• Title/Summary/Keyword: Activity Coefficient Models

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Development and Validation of Exposure Models for Construction Industry: Tier 1 Model (건설업 유해화학물질 노출 모델의 개발 및 검증: Tier-1 노출 모델)

  • Kim, Seung Won;Jang, Jiyoung;Kim, Gab Bae
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.24 no.2
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    • pp.208-218
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    • 2014
  • Objectives: The major objective of this study was to develop and validate a tier 1 exposure model utilizing worker exposure monitoring data and characteristics of worker activities routinely performed at construction sites, in order to estimate worker exposures without sampling. Methods: The Registration, Evaluation, Authorization and Restriction of Chemicals(REACH) system of the European Union(EU) allows the usage of exposure models for anticipating chemical exposure of manufacturing workers and consumers. Several exposure models have been developed such as Advanced REACH Tools(ART). The ART model is based on structured subjective assessment model. Using the same framework, a tier 1 exposure model has been developed. Worker activities at construction sites have been analyzed and modifying factors have been assigned for each activity. Korean Occupational Safety and Health Agency(KOSHA) accrued work exposure monitoring data for the last 10 years, which were retrieved and converted into exposure scores. A separate set of sampling data were collected to validate the developed exposure model. These algorithm have been realized on Excel spreadsheet for convenience and easy access. Results: The correlation coefficient of the developed model between exposure scores and monitoring data was 0.36, which is smaller than those of EU models(0.6~0.7). One of the main reasons explaining the discrepancy is poor description on worker activities in KOSHA database. Conclusions: The developed tier 1 exposure model can help industrial hygienists judge whether or not air sampling is required or not.

A Structural Equation Modeling of the Process of Science Related Career Choice (과학 관련 진로 선택 과정의 구조 방정식 모형)

  • Yoon, Jin;Pak, Sung-Jae
    • Journal of The Korean Association For Science Education
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    • v.23 no.5
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    • pp.517-530
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    • 2003
  • The purpose of this study is to find out a model to explain the process of students' science-related career choice by identifying the causal relationships between science career choice and related factors. Important factors of science-related career choice were identified through factor analysis. 'Perception about career related to science', 'preference for science learning' and 'participation in science related activity' were three main factors of science-related career choice. A questionnaire was developed to know the factors of students' science-related career choice, and so as to make it possible to be analysed by structural equation modeling. The subject were 947 grade 6, 9, and 11 students in Seoul. Numbers of boys and girls in each grade was almost same. According to the structural equation modeling, 4 corrected models were obtained. In all 4 corrected models, 'perception about career related to science' had direct influence, and 'preference for science learning' and 'participation in science related activity' had indirect influence on science-related career choice. In the most fitting model. 'perception about career related to science' had an effect on science-related career choice with standardized total effect coefficient 1.03(direct effect 0.82, indirect effect 0.21). 'Preference for science learning', which influence 'participation in science related activity', had an effect on science-related career choice with standardized indirect effect coefficient 0.65. 'Participation in science related activity', which influence 'perception about career related to science'. had an effect on science-related career choice with standardized indirect effect coefficient 0.79. The implication to school science education is that it is most effective to raise the 'perception about career related to science' in order to make more students choose science related career. It is also effective to have more students participate in science related activity and enhance the preference for science learning. To explain the process of science related career choice more fully, it is necessary to build a more comprehensive model containing more factors influencing science-related career choice. It is necessary to test and complement the structural equation model by enlarging the subject to science high school students and science related college students.

P56 LCK Inhibitor Identification by Pharmacophore Modelling and Molecular Docking

  • Bharatham, Nagakumar;Bharatham, Kavitha;Lee, Keun-Woo
    • Bulletin of the Korean Chemical Society
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    • v.28 no.2
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    • pp.200-206
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    • 2007
  • Pharmacophore models for lymphocyte-specific protein tyrosine kinase (P56 LCK) were developed using CATALYST HypoGen with a training set comprising of 25 different P56 LCK inhibitors. The best quantitative pharmacophore hypothesis comprises of one hydrogen bond acceptor, one hydrogen bond donor, one hydrophobic aliphatic and one ring aromatic features with correlation coefficient of 0.941, root mean square deviation (RMSD) of 0.933 and cost difference (null cost-total cost) of 66.23. The pharmacophore model was validated by two methods and the validated model was further used to search databases for new compounds with good estimated LCK inhibitory activity. These compounds were evaluated for their binding properties at the active site by molecular docking studies using GOLD software. The compounds with good estimated activity and docking scores were evaluated for physiological properties based on Lipinski's rules. Finally 68 compounds satisfied all the properties required to be a successful inhibitor candidate.

