• 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.

• Proceedings of the SCSK Conference
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• 2003.09a
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• pp.225-231
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• 2003

To search and development a new material with superior melanogenesis inhibitory activity, the bioactivities (obs. pl$_{50}$) of alkyl-3,4-dihydroxybenzoyl esters and N-alkyl-3,4-dihydroxybenz-oyl amides as substrate molecules were measured in mouse melanoma cells. And also, we have studied that 3-D QSARs (3 dimensional Quantitative Structure-Activity Relationships) between molecular interaction field of substrates and the bioactivities were analyzed using CoMFA (Comparative Molecular Field Analyses) method. When cross-validation value (q$^2$) is 0.68 at 3 components, the Pearson correlation coefficient ($r^2$) is 0.900. From the basis on the findings, the model was appeared by the contour map such as steric field and electrostatic field relationships between quantitative structure and the bioactivity of the various substrate derivatives. Measured bioactivities (obs. pl$_{50}$) of unknown compounds are very similar to predicted activity (pred. pl$_{50}$) according to the CoMFA model. As the results of prediction, we could conclude that the bioactivities were increased by creation of R$_1$ substitution of 5,5-dime-thylhexoxy, 6,6-dimethylheptyl, 1-amino-6,6-dimethylheptyl group etc and R$_2$ substitution of hydroxy, methyl, methoxy group etc.p etc.

• Bulletin of the Korean Chemical Society
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• v.25 no.10
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• pp.1513-1520
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• 2004

We investigate a series of synthesized ${\beta}$-methoxyacrylate analogues for their 3D QSAR & HQSAR against Magnaporthe grisea (Rice Blast Disease). We perform the three-dimensional Quantitative Structure-Activity Relationship (3D-QSAR) studies, using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) procedure. In addition, we carry out a two-dimensional Quantitative Structure-Activity Relationship (2D-QSAR) study, using the Hologram QSAR (HQSAR). We perform these studies, using 53 compounds as a training set and 10 compounds as a test set. The predictive QSAR models have conventional $r^2$ values of 0.955 at CoMFA, 0.917 at CoMSIA, and 0.910 at HQSAR respectively; similarly, we obtain cross-validated coefficient $q^2$ values of 0.822 at CoMFA, 0.763 at CoMSIA, and 0.816 at HQSAR, respectively. From these studies, the CoMFA model performs better than the CoMSIA model.

• Journal of the Korean Society of Safety
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• v.16 no.4
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• pp.103-108
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• 2001

Explosive limit is one of the major physical properties used to determine the fire and explosion hazards of the flammable substances. Explosive limits are used to classify flammable liquids according to their relative flammability. Such a classification is important for the safe handling of flammable liquids which constitute the solvent mixtures. Explosive limits of all compounds and solvent mixtures can be calculated with the appropriate use of the fundamental laws of Raoult, Dalton, Le Chatelier and activity coefficient models. In this paper, Raoult,s law and van Laar equation(activity coefficient model) are shown to be applicable for the prediction of the explosive limits in the flammable ethylacetate-toluene system. The values calculated by the proposed equations were a good agreement with literature data within a given percent. From a given results, by the use of the proposed equations, it is possible to predict explosive limits of the other flammable mixtures. It is hoped eventually that this method will permit the estimation of the explosive Properties of flammable mixtures with improved accuracy and the broader application for other flammable stances.

• Journal of the Korean Institute of Gas
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• v.13 no.5
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• pp.20-25
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• 2009

Low explosion limits of flammable liquid mixtures can be calculated with the appropriate use of the fundamental laws of Raoult, Dalton, Le Chatelier and activity coefficient models. In this paper, Raoult's law, van Laar equation and Wilson equation are shown to be applicable for the prediction of the lower explosion limits for ethylacetate+ethanol and ethanol+toluene systems. The calculated values based on Raoult's law were found to be better than those based on van Laar and Wilson equations.

• Journal of the Korean Society of Safety
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• v.30 no.4
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• pp.86-91
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• 2015

The flash point is used to categorize inflammable liquids according to their relative flammability. Such a categorization is important for the safe handling, storage, and transportation of inflammable liquids. The flash point temperature of two binary liquid mixtures(n-octane+n-decane and n-octane+n-dodecane) has been measured for the entire concentration range using Seta-flash closed cup tester based on the ASTM D3278 method. The closed cup flash point temperature was estimated using the UNIFAC(Universal Functional Activity Coefficient) group contribution model. The experimentally derived flash point was also compared with the predicted flash point from the UNIFAC model. The UNIFAC model is able to estimate the flash point fairly well for n-octane+n-decane mixture and n-octane+n-dodecane mixture.

