Orumiyeh, Iran
Orumiyeh, Iran

Urmia University is a public university in the city of Urmia, West Azerbaijan province, Iran. The university has six campuses, seven faculties, more than 14,000 students, and exclusive research centers in Microelectronic, Antenna and Microwave Laboratory, NanoTechnology, MEMS, and Artimia. The university also has two satellite campuses in Khoy and Miyandoab city. Nazlu campus of Urmia University is the biggest university campus in northwest of Iran. Urmia University is considered one of Iran's "Grade A" universities by Iranian Ministry of Science. Wikipedia.

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Nazarizadeh A.,Urmia University | Asri-Rezaie S.,Urmia University
AAPS PharmSciTech | Year: 2016

In the current study, antidiabetic activity and toxic effects of zinc oxide nanoparticles (ZnO) were investigated in diabetic rats compared to zinc sulfate (ZnSO4) with particular emphasis on oxidative stress parameters. One hundred and twenty male Wistar rats were divided into two healthy and diabetic groups, randomly. Each major group was further subdivided into five subgroups and then orally supplemented with various doses of ZnO (1, 3, and 10 mg/kg) and ZnSO4 (30 mg/kg) for 56 consecutive days. ZnO showed greater antidiabetic activity compared to ZnSO4 evidenced by improved glucose disposal, insulin levels, and zinc status. The altered activities of erythrocyte antioxidant enzymes as well as raised levels of lipid peroxidation and a marked reduction of total antioxidant capacity were observed in rats receiving ZnO. ZnO nanoparticles acted as a potent antidiabetic agent, however, severely elicited oxidative stress particularly at higher doses. © 2015, American Association of Pharmaceutical Scientists.


The present study develops a lumped capacitance model for modelling the heat transfer in a salinity gradient solar pond. This model is used to analyze the transient energy behaviour in each zone of the pond incorporating many processes that affect the performance of a solar pond. The effect of various parameters such as different solar attenuation models, thickness of each zone, heat loss from the pond's surface, and the wall-shading effect on the temperature of the storage zone would be investigated. The validity of the model is tested against experimental data for a small circular pond constructed in Urmia University, and a good agreement between theoretical and experimental data for the temperature in the storage zone has been obtained. The results indicated that the heat loss from the pond's surface occurs mostly by evaporation rather than radiation and convection. In addition, it is observed that the upper convective zone thickness should be as thin as possible and the lower convective zone thickness may be designed based on the application needs. It is concluded that wall-shading effect has a significant effect on the storage temperature of a small pond, however, the effect is found to be small in the large pond. © 2017 Elsevier Ltd


Babazadeh R.,Urmia University
RAIRO - Operations Research | Year: 2017

Accurate estimation and forecasting of gasoline is vital for policy and decision-making process in energy sector. This paper presents a hybrid data-driven model based on Artificial Neural Network (ANN) and autoregressive integrated moving average (ARIMA) approach for optimum estimation and forecasting of gasoline consumption. The proposed hybrid ARIMA-ANN approach considers six lagged variables and one forecasted values provided by ARIMA process. The ANN trains and tests data with Multi Layer Perceptron (MLP) approach which has the lowest Mean Absolute Percentage Error (MAPE). To show the applicability and superiority of the proposed hybrid approach, daily available data were collected for 7 years (2005-2011) in Iran. Although eliminating subside from gasoline price has led to appearing noisy data in gasoline consumption in Iran the acquired results show high accuracy of about 9427% by using the proposed hybrid ARIMA-ANN method. The results of the proposed model are compared respect to regression's models and ARIMA process. The outcome of this paper justifies the capability of the proposed hybrid ARIMA-ANN approach in accurate forecasting gasoline consumption. © 2017 EDP Sciences, ROADEF, SMAI.


