• Journal of Microbiology and Biotechnology
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• v.32 no.12
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• pp.1537-1546
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• 2022

Staphylococcus aureus is a cause of high mortality in humans and therefore it is necessary to prevent its transmission and reduce infections. Our goals in this research were to investigate the frequency of methicillin-resistant S. aureus (MRSA) in Taif, Saudi Arabia, and assess the relationship between the phenotypic antimicrobial sensitivity patterns and the genes responsible for resistance. In addition, we examined the antimicrobial efficiency and application of silver nanoparticles (AgNPs) against MRSA isolates. Seventy-two nasal swabs were taken from patients; MRSA was cultivated on Mannitol Salt Agar supplemented with methicillin, and 16S rRNA sequencing was conducted in addition to morphological and biochemical identification. Specific resistance genes such as ermAC, aacA-aphD, tetKM, vatABC and mecA were PCR-amplified and resistance plasmids were also investigated. The MRSA incidence was ~49 % among the 72 S. aureus isolates and all MRSA strains were resistant to oxacillin, penicillin, and cefoxitin. However, vancomycin, linezolid, teicoplanin, mupirocin, and rifampicin were effective against 100% of MRSA strains. About 61% of MRSA strains exhibited multidrug resistance and were resistant to 3-12 antimicrobial medications (MDR). Methicillin resistance gene mecA was presented in all MDR-MRSA strains. Most MDR-MRSA contained a plasmid of > 10 kb. To overcome bacterial resistance, AgNPs were applied and displayed high antimicrobial activity and synergistic effect with penicillin. Our findings may help establish programs to control bacterial spread in communities as AgNPs appeared to exert a synergistic effect with penicillin to control bacterial resistance.

• Journal of Environmental Health Sciences
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• v.44 no.2
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• pp.196-203
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• 2018

Objectives: The purpose of this study was to assess environmental risk on the emerging contaminants of concern, such as ivermetin, parziquantel, tamiflu and triclosan. Furthermore, we tried to provide a more efficient management practice and a basis for future studies of risk assessment on those substances. Methods: Predicted no effect concentration (PNEC) and predicted environmental concentration (PEC) were determined through modeling and literature reviews. Environmental risk assessment was evaluated by calculating HQ (hazard quotient) by a comparison of PEC (or measured environmental concentration (MEC)) and PNEC. Results: HQ value of tamiflu calculated from MEC was 1.9E-03. For ivermectin and triclosan, the HQ values were not available because these were not detected in the aquatic environment. The toxicity of ivermectin and triclosan showed a very low value, indicating a high level of HQ. However, praziquantel can be categorized into the material that do not require management since they have less than HQ 1. Conclusion: Based on the results of the initial risk assessment, it is assumed that the ivermectin and triclosan have potential to cause direct adverse effects on the aquatic environment. To conduct an accurate environmental risk assessment, the further study on PEC estimation of such contaminants should be actively carried out.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.111-119
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• 2024

In this paper, we propose a big data platform that can collect information from various sources collected at ocean. Currently operating ocean-related big data platforms are focused on storing and sharing created data, and each data provider is responsible for data collection and preprocessing. There are high costs and inefficiencies in collecting and integrating data in a marine environment using communication networks that are poor compared to those on land, making it difficult to implement related infrastructure. In particular, in fields that require real-time data collection and analysis, such as weather information, radar and sensor data, a number of issues must be considered compared to land-based systems, such as data security, characteristics of organizations and ships, and data collection costs, in addition to communication network issues. First, this paper defines these problems and presents solutions. In order to design a big data platform that reflects this, we first propose a data source, hierarchical MEC, and data flow structure, and then present an overall platform structure that integrates them all.

• Korean Journal of Clinical Laboratory Science
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• v.40 no.1
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• pp.48-54
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• 2008

Nine types of staphylococcal enterotoxin (SE) genes (sea~see, seg~sej), 3 types of virulence genes (eta, etb, tst), mecA and 16S rRNA as internal positive control were detected from 187 clinical MRSA (methicillin resistance Staphylococcus aureus) strains isolated from a variety hospitalized patients in Daegu and Gyeongsangbuk-do areas using the multiplex PCR. The frequency of the S. aureus strains harboring recently reported SE genes (seg~sej) were found to be very high (65.9%) and greater than that of the strains harboring classical SE (sea~see) genes (47.8%) as previously established. Taking into account that the newly described pairs form SE genes (i.e., sec+seg+sei, seg+sei) were many, in the other hand, single form SE genes (i.e., seg, seh, sei and sej) were rarely detected. The S. aureus with pairs form enterotoxigenic genes become more potentially toxigenic strains. Furthermore, this work indicated a systematic association between the seg and sei genes and their high incidence among the S, aureus strains, which suggests that these two SE's could be an important phylogenetic link among the staphylococcal enterotoxins.

• KNOM Review
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• v.23 no.1
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• pp.34-42
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• 2020

Network Function Virtualization (NFV) environment can deal with dynamic changes in traffic status with appropriate deployment and scaling of Virtualized Network Function (VNF). However, determining and applying the optimal VNF deployment is a complicated and difficult task. In particular, it is necessary to predict the situation at a future point because it takes for the process to be applied and the deployment decision to the actual NFV environment. In this paper, we randomly generate service requests in Multiaccess Edge Computing (MEC) topology, then obtain training data for machine learning model from an Integer Linear Programming (ILP) solution. We use the simulation data to train the machine learning model which predicts the optimal VNF deployment in a predefined future point. The prediction model shows the accuracy over 90% compared to the ILP solution in a 5-minute future time point.