• Korean Journal of Exercise Nutrition
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• v.24 no.1
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• pp.9-13
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• 2020

[Purpose] This preliminary study aimed to develop a regression model to estimate the resting metabolic rate (RMR) of young and middle-aged Koreans using various easy-to-measure dependent variables. [Methods] The RMR and the dependent variables for its estimation (e.g. age, height, body mass index, fat-free mass; FFM, fat mass, % body fat, systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulse pressure, and resting heart rate) were measured in 53 young (male n = 18, female n = 16) and middle-aged (male n = 5, female n = 14) healthy adults. Statistical analysis was performed to develop an RMR estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and age were important variables in both the regression models based on the regression coefficients. Mean explanatory power of RMR₁ regression models estimated only by FFM was 66.7% (R²) and 66.0% (adjusted R²), while mean standard errors of estimates (SEE) was 219.85 kcal/day. Additionally, mean explanatory power of RMR₂ regression models developed by FFM and age were 70.0% (R²) and 68.8% (adjusted R²), while the mean SEE was 210.64 kcal/day. There was no significant difference between the measured RMR by the canopy method using a metabolic gas analyzer and the predicted RMR by RMR₁ and RMR₂ equations. [Conclusion] This preliminary study developed a regression model to estimate the RMR of young and middle-age healthy Koreans. The regression model was as follows: RMR₁ = 24.383 × FFM + 634.310, RMR₂ = 23.691 × FFM - 5.745 × age + 852.341.

• Food Science and Biotechnology
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• v.16 no.1
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• pp.154-158
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• 2007

Adsorption isotherms for chaga mushroom powder as influenced by particle size were investigated using a gravimetric technique. Samples were equilibrated in desiccators containing sulfuric acid solutions of known water activity (0.11-0.93), then placed in temperature-controlled chambers for approximately ten days. Equilibrium moisture content (EMC) of chaga mushroom powder increased with water activity in all samples. EMC was slightly greater in the samples comprised of smaller particle size, however there was no marked difference in appearance between the three samples. The chaga mushroom powder exhibited Type II behavior. When the BET model was used to determine mean monolayer values, 0.077, 0.077, and 0.070 $H_2O/dry$ solid was observed for <250, 250-425, and $425-850\;{\mu}m$ sized samples, respectively, however mean monolayer values were 0.121, 0.111, and 0.101 $H_2O/dry$ solid, respectively, when the GAB model was used. The experimental EMC values were related to the computed values from Henderson's model. The coefficient of determination and standard error for the linear regression were 0.997 and 0.003, respectively.

• Korean Journal of Agricultural Science
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• v.35 no.1
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• pp.33-40
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• 2008

The structural characteristics that influence on the fungicidal activities of N-phenylbenzenesulfonamide (1~24) and N-phenyltheinylsulfonamide (25~30) derivatives against Dampping-off (Pythium ultimum) were discussed quantitatively using the models of molecular holographic quantitative structure-activity relationships (HQSAR). From the based on these findings, the statistical results of the optimized HQSAR F-3 model showed better predictablity ($r^2_{cv.}$ or $q^2=0.581$) and correlation coefficient ($r^2_{ncv.}=0.963$). And, from the analytical results of the atomic contribution maps on the fungicidal activities, the most active compound is $R_1=2-fluoro-4-chloro$ substituent (4) and the most inactive one is $R_1=4-methoxy$ substituent (20). It was found that the 2-fluoro-4-chlorophenyl group as a $R_1$-group was an important structure and a characteristic factor not only for herbicidal activity but also for fungicidal activity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.260-268
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• 2016

The objective of this study was to investigate the relationship among the variables and effects of depression and physical activity on fatigue in the elderly with chronic disease. A descriptive research design was employed in this study. In total, 500 elderly patients diagnosed with chronic disease were selected from 3 medical centers for the study. The measurements were used to examine their general characteristics, fatigue, depression, and physical activity. To analyze the data, statistical analyses, including ANOVA, t-test, Scheffe's test, Pearson's correlation coefficient, and hierarchical regression analysis, were conducted for the analysis of the data. The results indicated that the age, gender, and educational level in the first step model explained 6% of the effect on fatigue among the elderly with chronic disease. In addition, depression and physical activity in the second step model explained 16% of the effect on fatigue. These findings demonstrate the significance of (considering) depression and physical activity related to care plans when developing health-programs for decreasing fatigue and planning intervention strategies.