Hassanpour H.,Urmia University
LWT - Food Science and Technology | Year: 2015

Native populations of raspberry fruits (Rubus spp.) were coated with Aloe vera gel and were then assayed for the antioxidant capacity, total anthocyanin, total phenol, antioxidant enzyme activities and postharvest quality after 8 days storage at 4°C, relative to a control group. These berries, coated with Aloe vera gel, showed a higher antioxidant capacity, total anthocyanin and total phenol than those of the controls (non-treated) group. The treated fruits exhibited less incidence of decay during storage at 4°C than the control group. Thus postharvest life (as affected by fungal decay) was longer for berries treated with Aloe vera gel than for the control fruit. However, total soluble solid, titratable acidity and pH were predominantly influenced by storage periods. Aloe vera gel treatments could reduce the natural decay that happens over time. The activities of antioxidant enzymes, including glutathione peroxidase (GSH-POD), glutathione reductase (GR), superoxide dismutase (SOD), ascorbate peroxidase (AsA-POD) and guaiacol peroxidase (G-POD) were enhanced. The nonenzyme components such as reduced glutathione (GSH) and oxidized glutathione (GSSG) were also increased by Aloe vera gel. In conclusion, raspberry fruits treated with Aloe vera gel maintained higher levels of antioxidant capacity, total phenol, total anthocyanin and antioxidant enzymes during storage periods. © 2014 Elsevier Ltd.


Gholizadeh S.,Urmia University
Computers and Structures | Year: 2013

The main contribution of the present paper is to propose an efficient hybrid optimization algorithm for layout optimization of truss structures. To achieve this, computational merits of the cellular automata (CA) and the particle swarm optimization (PSO) are integrated. In the proposed hybrid algorithm a CA-based mechanism is utilized as the velocity updating equation of the particles in the framework of the sequential unconstrained minimization techniques and therefore it is denoted as sequential cellular PSO (SCPSO). The numerical results demonstrate that SCPSO not only converges to better solutions but also provides faster convergence rate in comparison with other algorithms. © 2013 Elsevier Ltd. All rights reserved.


In this investigation, the energy and exergy analyses are carried out in pre and main chambers of a Lister 8.1 indirect injection diesel engine (IDI) diesel engine for two loads (BMEP of 2.96 bar and 5.9 bar as 50% and full load operations) at maximum torque engine speed (730 rpm). The energy analyses are carried out during a closed engine cycle by using a computational fluid dynamics (CFD) code. The results for the pressure in cylinder for two loads are compared with the corresponding experimental data and show good agreement. Also, for the exergy analysis in the chambers, a developed in-house computational code is applied. Various exergy components are identified and calculated separately with crank position at both loads. The results show that at partial and full load operations 56% and 77% of total irreversibility are related to combustion process in main chamber, respectively. This work demonstrates that multidimensional modeling can be used at complex chamber geometry to gain more insight into the effect of flow field on the combustion process accounting for the second-law of thermodynamics. © 2012 Elsevier Ltd. All rights reserved.


Monitoring general variability of soil attributes is a fundamental requirement from the point of view of understanding and predicting how ecosystems yield. In order to monitor impact of different land use types on the combination of morphological, clay mineralogical and physicochemical characterizes, 42 soil samples (0-30 cm) were described and analyzed. Soil samples belonging to Cambisols and Vertisols reference soil groups collected from three neighboring land use types included cropland (under long-term continuous cultivation), grassland, and forestland. The soils were characterized by high pH (mean of 7.1-7.5) and calcium carbonate equivalent (CCE) (mean of 35-97 g kg-1) in the three land use types. The weakening in soil structure, hardening of consistency, and lighting of soil color occurred for the cropland under comparable condition with grassland and forest. Changes in land use types produced a remarkable change in the XRD patterns of clay minerals containing illite and smectite due the dynamic and removal of potassium. Continuous cultivation resulted in an increase in sand content up to 35 % while silt and clay content decreased up to 22 and 18 %, respectively, as compared to the adjoining grassland and forest mainly as a result of the difference of dynamic alterational and erosional process in the different land use. Long-term cultivation caused a negative and degradative aspects on soil heath as is manifested by the increasing in soil pH (a rise of 0.3-0.46 unit), electrical conductivity (EC) (a rise of 1.78-5.5 times), sodium absorption ration (SAR) (a rise of 10-51 %), exchangeable sodium percentage (ESP) (a rise of 3-46 %), and the decrease in soil organic C (a drop of 12-41 %), along with soil fertility attributes. Overall, the general distribution of soil organic C, total N, available P and K, cation exchange capacity (CEC), and exchangeable cations (Ca, Mg, and K) followed the order: forestland > grassland > cropland. The general distribution of EC, SAR, ESP, and exchangeable Na, however, followed the order: cropland > grassland > forestland. Soil quality index (SQI), calculated based on some physicochemical properties, specified that cultivation led to a negative effect in SQI for both Cambisols (a drop of 10-17 %) and Vertisols (a drop of 17 %) as compared to those of under grassland and forestland. © 2013 The Author(s).


