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In order to help in the engineering design of rice harvesting machines, there is a need to have exact information concerning the physical and mechanical properties of rice stems. The cutting force for rice stems, therefore, was measured by designing and fabricating a static and dynamic shear test apparatus. The effects of moisture levels and the cross-sectional area of stem as well as the variety, blade bevel angle, blade type and cutting speed on shearing strength have been evaluated. The results indicated that the cutting force increased with an increase in the cross-sectional area and decreased with an increase in moisture content. The static and dynamic shearing strength was different among the varieties. The maximum and minimum shearing strengths were related to the varieties Khazar and Hashemi, with an average of 1629 and 1429 kPa for static test and values of 187.4 and 144 kPa for the dynamic test, respectively. The shearing strength decreased from 234.4 kPa to 137.4 Kpa with an increase in blade cutting speed from 0.6 to 1.5 m/s. Blade bevel angle and blade type had no significant effect on the shearing strength of rice stem.

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The main goal of this paper is to analyze the exchange rate pass-through, the relationship between exchange rate and prices, provided that a shock occurs and changes exchange rate and prices. The key point in this study is that exchange rate is considered as an endogenous variable. This issue is important because exchange rate pass-through due to specific shocks differs from case to case. Hence a dynamic stochastic general equilibrium model is presented and simulated for Iran. The accuracy of the model is analyzed by comparing the moments of the model and the moments of the quarterly data from 1988 to 2010. Then, exchange rate pass-through conditional on each shock (technology, oil revenue, foreign output, and demand for money, foreign interest rate and monetary policy shocks) is calculated by the ratio of covariance of the impulse response of price and exchange rate to variance of the impulse response of exchange rate. Finally, aggregate exchange rate pass-through is computed as the sum of conditional pass-through coefficients in each time weighted by the contribution of each shock. The biggest exchange rate pass-through to consumer prices belongs to oil revenue and foreign output shocks which amounts to about 1, and the smallest one is related to technology shock.

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Three electrode system simulates the human tongue taste system and can be used to assess the quality of food. The sense of taste is one of the five senses and tongue recognizes certain molecules. In recent years, three electrode system with an array of electrodes has been used to identify various molecules. In this research, a three electrode system is used based on voltammetric methods with three graphite electrodes (Pencil Graphite (PG)), Screen Printed (SP) and Glassy Carbon (GC) to identify heavy metals (cadmium , Lead, tin and nickel) in olive oil. Heavy metals are added to the edible oil in three concentrations of 0.05, 0.1 and 0.25 ppm and then the output of the device is classified by chemometric method. According to PCA results, the PG electrode contains 96% of the variance between the data in olive edible oils. Also, SP electrode contains 91% and GC contains 100% of the variance between the data in olive oil. The SVM method showed a high ability to classify heavy metals in edible oils. Also, The PLS method was also able to predict 99% of the data in olive oil for all electrodes. Finally, according to the results, it can be said that the built-in three electrode system has a high accuracy in identifying heavy metals in edible oils.

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In this research , The kinetics of drying , The Determining The effective Moisture Diffusivity, Activation Energy, And also the prediction of the moisture ratio of red onion during the dry process with dryer-hot air drying were carried out with the help of mathematical models and fuzzy neural inference system (ANFIS). The experiments were performed at four levels of temperature at 50, 60, 70 and 80 0C and a constant air flow rate of 1 m/s . To select a suitable drying model, twelve thin layer drying models were used, as well as using fuzzy neural inference system R Software version 3.6.2. The results showed that among the mathematical models, The binomial model with the highest coefficient of explanation and the lowest root mean square error was the most suitable. The results of the correlation coefficient value (R2 = 0.999 and error) RMSE = ( 0.002) the lowest root mean square error It predicted the humidity ratio better than mathematical models. Effective Moisture Diffusivity for four temperatures, Respectively (0.03136255,0 0211698,00193770.001847669 0) M²/ S and The amount of activation energy was 1890.4 (kJ /(kg.K).