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Zn(BH4)2 (0.5-2 mmol) in the presence of Al2O3 (1 mmol) reduces varieties of organic carbonyl compounds such as aldehydes, ketones, acyloins, α-diketones and α, β-unsaturated carbonyl compounds to their corresponding alcohols. Reduction reactions were carried out in THF at room temperature in high to excellent yields of products. The chemoselective reduction of aldehydes over ketones was accomplished successfully with this reducing system. In addition, regioselectivity and exclusive 1,2-reduction of conjugated carbonyl compounds to their corresponding allylic alcohols in high to excellent yields was accomplished successfully with this reducing system

The oximation of a variety of carbonyl compounds was efficiently carried out with DOWEX(R)50WX4/ NH 2 OH·HCl system. The reactions were performed in ethanol to give Z-aldoximation isomers of aldehydes and E-oximaton of acetophenone derivatives in a perfect selectively. The oximation of compounds with two carbonyl groups was carried out selectively on one carbonyl moiety. Also, the oximation of aldehydes over ketones has been accomplished successfully by this system.

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This paper presents the application of feed forward and cascade forward neural networks to model the non-linear behavior of pistachio nut, squash and cantaloupe seeds during drying process. The performance of the feed forward and cascade forward ANNs was compared with those of nonlinear and linear regression models using statistical indices, namely mean square error ($MSE$), mean absolute error ($MAE$), standard deviation of mean absolute error (SDMAE) and the correlation coefficient (${R^2}$). The best neural network feed forward back-propagation topology for the prediction of effective moisture diffusivity and energy consumption were 3-3-4-2 with the training algorithm of Levenberg-Marquardt (LM). This structure is capable to predict effective moisture diffusivity and specific energy consumption with${R^2}$= 0.9677 and 0.9716, respectively and mean-square error ($MSE$) of 0.00014. Also the highest${R^2}$values to predict the drying rate and moisture ratio were 0.9872 and 0.9944 respectively.