL associated with awn development in rice, providing an important molecular target for basic genetic research and domestication studies. Our results lay the foundation for further cloning of the awn gene underlying qAwn9.

• Journal of Korean Society for Quality Management
• /
• v.51 no.3
• /
• pp.381-401
• /
• 2023

Purpose: The purpose of this study was to understand the perception of medical staff to propose an infected patient transport robot as a means of responding to infectious diseases. Methods: The data collected through the survey was analyzed through AHP analysis. The measurement tools used in this study were derived through the SERVQUAL model and Focus Group Interview(FGI), and consisted of four detailed questions for each of five classes: tangible, reliability, responsiveness, assurance, and empathy. Results: As a result of the study, there are concerns about risk factors that may occur in areas where medical staff intervention is minimized. Above all, we confirmed the consensus that safety should be the top priority during the process of robots to transport patients. In particular, highlighted were the resolution of device errors that may occur during the process for transporting patients and easy provision of the first aid. Additionally, the ability to monitor patients and suppress infection factors turned out to be important, which was directly related to the simplification of the role of medical staff and work efficiency. Conclusion: As one of the means of effectively controlling infectious diseases in a pandemic situation, a robot to transport the infected patient was considered. However, in order to commercialize this, specific verification of the safety of medical staff and patients is needed, and empirical data on providing the first aid, patient monitoring, and infection factor suppression should be presented.

• Journal of Web Engineering
• /
• v.14 no.15
• /
• pp.3125-3135
• /
• 2022

Alzheimer's disease (AD) is an irreversible neurodegenerative disease characterized by memory and cognitive impairments. Neurogenesis, which is related to memory and cognitive function, is reduced in the brains of patients with AD. Therefore, enhancing neurogenesis is a potential therapeutic strategy for neurodegenerative diseases, including AD. Hesperidin (HSP), a bioflavonoid found primarily in citrus plants, has anti-inflammatory, antioxidant, and neuroprotective effects. The objective of this study was to determine the effects of HSP on neurogenesis in neural stem cells (NSCs) isolated from the brain of mouse embryos and five familial AD (5xFAD) mice. In NSCs, HSP significantly increased the proliferation of NSCs by activating adenosine monophosphate (AMP)-activated protein kinase (AMPK)/cAMP-response element-binding protein (CREB) signaling, but did not affect NSC differentiation into neurons and astrocytes. HSP administration restored neurogenesis in the hippocampus of 5xFAD mice via AMPK/brain-derived neurotrophic factor/tropomyosin receptor kinase B/CREB signaling, thereby decreasing amyloid-beta accumulation and ameliorating memory dysfunction. Collectively, these preclinical findings suggest that HSP is a promising candidate for the prevention and treatment of AD.

• Bulletin of the Korean Chemical Society
• /
• v.33 no.5
• /
• pp.1707-1714
• /
• 2012

Grb2 is an adapter protein involved in the signal transduction and cell communication. The Grb2 is responsible for initiation of kinase signaling by Ras activation which leads to the modification in transcription. Ligand based pharmacophore approach was applied to built the suitable pharmacophore model for Grb2. The best pharmacophore model was selected based on the statistical values and then validated by Fischer's randomization method and test set. Hypo1 was selected as a best pharmacophore model based on its statistical values like high cost difference (182.22), lowest RMSD (1.273), and total cost (80.68). It contains four chemical features, one hydrogen bond acceptor (HBA), two hydrophobic (HY), and one ring aromatic (RA). Fischer's randomization results also shows that Hypo1 have a 95% significant level. The correlation coefficient of test set was 0.97 which was close to the training set value (0.94). Thus Hypo1 was used for virtual screening to find the potent inhibitors from various chemical databases. The screened compounds were filtered by Lipinski's rule of five, ADMET and subjected to molecular docking studies. Totally, 11 compounds were selected as a best potent leads from docking studies based on the consensus scoring function and critical interactions with the amino acids in Grb2 active site.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.2
• /
• pp.611-618
• /
• 2020

