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Survey on the Status of Microbial Contamination of Chicken Meats Collected from Poultry Processing Plants in Nationwide (우리나라 도계장 수거계육의 미생물학적 위생실태 조사)

  • Woo, Yong-Ku
    • Korean Journal of Microbiology
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    • v.43 no.3
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    • pp.186-192
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    • 2007
  • This study was conducted to survey the hygienic status of chicken meats on the microbial levels, which were collected from poultry processing plants located in the local provinces in nationwide including the JeJu island (n=15) in 1997. In particular, Salmonella spp., Campylobacter jejuni, and Listeria monocytogenes, which were retarded as one of the most important entero-pathogens relating to food home illness from poultry, were investigated on their isolation frequency including the other pathogens related on the food-borne illness. A total of 115 processed chickens were submitted on the present study. In general, the bacterial contamination frequency showed more or less lower $(10{\sim}100 cells)$ than those of sold on the retail and super markets and department stores because of lacking of cross-contamination incidences, depending on the total cells, Coliforms and Staphylococcal cells count. While, Salmonella species, Campylobacter jejuni, Listeria monocytogenes, and coagulase positive Staphylococcus aureus isolation frequency of chicken meats from slaughter houses were 58.3%, 37.4%, 43.5%, and 30.4%, in order. But the present microbial isolation data were a little lower levels than those of sold on the retail and super markets and famous department stores in Seoul and GyeongGi province at the same period. It seemed that the cross-contamination problems (including the human, environmental and instrumental factors) during the marketing stage (after the last processing procedure; rinsing step) had the major roles on the increasing of the microbial contamination frequency on the chicken meats after the slaughter houses.

Electrochemical Characteristic on Hydrogen Intercalation into the Interface between Electrolyte of the 0.1N H2SO4and Amorphous Tungsten Oxides Thin Film Fabricated by Sol-Gel Method (졸-겔법으로 제조된 비정질의 텅스텐 산화물 박막과 황산 전해질 계면에서 일어나는 수소의 층간 반응에 대한 전기화학적 특성)

  • Kang, Tae-Hyuk;Min, Byoung-Chul;Ju, Jeh-Beck;Sohn, Tae-Won;Cho, Won-Il
    • Applied Chemistry for Engineering
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    • v.7 no.6
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    • pp.1078-1086
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    • 1996
  • The peroxo-polytungstic acid was formed by the direct reaction of tungsten powder with the hydrogen peroxide solution. Peroxo-polytungstic powder were prepared by rotary evaporator using the fabricated on to ITO coated glass as substrate by dip-coating method using $2g/10mL(W-IPA/H_2O)$ sol solution. A substrate was dipped into the sol solution and after a meniscus had settled, the substrate was withdrawn at a constant rate of the 3mm/sec. Thicker layer could be built up by repeated dipping/post-treatment 15 times cycles. The layers dried at the temperature of $65{\sim}70^{\circ}C$ during the withdrawn process, and then tungsten oxides thin film was formed by final heating treatment at the temperature of $230{\sim}240^{\circ}C$ for 30min. A linear rotation between the thickness of thin film and the number of dipping/post-treatment cycles for tungsten oxides thin films made by dip-coating was found. The thickness of thin film had $60{\AA}$ after one dipping. From the patterns of XRD, the structure of tungsten oxides thin film identified as amorphous one and from the photographs of SEM, the defects and the moderate cracks were observed on the tungsten oxides thin film, but the homogeneous surface of thin films were mostly appeared. The electrochemical characteristic of the $ITO/WO_3$ thin film electrode were confirmed by the cyclic voltammetry and the cathodic Tafel polaization method. The coloring bleaching processes were clearly repeated up to several hundreds cycles by multiple cyclic voltammetry, but the dissolved phenomenon of thin film revealed in $H_2SO_4$ solution was observed due to the decrease of the current densities. The diffusion coefficient was calculated from irreversible Randles-Sevick equation from the data obtained by the cyclic voltammetry with various scan rates.

