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We have added expanded vermiculite and polypropylene fibers with low thermal conductivity to lightweight gypsum. Thermal conductivity of the composites decreases on addition of vermiculite as pore-maker. Physical and mechanical properties of the composites are improved by incorporating polypropylene fibers. A nonlinear finite element model of a three point bending model and a design of experiments analysis have been developed to evaluate and optimize the additive concentrations and also to understand the effects provided by the additives on the mechanical strength. Statistical response surface method with three-level factorial was employed to evaluate the effect of addition of vermiculite and polypropylene fibers on gypsum composites. Our methodology can be applied to other nonlinear materials for property optimization.

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a b s t r a c tThe objective of this study is to build a regression model of air quality by using the support vector machine (SVM) technique in the Avilés urban area (Spain) at local scale. Hazardous air pollutants or toxic air contaminants refer to any substance that may cause or contribute to an increase in mortality or serious illness, or that may pose a present or potential hazard to human health. To accomplish the objective of this study, the experimental data of nitrogen oxides (NO x ), carbon monoxide (CO), sulphur dioxide (SO 2 ), ozone (O 3 ) and dust (PM 10 ) for the years 2006-2008 are used to create a highly nonlinear model of the air quality in the Avilés urban nucleus (Spain) based on SVM techniques. One aim of this model is to obtain a preliminary estimate of the dependence between primary and secondary pollutants in the Avilés urban area at local scale. A second aim is to determine the factors with the greatest bearing on air quality with a view to proposing health and lifestyle improvements. The United States National Ambient Air Quality Standards (NAAQS) establishes the limit values of the main pollutants in the atmosphere in order to ensure the health of healthy people. They are known as criteria pollutants. This support vector regression model captures the main insight of statistical learning theory in order to obtain a good prediction of the dependence among the main pollutants in the Avilés urban area. Finally, on the basis of these numerical calculations, using the support vector regression (SVR) technique, conclusions of this work are drawn.