A Study on the Forecasting Model for Patent Using R&D Inputs (R&D투입요소를 이용한 특허예측모형에 관한 연구)

  • 이재하;박동진
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.20 no.44
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    • pp.257-261
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    • 1997
  • Patents often serve as leading indicators of technological change. This patenting activity reflected R&D (Research & Development) of new technology. The purpose of this study is to set up a forecasting model that anticipate the number of domestic patent applications and the number of patents granted relating to R&D inputs (R&D expenditure, R&D manpower) at the level of three industrial sectors in Korea : electrical-electronic, machinery, chemical etc. In this study, forecasting models were used trend extrapolation and a set of regressions. Both Theil's inequality coefficient and MAE(Mean Absolute Error) were utilized to test the precision of predicted value. The patent data and the R&D data were based on Indicators of Industrial Technology data throught 1980 to 1996. The major results obtained in this study are as follows (1) The regression model is more useful for forecasting the trends of the number of patent applications and patents granted than the trend extrapolation method. (2) The variance of Theil's inequality is smaller in patent applications than in patent granted.

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CoMFA Analyses on the Fungicidal Activity with N-phenylbenzensulfonamide Analogues against Gray Mold (Botrytis cinerea) (잿빛곰팡이균(Botrytis cinerea)에 대한 N-phenylbenzenesulfonamide 유도체들의 살균활성에 관한 CoMFA 분석)

  • Hwang, Tae-Yeon;Kang, Kyu-Young;Sung, Nack-Do
    • The Korean Journal of Pesticide Science
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    • v.12 no.2
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    • pp.111-117
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    • 2008
  • The comparative molecular field analysis (CoMFA) for the fungicidal activity with N-phenylbenzenesulfonamide analogues (1-45) against gray mold (Botriyts cinerea) were studied quantitatively. The statistical values of CoMFA models had much better predictability and fitness than those of comparative molecular similarity indices analysis (CoMSIA) models. The statistical values of the optimized CoMFA I model were predictablity, $r^2_{cv.}(or\;q^2)=0.457$ and correlation coefficient, $r^2_{ncv.}=0.959$, and their fungicidal activity was dependent on the steric field (52%) and electrostatic field (35.6%) of the substrate molecules. And also, it was found that the optimized CoMFA I model with the sensitivity to perturbation ($d_q^{2'}/dr^2_{yy'}=0.898$) and prediction ($q^2=0.346$ & SDEP=0.614) produced by a progressive scrambling analysis was not dependent on chance correlation. From the results of graphical analyses on the contour maps with the optimized CoMFA I model, it is expected that the $R_3$ and $R_4$-substituents on the N-phenyl ring as steric favor group and para-substituents ($R_1$) on the S-phenyl ring as steric disfavor group will contribute to the fungicidal activity. Therefore, the optimized CoMFA I model should be applicable to the prediction of the fungicidal activities against gray mold.

Machine learning based anti-cancer drug response prediction and search for predictor genes using cancer cell line gene expression

  • Qiu, Kexin;Lee, JoongHo;Kim, HanByeol;Yoon, Seokhyun;Kang, Keunsoo
    • Genomics & Informatics
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    • v.19 no.1
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    • pp.10.1-10.7
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    • 2021
  • Although many models have been proposed to accurately predict the response of drugs in cell lines recent years, understanding the genome related to drug response is also the key for completing oncology precision medicine. In this paper, based on the cancer cell line gene expression and the drug response data, we established a reliable and accurate drug response prediction model and found predictor genes for some drugs of interest. To this end, we first performed pre-selection of genes based on the Pearson correlation coefficient and then used ElasticNet regression model for drug response prediction and fine gene selection. To find more reliable set of predictor genes, we performed regression twice for each drug, one with IC50 and the other with area under the curve (AUC) (or activity area). For the 12 drugs we tested, the predictive performance in terms of Pearson correlation coefficient exceeded 0.6 and the highest one was 17-AAG for which Pearson correlation coefficient was 0.811 for IC50 and 0.81 for AUC. We identify common predictor genes for IC50 and AUC, with which the performance was similar to those with genes separately found for IC50 and AUC, but with much smaller number of predictor genes. By using only common predictor genes, the highest performance was AZD6244 (0.8016 for IC50, 0.7945 for AUC) with 321 predictor genes.