The reliability of the results of LCC analysis is determined by accurate analytical procedures and energy data from which the uncertainty is removed. Until now, systems that can automatically measure these energy data and produce databases have not been commercialized. Therefore this paper proposes a concept model of an S-LCC platform that can automatically collect and analyze electric energy consumption data of equipment systems using the IOT, which is the core tool in the Fourth Industrial Revolution and operates the equipment system efficiently using the analyzed results. The proposed concept model was developed by the convergence of existing BLCS and IOT and was comprised of five modules: Facility Control Module, LCC Analysis Module, Energy Consumption Control Module, Efficiency Analysis Module, and Maintenance Standard Reestablishment Module. Using the results of LCC analysis deduced from this system, the deterioration condition of an equipment system can be identified in real-time. The results can be used as the baseline data to re-establish standards for the maintenance factor, replacement frequency, and lifetime of existing equipment, and establish new maintenance standards for new equipment. If the S-LCC platform is established, it would increase the reliability of LCC analysis, reduce the labor force for entering data and improve accuracy, and would also change disregarded data into big data with high potential.

• The Journal of the Korea Contents Association
• /
• v.14 no.8
• /
• pp.505-516
• /
• 2014

This study was aimed at identifying the influence of Creative Thinking Filtering Mode program in international gifted program: how much it influences to improve the cognitive domains of creativity (fluency, flexibility, originality) and affective domains of creativity (independence, curiosity, diversity, sensitivity, sense of humor, individuality. To analyze data, ANCOVA(Analysis of Covariance)test was conducted, and the results are as belows. Firstly, the group applied in CTFM program was higher than controlled group on the domains of cognitive and affective. Specifically, in the factors of fluency, flexibility and originality among three cognitive domains and factors of individuality.In affective domains of creativity, independence, curiosity, diversity, a sense of humor among the five factors except of sensitivity were higher. Secondly, the result of analyzing the difference between before and after applying CTFM program was that three elements in cognitive domains : fluency, flexibility and originality improved, especially, the fluency was the most improved. Thirdly, the result of analyzing the difference of affective factor between before and after applying CTFM program was that the originality, diversity, a sense of humor and individuality among the 6 elements of affective domain improved, especially the individuality was the most improved.

• Journal of the Korean Society for Railway
• /
• v.19 no.4
• /
• pp.539-546
• /
• 2016

It is over 12 years since the launch of Korea Train eXpress (KTX) services. Demand for the KTX has been on the increase continuously but few studies have been produced related to this phenomenon. KTX passenger demand has been constantly increasing due to influencing factors such as the expansion of network, rise of oil prices, etc. In this study, our main focus is to verify that there are other types of elements that are causing an increase in KTX demand; our approach looks at changes in social and psychological aspect that have occurred due to the reduction of travel time and cost, as well as the imposition of a five-day workweek. In other words, we considered diffusion theory in the marketing area, which affects product selection and purchasing attitudes, as a key factor that is causing passenger demand to increase. That is to say that it is hypothesized that the demand for travel on the KTX has increased due to the train's utility, which is spread by the diffusion effect Therefore, the Bass diffusion model was applied to explain the dramatic increase in KTX passenger demand. Based on this foundation, it was also discussed how certain marketing strategies that incorporate the diffusion effect should be considered variously for sustainable management of rail transportation, while considering a steady passenger demand.

• Korea Real Estate Review
• /
• v.28 no.4
• /
• pp.37-51
• /
• 2018

The purpose of this paper is to analyze the effects of location factors on sales by restaurant type in the six districts of Seoul (Jongno-gu, Jung-gu, Yeongdeungpo-gu, Gangnam-gu, Seocho-gu, and Songpa-gu). Ordinary least squares (OLS) regression model is selected for four restaurant types whose spatial autocorrelation is not identified, spatial lag model (SLM) is only selected for seafood restaurant, and spatial error model (SEM) is selected for nine other restaurant types. The floating population and the workers of surrounding businesses have generally positive effects on the sales of restaurants. The floating population elasticity of the sales of restaurants are found to be in the descending order of Oriental food, pub, Western food, and traditional food restaurant, and the elasticity of the workers of surrounding businesses are in the descending order of bakery, Oriental food, and Western food restaurant. The spatial multiplier effects are in the descending order of Oriental food, pub, and Western food restaurant. There is a statistically significant sales gap between roast meat, pub, and bakery in Gangnam-gu and those in five other districts. The results of this research can help in starting a restaurant in that they can provide information on the suitability of location by restaurant type.

