The dependency of uniform corrosion of structural steel on the average grain Size (D) should be quantified for design purposes. In the present work, a spectrum of grain Sizes was obtained by simple heat treatment routes in st37 structural steel. It was revealed that the corrosion current density (icorr) increased by grain refinement, which was related to the increased density of grain boundaries. The data on the plots of hardness and icorr versus 1/√ D √ were successfully fitted by a straight line and an exponential function, respectively. Therefore, the mechanical response was rationalized by a Hall-Petch type relationship with a slope of 237. 8 MPa/μ m0. 5. Moreover, the obtained simple relationship between icorr and 1/√ D √ can be used for prediction of the dependency of uniform corrosion on the average grain Size.

Nanocrystalline materials show a higher strain-rate sensitivity in contrast to the conventional coarse-grained materials and a different grain Size dependency. To explain these phenomenon, a finite element model is constructed that considers both grain interior and grain boundary deformation of nanocrystalline materials. The model consist of several crystalline cores with different orientations and grain boundary phase. The nonlinear behavior of the nanocrystalline core is implemented by a grain Size dependent crystal plasticity. The boundary phase is assumed to have the mechanical properties of quasi-amorphous material. The constitutive equations for both grains interior and boundary phase are implemented into the finiteelement software Abaqus. A calibration procedure was used to tune some parameters of the model with the previously published experimental data on the nanocrystalline copper. Then the model is used to predict the material behavior in various strain rates and grain Sizes. The stresses obtained from these simulations match well with the experimental data for nanocrystalline copper at different strains and strain rates. Deviation from the Hall-Petch law and inverse Hall-Petch effect are also well illustrated by the model.

In the present work, a computer-based method is proposed to investigate the relationship between the steady-state grain Size (ds) and stacking fault energy (SFE) in severely plastic deformed (SPDed) materials. The stacking fault energy, γ, , plays an important role in determining the mechanical properties of face-centered cubic (fcc) metals. A number of models have been proposed to show this role. These models have several shortcomings, including complex computational variables, data constraints and small computational range constraints. The present model compatible with experimental results does not employ hard calculable variables. Besides, it is applicable not only for pure metals but also for alloys. The squared regression (R2) and error sum of squares (SSE) for the training and testing data of the presented model are 0. 93, 0. 0006 and 0. 98, 0. 00018, respectively, which indicates the high accuracy of the proposed model. The slope of the log Gb ,versus log s d b is about 0. 6453 which is comparable to all the models offered in this field.

Methamphetamine use and dependency is a serious public health problem with implications across multiple areas from societal impact to burden on psychiatric and medical resources. Different areas such as East and Southeast Asia, Australia, Middle West and Western areas of United States and some regions of Great Britain are suffering from Methamphetamine use and related problems. An estimated 8% of admissions to substance abuse treatment programs are associated to stimulants with Methamphetamine misuse. The comparison of demographic characteristics and variety of substances in Methadone maintenance clinic of Baharan Psychiatry Hospital in Zahrdan, Iran in 2009-2011, has reported an increasing proceeding of methamphetamine use from 6% to about 20%. The Administrator of Health and Social anti-drug campaign declared that the substance related psychotic symptoms are noticeable among Methamphetamine users, it has also been reported that 50% of patients of psychiatric wards consist of Methamphetamine users psychosis patients, which would bring a number of harmful demerits to this the wards.

I read with great interest the article entitled “, Comparative investigation of sleep problems in opioid-dependent and normal subjects”,by Madanifard et al. . . .

dependency parser is one of the most important fundamental tools in the natural language processing, which extracts the structure of sentences and determines the relations between words based on the grammar dependency. The dependency parser is proper for free-order languages such as Persian. In this work, data-driven dependency parser is developed with the help of phrase-structure parser for Persian. The defined feature space in each parser is one of the important factors involved in its success. Our goal is to generate and extract appropriate features to dependency parsing of Persian sentences. In order to achieve this goal, new semantic and syntactic features are defined and added to the MSTParser by the stacking method. Semantic features are obtained using word clustering algorithms based on syntagmatic analysis, and the syntactic features are obtained using the Persian phrase-structure parser, and are used as bit-string. Experiments are conducted on the Persian dependency Treebank (PerDT) and the Uppsala Persian dependency Treebank (UPDT). The results obtained indicate that the definition of new features improves the performance of the dependency parser for Persian. The achieved unlabeled attachment scores for PerDT and UPDT are 89. 17% and 88. 96%, respectively.