Kn Toosi University Of Technologytehran

science, Iran

Kn Toosi University Of Technologytehran

science, Iran
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Ramezankhani R.,U.S. Center for Disease Control and Prevention | Ramezankhani R.,Islamic Azad University at North Tehran | Hosseini A.,Shahid Rajaee Teacher Training University | Sajjadi N.,Islamic Azad University at North Tehran | And 2 more authors.
Spatial and Spatio-temporal Epidemiology | Year: 2017

Objectives This study was designed to determine the environmental factors associated with cutaneous leishmaniasis (CL) in Isfahan Province, using spatial analysis. Methods Data of monthly CL incidence from 2010 to 2013, climate and environmental factors including: temperature, humidity, rainfall, wind speed, normalized difference vegetation index (NDVI), altitude and population density across the Isfahan's cities was used to perform spatial analysis by ordinary least square (OLS) regression and geographically weighted regression (GWR). Results OLS revealed a significant correlation between CL incidence and five predictors including temperature, population density, wind speed, humidity and NDVI; which explained 28.6% of variation in CL incidence in the province. Considering AICc and adjusted R2, GWR provided a better fit to the data compared with OLS. Conclusion There was a positive correlation between temperature and population density with CL incidence in both local (city) and global (province) level. © 2017 Elsevier Ltd


Esmaeilzehi A.,Kn Toosi University Of Technologytehran | Abrishami Moghaddam H.,Kn Toosi University Of Technologytehran | Abrishami Moghaddam H.,University of Picardie Jules Verne
Pattern Recognition Letters | Year: 2017

Sparse representation-based classifier (SRC) and kernel sparse representation-based classifier (KSRC) are founded on combining pattern recognition and compressive sensing methods and provide acceptable results in many machine learning problems. Nevertheless, these classifiers suffer from some shortcomings. For instance, SRC's accuracy drops against samples from same directional classes or KSRC's output declines when data is not normally distributed in kernel space. This paper introduces nonparametric kernel sparse representation-based classifier (NKSRC) as a generalized framework for SRC and KSRC. First, it applies kernel on samples to overcome data directionality and then employs nonparametric discriminant analysis (NDA) to reduce data dimensionality in kernel space alleviating concern about data distribution type. The experimental results of NKSRC demonstrate its superiority over SRC and KSRC–LDA and its equal or superior performance with respect to KSRC–PCA on some synthetic, four well-known face recognition and several UCI datasets. © 2017


Modarresi S.M.,Kn Toosi University Of Technologytehran | Masoudi S.F.,Kn Toosi University Of Technologytehran | Karimi M.,Amirkabir University of Technology
Radiation Physics and Chemistry | Year: 2017

A method for considering the spatial variation of deal layer (DL) thickness at the lateral and top surfaces of HPGe detectors is proposed. Instead of considering the exact variation of DL thickness at detector surface, the lateral surface is divided into 12 segments, assuming each segments covers 30 degrees of the detector lateral surface and has a different DL thickness. Then, using Am-241 source at 12 positions on lateral surface and also on top surface of a HPGe detector, the nearest DL thickness for each segment can be selected through estimation of Full Energy Peak Efficiency (FEPE). This is the case in both experimental and simulation sides. The proposed detector can be used for FEPE calculation of bulk samples geometries such as Marinelli beaker containers. In order to check the suitability of proposed detector for bulky samples, a Marinelli beaker containing a set of standard radiation source solution with specified activities is considered. The experimental and simulation results of FEPE show good agreement with minimum 2% to maximum 6% relative difference from low (59.5 keV) to high energy (1.33 MeV) gamma ray. © 2016 Elsevier Ltd


Makhuri F.R.,Kn Toosi University Of Technologytehran | Ghasemi J.B.,Kn Toosi University Of Technologytehran
European Journal of Pharmaceutical Sciences | Year: 2015