Development of L-Threonine Producing Recombinant Escherichia coli using Metabolic Control Analysis (대사 조절 분석 기법을 이용한 L-Threonine 생산 재조합 대장균 개발)

  • Choi, Jong-Il;Park, Young-Hoon;Yang, Young-Lyeol
    • KSBB Journal
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    • v.22 no.1
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    • pp.62-65
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    • 2007
  • New strain development strategy using kinetic models and metabolic control analysis was investigated. In this study, previously reported mathematical models describing the enzyme kinetics of intracellular threonine synthesis were modified for mutant threonine producer Escherichia coli TF5015. Using the modified models, metabolic control analysis was carried out to identify the rate limiting step by evaluating the flux control coefficient on the overall threonine synthesis flux exerted by individual enzymatic reactions. The result suggested the production of threonine could be enhanced most efficiently by increasing aspartate semialdehyde dehydrogenase (asd) activity of this strain. Amplification of asd gene in recombinant strain TF5015 (pCL-$P_{aroF}$-asd) increased the threonine production up to 23%, which is much higher than 14% obtained by amplifying aspartate kinse (thrA), other gene in threonine biosynthesis pathway.

Relationship between Information Security Activities of Enterprise and Its Infringement : Mainly on the Effects of Information Security Awareness (기업의 정보보호 활동과 정보침해 사고 간의 관계: 정보보호 인식의 매개효과를 중심으로)

  • Moon, Kunwoong;Kim, Seungjoo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.27 no.4
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    • pp.897-912
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    • 2017
  • This paper focuses on how the protection of information security incident is effective in via Information security awareness when conducting information security activities of enterprises. Research models have theorized that the information security activity and the information security awareness will reduce the incidence of information security. The general characteristics of analysis targets have been carried out in the frequency analysis, and the reliability of the measuring tool has been utilized to calculate the coefficient of Cronbach's information protection. Evidence has been demonstrated regarding the relationship between information security activities and information security awareness and information security incidents.

Hologram Based QSAR Analysis of Caspase-3 Inhibitors

  • Sathya., B
    • Journal of Integrative Natural Science
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    • v.11 no.2
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    • pp.93-100
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    • 2018
  • Caspases, a family of cysteinyl aspartate-specific proteases plays a central role in the regulation and the execution of apoptotic cell death. Caspase-3 has been proven to be an effective target for reducing the amount of cellular and tissue damage because the activation of caspases-3 stimulates a signalling pathway that ultimately leads to the death of the cell. In this study, Hologram based Quantitative Structure Activity Relationship (HQSAR) models was generated on a series of Caspase-3 inhibitors named 3, 4-dihydropyrimidoindolones derivatives. The best HQSAR model was obtained using atoms, bonds, and hydrogen atoms (A/B/H) as fragment distinction parameter using hologram length 61 and 3 components with fragment size of minimum 5 and maximum 8. Significant cross-validated correlation coefficient ($q^2=0.684$) and non cross-validated correlation coefficients ($r^2=0.754$) were obtained. The model was then used to evaluate the eight external test compounds and its $r^2_{pred}$ was found to be 0.559. Contribution map show that presence of pyrrolidine sulfonamide ring and its bulkier substituent's makes big contributions for improving the biological activities of the compounds.

Thermal managing effects by cooling channels on performance of a PEMFC (냉각채널 열관리에 따른 고분자연료전지의 성능영향 연구)

  • Sohn, Young-Jun;Kim, Min-Jin;Park, Gu-Gon;Kim, Kyoung-Youn;Lee, Won-Yong
    • 한국신재생에너지학회:학술대회논문집
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    • 2009.06a
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    • pp.373-373
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    • 2009
  • Relative humidity, membrane conductivity and water activity are critical parameters of polymer electrolyte membrane fuel cells (PEMFC) for high performance and reliability. These parameters are closely related with temperature. Moreover, the ideal values of these parameters are not always identical along the channels. Therefore, the cooling channel design and its operating condition should be well optimized along the all location of the channels. In the present study, we have performed a numerical investigation on the effects of cooling channels on performance of a PEMFC. Three-dimensional Navier-Stokes equations are solved with the energy equation including heat generated by the electrochemical reactions in the fuel cell. The present numerical model includes the gas diffusion layers (GDL) and serpentine channels for both anode and cathode gas flows, as well as cooling channels. To accurately predict the water transport across the membrane, the distribution of water content in the membrane is calculated by solving a nonlinear differential equation with a nonlinear coefficient, i.e., the water diffusivity which is a function of water content as well as temperature. Main emphasis is placed on the heat transfer between the solid bipolar plate and coolant flow. The present results show that local current density is affected by cooling channels due to the change of the oxygen concentration and the membrane conductivity as well as the water content. It is also found that the relative humidity is influenced by the generated water and the gas temperature and thus it affects the distribution of fuel concentration and the conductivity of the membrane, ultimately fuel cell performance. Unit-cell experiments are also carried out to validate the numerical models. The performance curves between the models and experiments show reasonable results.

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