In order to study the effect of drought stress on morphophysiologic characteristics, yield and yield components of 8 new hybrids of corn (Zea maize L.) and KSC704 commercial hybrid as control resistant to drought and warm (which were bred and screened in Khozestan province condition), an experiment was conducted in a Randomized Complete Block Design (RCBD) with three replications under drought stress and normal irrigation at Khorasan-Razavi Agriculture Research Center, Mashhad, Iran on June 10, 2011. The results of analyze variance showed that under normal irrigation and drought condition, there was a significant difference (p<0.01) between the hybrids. Mean comparison of hybrids revealed that in normal irrigation H6 and in drought stress H8 hybrid had the maximum grain yield (12.85 and 6.75 ton/ha, respectively). Based on the grain yields of studied hybrids, stress tolerance index (STI), stress susceptibility index (SSI), tolerance index (TOI), mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HM) and golden mean (GM) were estimated. Results showed that among drought tolerance indices, MP, GMP, STI and HM were the best indices for corn and KSC704 hybrid and H4 had the highest tolerance to drought in Mashhad weather condition.

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In this study, poly ethyleneimine (PEI)/Titania (TiO 2 ) multilayer film on quartz tubes have been successfully fabricated via a layer-by-layer (LbL) self-assembly method. Scanning electron microscopy (SEM) and Brunauer-Emmett-Teller (BET) surface area analysis were carried out for characterization of the layers on quartz tube. The SEM pictures showed that the film surface is smooth and uniform. The BET characterization verified the formation of multilayer thin film. The photocatalytic activity of the PEI/TiO 2 multilayer deposited on the quartz tubes was evaluated in the treatment of raw petroleum refinery wastewater (PRW) under UV light irradiation in three annular photocatalytic reactors. This study examined the impact of initial chemical oxygen demand (COD) concentration, H 2 O 2 concentration, pH and reaction time on the PRW treatment and the results were used to generate both a response surface methodology (RSM) model and an artificial neural network (ANN) model. Maximum COD removal (98 %) was achieved at the optimum conditions (initial COD concentration of 300 mg/l, hydrogen peroxide concentration of 8.8 mM, pH of 5 and reaction time of 120 min). A comparison between the model results and experimental data gave a high correlation coefficient (R ANN 2 = 0.9632, R RSM 2 = 0.943) and showed that two models were able to predict COD removal from PRW by PEI/TiO 2 /UV process. However, ANN model was superior to RSM model with higher value of coefficient of determination (0.9632 ANN [ 0.94 RSM ) and the lower root mean square error (RMSE) (3.377 AAN \ 3.569 RSM ). The average percentage error for ANN and RSM models was 0.18 and 0.73, respectively, indicating the superiority of ANN in capturing the nonlinear behavior of the system. It was clear that the best networks were able to predict the experimental responses more accurately than the multiple regression analysis.