Abstract In this study as the first attempt; comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and AutoGPA-based 3D-QSAR methods were applied on a set of 47 recently reported Ck1d inhibitors, in order to gain an insight into the structural requirements which providing guidelines for the design of next generation compounds with enhanced bioactivity. The results of 3D-QSAR analyses indicated that hydrophobic and negatively charged groups at 6th position of benzothiazole ring and positively charged and bulky groups at ortho position of phenyl ring are favorable for high activity. Moreover, molecular docking studies with GOLD protocol revealed that this chemical series has two different orientations in CK1d active site: orientation 1, in which the benzothiazole ring of the compounds is the closet to the hydrophobic area created by Ile23 and 37, Ala36 Lys 38, Met80, 82 and Val81, and orientation 2, in which the benzene ring of the compounds is directed toward the hydrophobic center. Molecular docking result of the riluzole, the only drug approved by FDA for amyotrophic lateral sclerosis (ALS), indicated that the orientation 2 is preferred due to the presence of OCF3 group in R1 situation at 6th position of benzothiazole ring, while with replacement of OCF3 group by CF3, the orientation 1 is observed. At the end, to find similar analogs by virtual screening, a two-stage approach: pharmacophore-based screening using generated AutoGPA-based 3D-QSAR model followed by structure-based virtual screening using molecular docking was employed. Visual inspection of the docking results of virtually obtained hits revealed two different binding orientations, in which compounds with high GOLD fitness scores produced binding modes, which were the same as the one observed in compounds with orientation 1, whereas the binding modes of the structures with low GOLD fitness scores were in agreement with orientation 2. Further, the drug-like properties of the obtained seven hits with the highest GOLD scores were investigated as a tool to optimize the selection of the most suitable candidates for drug development. © 2015 Elsevier B.V.


Saadatfara M.,Kn Toosi University Of Technologytehran | Aghaie-Khafri M.,Kn Toosi University Of Technologytehran
Smart Structures and Systems | Year: 2015

The electro-magneto- thermo-elastic behavior of a rotating functionally graded long hollow cylinder with functionally graded piezoelectric (FGPM) layers is analytically analyzed. The layers are imperfectly bonded to its inner and outer surfaces. The hybrid cylinder is placed in a constant magnetic field subjected to a thermo-electro-mechanical loading and could be rested on a Winkler-type elastic foundation. The material properties of the FGM cylinder and radially polarized FGPM layers are assumed to be graded in the radial direction according to the power law. The hybrid cylinder is rotating about its axis at a constant angular velocity. The governing equations are solved analytically and then stresses, displacement and electric potential distribution are calculated. Numerical examples are given to illustrate the effects of material in-homogeneity, magnetic field, elastic foundation, applied voltage, imperfect interface and thermo-mechanical boundary condition on the static behavior of a FG smart cylinder. Copyright © 2015 Techno-Press, Ltd.


Kamalinejad M.,Kn Toosi University Of Technologytehran | Amidpour M.,Kn Toosi University Of Technologytehran | Naeynian S.M.M.,Kn Toosi University Of Technologytehran
Chinese Journal of Chemical Engineering | Year: 2015

Abstract Liquefied natural gas (LNG) is the most economical way of transporting natural gas (NG) over long distances. Liquefaction of NG using vapor compression refrigeration system requires high operating and capital cost. Due to lack of systematic design methods for multistage refrigeration cycles, conventional approaches to determine optimal cycle are largely trial-and-error. In this paper a novel mixed integer non-linear programming (MINLP) model is introduced to select optimal synthesis of refrigeration systems to reduce both operating and capital costs of an LNG plant. Better conceptual understanding of design improvement is illustrated on composite curve (CC) and exergetic grand composite curve (EGCC) of pinch analysis diagrams. In this method a superstructure representation of complex refrigeration system is developed to select and optimize key decision variables in refrigeration cycles (i.e. partition temperature, compression configuration, refrigeration features, refrigerant flow rate and economic trade-off). Based on this method a program (LNG-Pro) is developed which integrates VBA, Refprop and Excel MINLP Solver to automate the methodology. Design procedure is applied on a sample LNG plant to illustrate advantages of using this method which shows a 3.3% reduction in total shaft work consumption. © 2015 Elsevier B.V.