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.32 no.1
• /
• pp.64-77
• /
• 2022

Objectives: The purpose of this study is to objectify the level of case management performance and the factors influencing performance, to improve the case management performance at the Korea Worker's Compensation & Welfare Service (KWCWS) on the basis of the recognition of the objective realities of case management by job coordinators at the KWCWS, to develop a model of case management fit for the KWCWS, and to provide a basis for establishing guidelines for standardized case management. Methods: A total of 156 questionnaires were distributed to job coordinators at the KWCWS's headquarters, six regional headquarters, and 55 branches. One hundred forty-one questionnaires were collected and 126 were analyzed statistically using SPSS 21.0. Factor analysis and reliability analysis were conducted to verify the validity and reliability of the main measurement items in the research model. Frequency analysis was conducted for general characteristics of survey subjects. Frequency analysis or descriptive statistics were conducted to identify the level of independent variables (case manager's individual variables, job variables, institutional and organizational variables). Dependent variables (case management performance) and the degree of correlation were analyzed through correlation analysis between research variables. Multiple regression analysis and hierarchical regression analysis were conducted to examine the effect of independent variables on case management performance. Results: The results of the study showed that the level of overall performance in the five stages of case management was ordinary, with an average level of 3.45 on a 5-point scale. Levels of performance by step were institutional approach and intake (3.69), assessment (3.63), goal setting and intervention planning (3.46), implementation of intervention plan (3.32), and evaluation and termination (3.20), in that order. The explanatory power of case management performance (overall) by case managers with the KWCWS was case manager's institutional and organizational variables, job variables, and individual variables, in that order. At each stage of case management, the explanatory power of a case manager's institutional and organizational variables was found to be the greatest. The model changes at each stage of case management assume similar aspects statistically. In hierarchical regression analysis, it was institutional support that had a significant effect on case management performance (overall), and institutional support had the greatest effect. The results of multiple regression analysis in which all variables are input simultaneously showed that institutional support and expertise as well as self-efficacy had a positive effect. However, case management work experience, expertise (technology), and autonomy were found to have a negative effect during the stage of case management performance. Conclusions: As a result of the study, it was confirmed that raising the case manager's expertise and support from the institution and organization are important factors to improve the level of case management performance. The research also derived practical ways of reinforcement of case manager capacity, institutional and organizational support, operation of rehabilitation-case management teams, and occupational health-related aspects.

• Economic and Environmental Geology
• /
• v.56 no.3
• /
• pp.331-341
• /
• 2023

When creating a soil contamination map using geostatistical techniques, there are various sources that can affect prediction errors. In this study, a grid-based soil contamination map was created from the sampling data of heavy metal concentrations in soil in abandoned mine areas using Ordinary Kriging. Five factors that were judged to affect the prediction error of the soil contamination map were selected, and the variation of the root mean squared error (RMSE) between the predicted value and the actual value was analyzed based on the Leave-one-out technique. Then, using a machine learning algorithm, derived the top three factors affecting the RMSE. As a result, it was analyzed that Variogram Model, Minimum Neighbors, and Anisotropy factors have the largest impact on RMSE in the Standard interpolation. For the variogram models, the Spherical model showed the lowest RMSE, while the Minimum Neighbors had the lowest value at 3 and then increased as the value increased. In the case of Anisotropy, it was found to be more appropriate not to consider anisotropy. In this study, through the combined use of geostatistics and machine learning, it was possible to create a highly reliable soil contamination map at the local scale, and to identify which factors have a significant impact when interpolating a small amount of soil heavy metal data.