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Institution

Islamic Azad University

EducationTehran, Iran
About: Islamic Azad University is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Population & Adsorption. The organization has 83635 authors who have published 113437 publications receiving 1275049 citations. The organization is also known as: Azad University.


Papers
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Journal ArticleDOI
01 Jan 2012-Energy
TL;DR: In this paper, a multiobjective stochastic search algorithm based on 2m point estimated method is implemented to analyze the probabilistic wind-thermal economic emission dispatch problem considering both overestimation and underestimation of available wind power.

150 citations

Journal ArticleDOI
TL;DR: In this article, an acid functionalized multi-walled carbon nanotube (MWCNT) was modified by three hydrophilic polymers during an in situ polymerization reaction.

150 citations

Journal ArticleDOI
TL;DR: This is the first study in which the microstructural properties of a macromolecule are examined in a deep eutectic solvent and it was found that urea molecules denature the enzyme by interrupting the intra-chain hydrogen bonds in a "direct denaturation mechanism".
Abstract: Deep eutectic solvents (DESs) are utilized as green and inexpensive alternatives to classical ionic liquids. It has been known that some of DESs can be used as solvent in the enzymatic reactions to obtain very green chemical processes. DESs are quite poorly understood at the molecular level. Moreover, we do not know much about the enzyme microstructure in such systems. For example, how some hydrolase can remain active and stable in a deep eutectic solvent including 9 M of urea? In this study, the molecular dynamics of DESs as a liquid was simulated at the molecular level. Urea : choline chloride as a well-known eutectic mixture was chosen as a model DES. The behavior of the lipase as a biocatalyst was studied in this system. For comparison, the enzyme structure was also simulated in 8M urea. The thermal stability of the enzyme was also evaluated in DESs, water, and 8M urea. The enzyme showed very good conformational stability in the urea : choline chloride mixture with about 66% urea (9 M) even at high temperatures. The results are in good agreement with recent experimental observations. In contrast, complete enzyme denaturation occurred in 8M urea with only 12% urea in water. It was found that urea molecules denature the enzyme by interrupting the intra-chain hydrogen bonds in a “direct denaturation mechanism”. However, in a urea : choline chloride deep eutectic solvent, as a result of hydrogen bonding with choline and chloride ions, urea molecules have a low diffusion coefficient and cannot reach the protein domains. Interestingly, urea, choline, and chloride ions form hydrogen bonds with the surface residues of the enzyme which, instead of lipase denaturation, leads to greater enzyme stability. To the best of our knowledge, this is the first study in which the microstructural properties of a macromolecule are examined in a deep eutectic solvent.

150 citations

Journal ArticleDOI
TL;DR: A Vendor Managed Inventory (VMI) model for a two-level supply chain comprised of one vendor and several non-competing retailers in which both the raw material and the finished product have different deterioration rates is developed.

150 citations

Journal ArticleDOI
TL;DR: Experimental results demonstrate that the proposed algorithm not only achieves high embedding capacity but also enhances the PSNR of the stego image.
Abstract: Steganography is knowledge and art of hiding secret data into information which is largely used in information security systems. Various methods have been proposed in the literature which most of them are not capable of both preventing visual degradation and providing a large embedding capacity. In this paper, we propose a tunable visual image quality and data lossless method in spatial domain based on a genetic algorithm (GA). The main idea of the proposed technique is modeling the steganography problem as a search and optimization problem. Experimental results, in comparison with other currently popular steganography techniques, demonstrate that the proposed algorithm not only achieves high embedding capacity but also enhances the PSNR of the stego image.

150 citations


Authors

Showing all 83704 results

NameH-indexPapersCitations
Ajit Kumar Mohanty141112493062
Pierluigi Paolucci1381965105050
Eric Conte132120684593
Patrizia Azzi132127583686
D. Del Re131140687230
Jean-Laurent Agram128122184423
Seyed Mohsen Etesami128110176488
Jean-Charles Fontaine128119084011
Roberta Arcidiacono128132280917
Tejinder Virdee128120874372
Frank Hartmann127111681455
Paolo Azzurri126105881651
Achim Stahl1241248111121
Federica Primavera12087663895
Riccardo Andrea Manzoni12094667897
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202335
2022372
202111,539
202012,092
201911,011
201810,260