• Journal of Chest Surgery
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• v.30 no.1
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• pp.1-10
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• 1997

The successful cardiac transplantation depends partly on the donor heart preservation by a solution that will ensure recovery of myocardial function. The purpose of this study was to perform the evaluation of various preservation solutions and to accumulate the data on the requisites for ideal preservation solution. The experimental setup was the constant pressure Langendorffs perfusion system. Isolated rabbit hearts were perfused for 20minutes with unarm Krebs-Henseleit solution, stored for 4 hours in cold preservation solution after cardioplegia, and then were reperfused for 20minutes. The 4 experimental groups were prepared Hartmann's solution group (group 1, control), modified Euro-collins solution group(group II. MEC), modified University of Wisconsin group (group n, MUW), and CK solution(made by the author) group (group W, CK). The parameters for assessing the preservation ability were levels of enzymes in freezed myocardial tissues (lactate, creatine kinase-MB and adenosine deaminase), coronary flow. left ventricular developing pressure and dpldt. In conclusion, the ability of preservation for isolated rabbit heart was excellent in CK solution and modified University of Wisconsin solution, and poor in modified Euro-collins solution, compared with Hartmann solution. CK solution has low potassium concentrations(34.2mEq/L) and includes various substrates to be salutary on myocardial preservation. This fact may indicates the necessity of further refinements in selection or composition of electrolytes and substrates.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.669-674
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• 2017

Due to the depletion of fossil fuels and the increase in environmental pollution, electric vehicles are attracting attention as next-generation transportation and are becoming popular all over the world. As the interest in electric vehicles and the penetration rate increase, studies on the charging infrastructure with vehicle-to-grid (V2G) technology and information technology are actively under way. In particular, communication with the grid network is the most important factor for stable charging and load management of electric vehicles. However, with the existing centralized infrastructure, there are problems when control-message requests increase and the charging infrastructure cannot efficiently operate due to slow response speed. In this paper, we propose a new charging infrastructure using mobile edge computing (MEC) that mitigates congestion and provides low latency by applying distributed cloud computing technology to wireless base stations. Through a performance evaluation, we confirm that the proposed charging infrastructure (with low latency) can cope with peak conditions more efficiently than the existing charging infrastructure.

• ALGAE
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• v.28 no.4
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• pp.371-378
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• 2013

Water and methanolic extracts of Ecklonia cava, a marine brown alga, were prepared by ultrasonic extraction (UE) and conventional extraction (CE) methods. The radical-scavenging activity and the inhibitory effects against hydrogen peroxide ($H_2O_2$)-induced DNA damage of the extracts were investigated. All extracts prepared by CE exhibited higher total polyphenolic content than that in the extracts prepared by UE. Extraction yield and total phenolic content increased as the UE time increased. The radical-scavenging activities increased as the UE time increased. All extracts prepared by CE exhibited higher 1,1-diphenyl-2-pricrylhydrazyl (DPPH) and hydroxyl radical-scavenging activities than did those prepared by UE. Extracts prepared by UE showed stronger scavenging activities on alkyl radical and $H_2O_2$ than those prepared by CE did. Methanolic extract with UE 12 h (100MEU-12h) and methanolic extract with CE 24 h (100MEC-24h) were selected and evaluated by comet assay for their inhibitory effect against $H_2O_2$-induced DNA damage. 100MEU-12h showed slightly greater protective effect against $H_2O_2$-induced DNA damage than 100MEC-24h. Thus, UE can be effectively used as a seaweed extraction technique, and there is potential for scale-up of the extraction process.

• Journal of Korean Society on Water Environment
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• v.37 no.6
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• pp.501-509
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• 2021

In 2018, total 263 micro and emerging contaminants were selected as target substances by the Ministry of Environment, and 80 of them were first-class substance including endocrine disruptors, residual Pharmaceuticals and Personal Care Products (PPCPs), residual organic pollutants, pesticides and heavy metals. In this study, in order to evaluate the Hazard Quotient (HQ) of the 80 types in the domestic water environment the concentration of discharged effluent and nearby water environment reported by Korean institutes since 2010 was investigated. There were 45 substances reported to be detected, and Measurement Environment Concentration (MEC) were obtained by collectively converting them into water environment concentration. For biotoxicity, half maximal Effective Dose (EC50) to Daphnia magna, a water fleas species widely adopted in Material Safety Data Sheet (MSDS) was applied. As for the biotoxicity level, the Predicted No-Effect Concentration (PNEC) was obtained by applying the Assessment Factor (AF) and the HQ was derived by dividing it from the MEC. As a result of calculating the HQ, more than 1 substances were Cabamazepine, Mefenamic acid, Acetaminophen, Ibuprofen, Nonylphenol, Nickel, Erythromycin, Acetylslic acid, etc. Meanwhile, perfluorinated compounds were identified as hazardous substances in the water env ironment, with 5 out of 14 species included in the 20 ranks of first-class substance.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.537-541
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• 2022

As technology advances, various applications linked to the music industry are becoming popular through new media. There have been many changes in the music market. Beyond the existing music market, where music copyright and performance rights were the center of the music business, we are unifying and operating communication channels that connect artists and fans, such as investment products derived from music copyrights. The technology that connects the fandom with additional business digital content has transformed into global platforms such as HYBE Entertainment's and YG Entertainment's Weverse, as well as SM Entertainment's Bubble. In addition, various national support projects to build a 5G MEC (MobileEdge Computing) environment to quickly respond to the rapidly changing 5G industry ecosystem are supporting for the immersive content demonstration, immersive content testing, and technical analysis, we are laying the groundwork to efficiently respond to the ever-expanding metaverse content market. Technology is changing dramatically. Therefore, we would like to study to changes in the music market brought about by technology and suggest strategies for a new era in the music business.