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Articles by A. Shafiee
Total Records ( 3 ) for A. Shafiee
  H.R. Sadeghipour Roodsari , M. Amini , Z. Naghibi Harat , P. Daneshgar , M. Vosooghi and A. Shafiee
  In the present study, the activity of seven newly synthesized dihydropyridine analogues on the motility of sperm were determined and compared to nifedipine activity that was used as standard. Sperm motility reduced value for test compounds 6a-g shows a gradual increase proportional to the size elongation of alkyl ester groups. Consequently the size of alkyl is important in the activity of test compounds and finally increase in the lipophil size of hydrocarbon`s ester (R1) is inversely related to the activity of the synthetic compounds. As a result, the methyl ester of the test compounds with 50% of nifedipine activity (in two hours group) is the most active test compound.
  A. Shafiee , H.R. Tavakoli and M.K. Jafari
  This study describes an experimental study on compacted sand-clay mixtures to investigate pre-failure and failure characteristics of such mixtures under monotonic compression and extension loading paths. Results reveal that pore pressure, secant modulus, undrained shear strength and angle of shearing resistance increase when sand content was raised in both compression and extension. It was also found that the tested materials were overconsolidated by the fact that normalized shear strength depends on initial confining stress. The compacted sand-clay mixtures exhibit anisotropy in mechanical behavior so that undrained shear strength and angle of shearing resistance were greater in compression than in extension. The extent of the anisotropy increases with sand content.
  A. Shafiee and R. Ghate
  An extensive test program was conducted on kaolin-gravel and kaolin-sand mixtures to evaluate shear modulus, damping ratio and pore pressure of the mixtures. Test results reveal that shear modulus increases with aggregate content and confining stress and decreases with shear strain amplitude and loading cycles. Meanwhile, damping ratio depends mainly on aggregate content and shear strain amplitude and is less affected by loading cycles. Pore pressure also plays an important role in aggregate-kaolin mixtures and increases with aggregate content. An attempt has also been made to implement Artificial Neural Networks (ANNs) for modeling shear modulus, damping ratio and pore pressure build-up in the mixtures. The study indicates that ANNs can successfully model the complex relationship between cyclic deformation properties and input parameters including current state of stress, aggregate content, shear strain amplitude, confining stress, aggregate size and loading cycles.
 
 
 
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