• International Journal of Safety
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• v.10 no.1
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• pp.5-9
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• 2011

Two popular activity coefficient models, Wilson and NRTL equations have been used to correlate the published flash point data on the n-propanol + propionic acid and n-butanol + propionic acid systems through the optimization method. The results of these correlation were compared with the results calculated by Raoult's law. The optimization method were found to be better than those based on the Raoult's law. The optimization method based on the Wilson equation described the published data more effectively than was the case when the optimization method was based upon the NRTL equation.

• Journal of Industrial Technology
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• v.20 no.A
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• pp.185-194
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• 2000

In this work we measured the total pressure of the aqueous solutions and the methanol-water solutions dissolved with inorganic salts, at $25^{\circ}C$. In organic electrolytes used in this work were $K_2SO_4$ and $(NH_4)_2SO_4$. Using the measured vapour pressures the activity coefficient of solvents and the mean ionic activity coefficient were obtained through thermodynamic relations. The activity coefficients of solvent and the mean ionic activity coefficirnt obtained in this work were fitted with Macedo's model and Acard's model. Both two models were good agreeable to the vapor pressure and the mean ionic activity coefficient for the electroyte aqueous solutions. For electrolyte /methanol/water solutions, Macedo's model had much deviation from experimental data, while Acard's model showed a good agreement with experimental data.

• Bulletin of the Korean Chemical Society
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• v.34 no.6
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• pp.1823-1828
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• 2013

Tetraoxanes (1,2,4,5-tetraoxanes) have been reported to exhibit potent antimalarial activity. In the present study, the three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on a series of tetraoxanes derivatives using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The best predictive CoMFA model with atom fit alignment resulted in cross-validated coefficient ($q^2$) value of 0.719, non-cross-validated coefficient ($r^2$) value of 0.855 with standard error of estimate (SEE) 0.335. Similarly, the best predictive CoMSIA model was derived with $q^2$ of 0.739, $r^2$ of 0.847 and SEE of 0.344. The generated models were externally validated using test sets. The final QSAR models as well as the information gathered from 3D contour maps should be useful for the design of novel tetraoxanes having improved antimalarial activity.

• Fire Science and Engineering
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• v.31 no.3
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• pp.19-24
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• 2017

Flammable substances are used in laboratories and industrial process. The flash point (FP) is one of the most important physical properties used to determine the potential for characterizing the fire and explosion hazard of liquids. The FP data at 101.3 kPa were measured for the binary systems {toluene+ethylbenzene}, {methlycyclohenxane+ethylbenzene} and {n-heptane+ ethylbenzene}. The experiments were performed according to the standard test method (ASTM D 3278) using a SETA closed cup flash point tester. The measured FPs were compared with the values predicted using the following activity coefficient models: Wilson, Non-Random Two Liquid (NRTL), and UNIversal QUAsiChemical (UNIQUAC). The average absolute deviation between the predicted and measured lower FP was less than 1.74 K.

• Fire Science and Engineering
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• v.29 no.5
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• pp.1-6
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• 2015

Flash point is one of the most important variables used to characterize fire and explosion hazard of liquids. The lower flash point data were measured for the binary systems {methanol + 1-butanol}, {ethanol + 1-butanol} and {2-propanol + 1-butanol} at 101.3 kPa. Experiments were performed according to the standard test method (ASTM D 3278) using a SETA closed cup flash point tester. The measured flash points were compared with the predicted values calculated using the following activity coefficient models: Wilson, Non-Random Two Liquid (NRTL), and UNIversal QUAsiChemical (UNIQUAC). The measured FP data agreed well with the predicted values of Raoult's law, Wilson, NRTL and UNIQUAC models. The average absolute deviation between the predicted and measured lower FP was less than 1.14 K.

• Bulletin of the Korean Chemical Society
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• v.32 no.5
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• pp.1604-1612
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• 2011

We developed three-dimensional quantitative structure activity relationship (3D-QASR) models for 17 adamantyl derivatives as P-glycoprotein (P-gp) inhibitors. Eighteen different partial charge calculation methods were tested to check the feasibility of the 3D-QSAR models. Best predictive comparative molecular field analysis (CoMFA) model was obtained with the Austin Model 1-Bond Charge Correction (AM1-BCC) atomic charge. The 3D-QSAR models were derived with CoMFA and comparative molecular similarity indices analysis (CoMSIA). The final CoMFA model ($q^2$ = 0.764, $r^2$ = 0.988) was calculated with an AM1-BCC charge and electrostatic parameter, whereas the CoMSIA model ($q^2$ = 0.655, $r^2$ = 0.964) was derived with an AM1-BCC charge and combined steric, electrostatic, hydrophobic and HB-acceptor parameters. Leave-five-out (LFO) cross-validation was also performed, which yielded good correlation coefficient for both CoMFA (0.801) and CoMSIA (0.656) models. Robustness of the developed models was checked further with 1000 run bootstrapping analyses, which gave an acceptable correlation coefficient for CoMFA (BS-$r^2$ = 0.997, BS-SD = 0.003) and CoMSIA (BS-$r^2$ = 0.996, BS-SD = 0.018).