In this investigation, the energy and exergy analyses are carried out for a Lister 8.1 IDI (indirect injection) diesel engine at four different EGR (exhaust gas recirculation) mass fractions (0%, 10%, 20% and 30%) and at 50% load operation. The energy analysis is performed during a closed cycle by using a three-dimensional CFD (Computational Fluid Dynamics) code. For the exergy analysis, an in-house computational code is developed, which uses the results of the energy analysis at different EGR mass fractions. The cylinder pressure results for baseline engine are compared with the corresponding experimental data that shows a good agreement. With crank position at different EGR mass fractions, various exergy components and the cumulative exergy are identified and calculated separately. It is found that at 50% load operation, as EGR mass fraction increases from 0% to 30% (in 10% increments), exergy efficiency decreases from 31.74% to 25.38%. Also, the cumulative irreversibility related to the combustion chamber decreases from 29.8% of the injected fuel exergy to 25.5%. This work demonstrates that multidimensional modeling can be used to simulate the effect of various EGR mass fractions and gain more insight into the impact of flow field on combustion process in IDI engines from the second law perspective. © 2014 Elsevier Ltd.


Machine dynamics and soil elastic-plastic characteristic sort out the soil-wheel interaction productions as very complex problem to be estimated. Energy dissipation due to motion resistance, as the most prominent performance index of towed wheels, is associated with soil properties and tire parameters. The objective of this study was to develop, for the first time, a model for prediction of energy loss in soil working machines using the datasets obtained from soil bin facility and a single-wheel tester. A total of 90 data points were derived from experimentations at five levels of wheel load (1, 2, 3, 4, and 5kN), six tire inflation pressure (50, 100, 150, 200, 250, and 300kPa) and three forward velocities (0.7, 1.4 and 2m/s). ANN (Artificial neural network) was used for modeling of obtained results compared to the forecasting ability of SVR (support vector regression) technique. Several statistical criterions, (i.e. MAPE (mean absolute percentage error), MSE (mean square error), MRE (mean relative error) and coefficient of determination (R2) were incorporated in the investigations. It was observed, on the basis of statistical criterions, that SVR-based generalized model outperformed ANN in modeling energy loss and exhibited its applicability as a promising tool in this domain. © 2014 Elsevier Ltd.


A general algorithm is presented to approximately solve a great variety of linear and nonlinear ordinary differential equations (ODEs) independent of their form, order, and given conditions. The ODEs are formulated as optimization problem. Some basic fundamentals from different areas of mathematics are coupled with each other to effectively cope with the propounded problem. The Fourier series expansion, calculus of variation, and particle swarm optimization (PSO) are employed in the formulation of the problem. Both boundary value problems (BVPs) and initial value problems (IVPs) are treated in the same way. Boundary and initial conditions are both modeled as constraints of the optimization problem. The constraints are imposed through the penalty function strategy. The penalty function in cooperation with weighted-residual functional constitutes fitness function which is central concept in evolutionary algorithms. The robust metaheuristic optimization technique of the PSO is employed to find the solution of the extended variational problem. Finally, illustrative examples demonstrate practicality and efficiency of the presented algorithm as well as its wide operational domain. © 2013 Elsevier B.V. All rights reserved.

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