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Effect of Fermented Cucumber Beverage on Ethanol Metabolism and Antioxidant Activity in Ethanol-treated Rats (오이 발효음료가 만성적으로 에탄올을 급여한 흰쥐의 에탄올 대사와 항산화방어계에 미치는 영향)

  • Lee, Hae-In;Seo, Kwon-Il;Lee, Jin;Lee, Jeom-Sook;Hong, Sung-Min;Lee, Ju-Hye;Kim, Myung-Joo;Lee, Mi-Kyung
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.40 no.8
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    • pp.1099-1106
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    • 2011
  • Cucumber fermentation has been used as a means of preservation. This study was performed to investigate the effects of fermented cucumber beverage (CF) containing beneficial materials for an ethanol hangover based on Hovenia dulcis (SKM) on ethanol-induced hepatotoxicity. Male Sprague-Dawley rats were randomly divided into three groups: ethanol control, ethanol plus SKM, and ethanol plus CF+SKM. SKM or CF+SKM was orally administered at a dose of 7 mL/kg body weight once per day for 5 weeks. Control rats were given an equal amount of water. CF+SKM significantly lowered plasma ethanol levels, whereas SKM tended to decrease the levels compared to the control. Both SKM and CF+SKM significantly lowered the plasma acetaldehyde levels and serum transaminase activities compared to those in the control. SKM and CF+SKM did not affect hepatic alcohol dehydrogenase activity; however, it significantly inhibited cytochrome P450 2E1 (CYP2E1) activity. Hepatic aldehyde dehydrogenase (ALDH) activity was significantly higher in the SKM and CF+SKM groups than that in the control group. Plasma acetaldehyde concentration was significantly correlated with hepatic CYP2E1 (r=0.566, p<0.01) activity and ALDH (r=-0.564, p<0.01) activity. Hepatic superoxide dismutase and catalase activities as well as glutathione content increased with the SKM and CF+SKM administration, whereas lipid peroxide content decreased significantly. Furthermore, SKM and CF+SKM lowered plasma and hepatic lipid content and lipid droplets compared to those in the control group. These results indicate that SKM and CF+SKM exhibit hepatoprotective properties partly by inhibiting CYP2E1 activity, enhancing ALDH activity and stimulating the antioxidant defense systems in ethanol-treated rats.

Chemical Changes of Meju made with Barly Bran Using Fermentation (보리등겨로 제조한 메주의 발효기간에 따른 각종 성분 변화)

  • Kwon, O-Jun;Choi, Ung-Kyu;Lee, Eun-Jeong;Cho, Young-Je;Cha, Won-Senp;Son, Dong-Hwa;Chung, Yung-Gun
    • Korean Journal of Food Science and Technology
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    • v.32 no.5
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    • pp.1135-1141
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    • 2000
  • For investigation of new utilization as jang-products, Meju was prepared using barely bran. As barley meju was fermented, change of pH was $5.2{\sim}5.6$, it was indistinguishable change. L-value of color was changed from 46.9 to 60.3, that meant it was getting moe dark. The counts of aerobic bacteria were $4.8{\times}10^7{\sim}5.6{\times}10^9$ CFU/g, it was extraordinarily increased during fermentation. Counts of Yeast, molds, and bacteria were $9.1{\times}10^6{\sim}5.0{\times}10^8$ CFU/g, $8.3{\times}10^5{\sim}6.9{\times}10^7$, and $2.0{\times}10^2{\sim}4.5{\times}10^6$ CFU/g, respectively. Crude ash content was $3146.0{\sim}7147.4$ mg%. The level of K was the highest in quantity among the crude ash in barely meju. 7 free sugars(i.e., raffnose, stachyose, inositol, fructose, glucose, arabinose, and maltose), 3 volatile organic acid(i.e., acetic acid, propionic acid, and butyric acid) and 4 non-volatile organic acid(i.e., fumaric acid, ${\alpha}-ketoglutaric$ acid, malic acid, and citric acid) were detected. The content of free amino acid was $596.3{\sim}1580.8$ mg%. Glutamic acid was most abundant component among the amino acids, 2nd abundant component was alanine, it's content was $79.9{\sim}165.3$ mg%, 3rd abundant component was leucine, it's count was $41.7{\sim}161.6$ mg%. Finally, essential amino acid content was revealed $33.2{\sim}40.38%$.

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An Intelligent Decision Support System for Selecting Promising Technologies for R&D based on Time-series Patent Analysis (R&D 기술 선정을 위한 시계열 특허 분석 기반 지능형 의사결정지원시스템)

  • Lee, Choongseok;Lee, Suk Joo;Choi, Byounggu
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.79-96
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    • 2012
  • As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.