• Journal of Integrative Natural Science
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• v.8 no.1
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• pp.40-47
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• 2015

Glycogen synthase kinase 3 (GSK-3) is a serine/threonine protein kinase that has recently emerged as a promising target in drug discovery. It is involved in multiple cellular processes and associated with the pathogenesis of several diseases. A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was performed on a series of GSK-3 inhibitors to understand the structural basis for inhibitory activity. Comparative molecular field analysis (CoMFA) method was used to derive 3D-QSAR models. A reliable CoMFA model was developed using ligand-based alignment scheme. The model produced statistically acceptable results with a cross-validated correlation coefficient ($q^2$) of 0.594 and a non-cross-validated correlation coefficient ($r^2$) of 0.943. Robustness of the model was checked by bootstrapping and progressive scrambling analysis. This study could assist in the design of novel compounds with enhanced GSK-3 inhibitory activity.

• Journal of Integrative Natural Science
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• v.8 no.4
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• pp.258-266
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• 2015

Xanthine Oxidase is an enzyme, which oxidizes hypoxanthine to xanthine, and xanthine to uric acid. It is widely distributed throughout various organs including the liver, gut, lung, kidney, heart, brain and plasma. It is involved in gout pathogenesis. In this study, we have performed Comparative Molecular Field Analysis (CoMFA) on a series of 2-(indol-5-yl) thiazole derivatives as xanthine oxidase (XO) inhibitors to identify the structural variations with their inhibitory activities. Ligand based CoMFA models were generated based on atom-by-atom matching alignment. In atom-by-atom matching, the bioactive conformation of highly active molecule 11 was generated using systematic search. Compounds were aligned using the bioactive conformation and it is used for model generation. Different CoMFA models were generated using different alignments and the best model yielded a cross-validated $q^2$ of 0.698 with five components and non-cross-validated correlation coefficient ($r^2$) of 0.992 with Fisher value as 236.431, and an estimated standard error of 0.068. The predictive ability of the best CoMFA models was found to be $r^2_{pred}$0.653. The CoMFA study revealed that the $R_3$ position of the structure is important in influencing the biological activity of the inhibitors. Electro positive groups and bulkier substituents in this position enhance the biological activity.

• International Union of Geodesy and Geophysics Korean Journal of Geophysical Research
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• v.23 no.1
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• pp.1-11
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• 1995

Thermospheric neutral winds and temperatures have been collected from the ground-based Fabry-Perot interferometer (FPI) at Thule Air Base ($76.5^{\circ}N{\;}69.0^{\circ}W$), Greenland since 1985. The thermospheric observations are obtained by determining the Doppler characteristics f the [OI] 6300 ${\AA}$ emissions of atomic oxygen. The FPI operates routinely during the winter season, with a limitation in the observation by the existence of clouds. For this study, data acquired from 1985 to 1991 were analyzed. The neutral wind measurements from these long-term measurements are used to investigate the influence of solar cycle variation on the high-latitude thermospheric dynamics. These data provide experimental results of the geomagnetic polar cap are also compared with the predictions of two semiempirical models : the vector spherical harmonics (VSH) model of Killeen et al. (1987) and the horizontal wind model (HWM) of Hedin et al. (1991). The experimental results show a good positive correlation between solar activity and thermospheric wind speed over the geomagnetic polar cap. The calculated correlation coefficient indicates that an increase of 100 in F10.7 index corresponds to an increase in wind speed of about 100 m/s. The model predictions reveal similar trends of wind speed variation as a function of solar activity, with the VSH and HWM models tending to overestimate and underestimate the wind speed, respectively.

• Computers and Concrete
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• v.31 no.2
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• pp.85-95
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• 2023

Natural pozzolans are used as additives in cement to develop more durable and high-performance concrete. Pozzolanic activity index (PAI) is important for assessing the performance of a pozzolan as a binding material and has an important effect on the compressive strength, permeability, and chemical durability of concrete mixtures. However, the determining of the 28 days (short term) and 90 days (long term) PAI of concrete mixtures is a time-consuming process. In this study, to reduce extensive experimental work, it is aimed to predict the short term and long term PAIs as a function of the chemical compositions of various natural pozzolans. For this purpose, the chemical compositions of various natural pozzolans from Central Anatolia were determined with X-ray fluorescence spectroscopy. The mortar samples were prepared with the natural pozzolans and then, the short term and the long term PAIs were calculated based on compressive strength method. The effect of the natural pozzolans' chemical compositions on the short term and the long term PAIs were evaluated and the PAIs were predicted by using multiple linear regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) model. The prediction model results show that both reactive SiO₂ and SiO₂+Al₂O₃+Fe₂O₃ contents are the most effective parameters on PAI. According to the performance of prediction models determined with metrics such as root mean squared error (RMSE) and coefficient of correlation (R²), ANFIS models are more feasible than the multiple regression model in predicting the 28 days and 90 days pozzolanic activity. Estimation of PAIs based on the chemical component of natural pozzolana with high-performance prediction models is going to make an important contribution to material engineering applications in terms of selection of favorable natural pozzolana and saving time from tedious test processes.