Salahinejad E.,Kn Toosi University Of Technologytehran | Ghaffari M.,Bruker AXS Inc. | Vashaee D.,North Carolina State University | Tayebi L.,Marquette University | Tayebi L.,University of Oxford
Materials Science and Engineering C | Year: 2016

It has been frequently reported that cell viability on stainless steels is improved by increasing their corrosion resistance. The question that arises is whether human cell viability is always directly related to corrosion resistance in these biostable alloys. In this work, the microstructure and in vitro corrosion behavior of a new class of medical-grade stainless steels were correlated with adult human mesenchymal stem cell viability. The samples were produced by a powder metallurgy route, consisting of mechanical alloying and liquid-phase sintering with a sintering aid of a eutectic Mn-Si alloy at 1050°C for 30 and 60 min, leading to nanostructures. In accordance with transmission electron microscopic studies, the additive particles for the sintering time of 30 min were not completely melted. Electrochemical impedance spectroscopic experiments suggested the higher corrosion resistance for the sample sintered for 60 min; however, a better cell viability on the surface of the less corrosion-resistant sample was unexpectedly found. This behavior is explained by considering the higher ion release rate of the Mn-Si additive material, as preferred sites to corrosion attack based on scanning electron microscopic observations, which is advantageous to the cells in vitro. In conclusion, cell viability is not always directly related to corrosion resistance in stainless steels. Typically, the introduction of biodegradable and biocompatible phases to biostable alloys, which are conventionally anticipated to be corrosion-resistant, can be advantageous to human cell responses similar to biodegradable metals. © 2016 Elsevier B.V. All rights reserved.


Mohammadi K.,University of Massachusetts Amherst | Alavi O.,Kn Toosi University Of Technologytehran | Mostafaeipour A.,University of Yazd | Goudarzi N.,University of Maryland University College | Jalilvand M.,University of Siegen
Energy Conversion and Management | Year: 2016

In this study, the effectiveness of six numerical methods is evaluated to determine the shape (k) and scale (c) parameters of Weibull distribution function for the purpose of calculating the wind power density. The selected methods are graphical method (GP), empirical method of Justus (EMJ), empirical method of Lysen (EML), energy pattern factor method (EPF), maximum likelihood method (ML) and modified maximum likelihood method (MML). The purpose of this study is to identify the more appropriate method for computing the wind power density in four stations distributed in Alberta province of Canada namely Edmonton City Center Awos, Grande Prairie A, Lethbridge A and Waterton Park Gate. To provide a complete analysis, the evaluations are performed on both daily and monthly scales. The results indicate that the precision of computed wind power density values change when different parameters estimation methods are used to determine the k and c parameters. Four methods of EMJ, EML, EPF and ML present very favorable efficiency while the GP method shows weak ability for all stations. However, it is found that the more effective method is not similar among stations owing to the difference in the wind characteristics. © 2015 Elsevier Ltd.


Asl Y.A.,Tarbiat Modares University | Yamini Y.,Tarbiat Modares University | Seidi S.,Kn Toosi University Of Technologytehran
Talanta | Year: 2016

In the present study, for the first time, an on-chip liquid phase microextraction (LPME) coupled with high performance liquid chromatography was introduced for the analysis of levonorgestrel (Levo), dydrogesterone (Dydo) and medroxyprogesterone (Medo) as the model analytes in biological samples. The chip-based LPME set-up was composed of two polymethyl methacrylate (PMMA) plates with microfabricated channels and a microporous membrane sandwiched between them to separate the sample solution and acceptor phase. These channels were used as a flow path for the sample solution and a thin compartment for the acceptor phase, respectively. In this system, two immiscible organic solvents were used as supported liquid membrane (SLM) and acceptor phase, respectively. During extraction, the model analytes in the sample solution were transported through the SLM (n-dodecane) into the acceptor organic solvent (methanol). The new set-up provided effective and reproducible extractions using low volumes of the sample solution. The effective parameters on the extraction efficiency of the model analytes were optimized using one variable at a time method. Under the optimized conditions, the new set-up provided good linearity in the range of 5.0–500 µg L−1 for the model analytes with the coefficients of determination (r2) higher than 0.9909. The relative standard deviations (RSDs%) and limits of detection (LODs) values were less than 6.5% (n=5) and 5.0 µg L−1, respectively. The preconcentration factors (PFs) were obtained using 1.0 mL of the sample solution and 20.0 µL of the acceptor solution higher than 19.9-fold. Finally, the proposed method was successfully applied for the extraction and determination of the model analytes in urine samples. © 2016 Elsevier B.V.

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