Islamic Azad University North Tehran Branch

About: Islamic Azad University North Tehran Branch is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Adsorption & Catalysis. The organization has 868 authors who have published 968 publications receiving 9987 citations.

Optimization of sonophotocatalytic decolorization of Begazol Black B by loaded, double-sided nanophotocatalysts on porous substrate: A central composite design approach

Abstract: In this study, sonophotocatalytic decolorization of Begazol Black B by double-sided, sonoloaded nanophotocatalysts (nphs) on 3D porous substrate (3D-PS) was reported for the first time. Sonoloading is a facile fabrication route that allows two-sided loading of nphs on 3D-PS. Morphology of the 3D-PS and the presence of the nphs were studied using field emission scanning electron microscopy and energy dispersive X-ray spectroscopy, respectively. Moreover, the durability of the nphs on the 3D-PS was studied using X-ray fluorescence. The central composite design based on response surface methodology was employed to find the maximum yield of sonophotocatalytic decolorization and optimize the process variables (initial BBB concentration, initial H2O2 concentration, pH and ultrasonication time). Complete decolorization was achieved at only 40 min treatment under the optimum conditions. Moreover, sonoloaded nphs on 3D-PS exhibited 93% durability after 50 h sonophotocatalytic decolorization. The anticipated values of the decolorization efficiency showed excellent agreement with the experimental values (R2 = 0.9823, Adj-R2 = 0.9657). Furthermore, the kinetic analysis demonstrated that the sonophotocatalytic decolorization followed the Langmuir-Hinshelwood kinetic model. Finally, a comparative study between sonocatalytic, photocatalytic and sonophotocatalytic processes was conducted at the optimum condition. The results revealed that sonophotocatalytic process can markedly enhance the decolorization efficiency compared to sonocatalytic and photocatalytic methods due to the enhanced reactive radical generation.

Comparison of the Volatile Oils of Satureja atropatana Bung. and Satureja mutica Fisch. et C.A. Mey. from Iran

Abstract: The oil obtained by hydrodistillation of the aerial parts of Satureja atropatana Bung., endemic in Iran, and S. mutica Fisch. et C.A. Mey. was analyzed by GC/MS. Thirty-seven compounds representing 99.3% of the oil of S. atropanata were identified, among them carvone (21.5%), menthol (18.1%), 1,8-cineol (13.1%), methyl chavicol (11.1%) and menthone (10.5%) being the major ones. The oil of S. mutica was characterized by higher amount of menthol (37.4%), menthone (17.2%) and 1,8-cineol (9.3%) among the 39 components comprising 95.1% of the total oil detected. Both oils were richer in oxygenated monoterpenes than sesquiterpenes.

Volatile Oils of Ferulago phialocarpa Rech. f. et H. Reidl. and Leutea elbursensis Mozaffarian from Iran

Abstract: The water distilled oils from the aerial parts of Ferulago phialocarpa Rech. f. et H. Riedl. and the aerial parts of Leutea elbursensis Mozaffarian (Umbelliferae), which are endemic to Iran, were analyzed by GC/MS. α-Pinene (40.9%), α-phellandrene (14.2%) and β-phellandrene (9.6%) were the main components among the 26 constituents characterized in the oil of Ferulago phialocarpa, representing 93.8% of the total components detected. Thirty-three compounds were identified in the oil of L. albursensis, representing 98.0% of the total oil, with α-pinene (37.3%) and β-pinene (36.1%) as main constituents. Both oils were richer in monoterpene, rather than sesquiterpene, hydrocarbons.

Template Matching Advances and Applications in Image Analysis

Abstract: In most computer vision and image analysis problems, it is necessary to define a similarity measure between two or more different objects or images. Template matching is a classic and fundamental method used to score similarities between objects using certain mathematical algorithms. In this paper, we reviewed the basic concept of matching, as well as advances in template matching and applications such as invariant features or novel applications in medical image analysis. Additionally, deformable models and templates originating from classic template matching were discussed. These models have broad applications in image registration, and they are a fundamental aspect of novel machine vision or deep learning algorithms, such as convolutional neural networks (CNN), which perform shift and scale invariant functions followed by classification. In general, although template matching methods have restrictions which limit their application, they are recommended for use with other object recognition methods as pre- or post-processing steps. Combining a template matching technique such as normalized cross-correlation or dice coefficient with a robust decision-making algorithm yields a significant improvement in the accuracy rate for object detection and recognition.