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The present paper provides information about the Alysiinae (Hymenoptera: Braconidae) species captured in Kerman province (Iran). A total of 14 species belonging to eight genera were collected and identified, of which three species are reported for the first time from Iran: Dinotrema (Prosapha) speculum (Haliday, 1838), Idiasta (Idiasta) dichrocera Konigsmann, 1960 and Protodacnus atristis (Nees, 1834). Diagnostic characters of the newly recorded species is presented.

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We present a list of 25 Chrysididae species mainly captured at high altitudeson mountains of the Kerman province, Iran. Thenumerous records evidences the rich biodiversity present at high altitudes in Iranian mountainsup to an elevation of about 3000 m.The largest richness was observed in the 2100-2300m range. Elampus kashmirensis Nurse, 1902, Holopyga chrysonota appliata Linsenmaier, 1959, Chrysis quadrispina Buysson, 1887 and Chrysis sacrata Buysson, 1898 are new records for Iranian fauna.

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The common pistachio psyllid, Agonoscena pistaciae Burckhardt & Lauterer (Hemiptera: Psyllidae), is a key pest of pistachio trees in Iran. Both psyllid nymphs and adults directly damage pistachio; they extract large quantities of sap from tree and produce honeydew and cause deformation of leaves resulting in great economic damage. Little is known about the intraspecific variation of common pistachio psyllid in regions with stressed conditions, such as areas under high levels of pesticide application. Therefore, this study using geometric morphometrics was designed to 1) evaluate morphological differences in wing shape in populations under different levels of pesticide application in Kerman province as the main pistachio producer in the world, and 2) search for a link between the morphological data and previously studied molecular data. The populations were collected from regions with high and low pesticide applications. The results showed that wing shape (P< 0.01) and size (P< 0.01) are different between populations exposed to different chemical control programs. Based on the results, narrower wing shape was found in psyllid population in stressed environment (population with extreme chemical control programs). In spite of allometric growth, significant shape differences still remain when the data are adjusted to constant size, which showed the important role of genetic changes in the observed morphological changes. Moreover, links between morphologic and previously studied molecular data were revealed. Based on the results, it appears that an evolutionary resistance process is developing, therefore insecticide resistance management programs, in the regions under investigation, is recommended.

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In this paper, the effects of the addition of an active toe joint on a 2D humanoid robot with heel-off and toe-off motions are studied. To this end, the trajectories of joints and links are designed firstly. After gait planning, the dynamic model of the humanoid robot in different phases of motion is derived using Kane and Lagrange methods. Then, the veracity of the derived dynamic model is demonstrated by two different methods. The under-study model, is in accordance with the features of SURENA III, which is a humanoid robot designed and fabricated at the Center of Advanced Systems and Technologies (CAST) located in University of Tehran. Afterward, the optimization procedure is done by selection of two different goal functions; one of them minimizes the energy consumption and the other maximizes the stability of the robot. At last, the obtained results are presented. According to the results, there is an optimum value for heel-off and toe-off angles in each velocity which minimizes the consumption of energy. The results also show that, the heel-off angle does not have any significant effects on the stability of the robot while increasing the toe-off angle improves the stability of motion. Finally, the effects of mass and length of the toe joint is inspected. These inspections suggest that heavier toe joints cause an increase in both energy consumption and stability of the robot while increasing the length of the toe joint does not have any effects on both goal functions.

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Mathematical modeling of tumor growth as modeling of other biological tissues is important since these models enable us to predict and evaluate the parameters that could not be measured easily. The accuracy of a derived model depends upon considering more involved factors and mechanisms and will lead us toward a realistic modelling.
In this study, a finite element model of avascular tumor growth is represented. This model concentrates on the constitutive behavior of tissues and the resulting stresses. The tumor and its host are assumed to behave as a hyperelastic material. The tumor model is supplied with a growth term which is a function of nutrient concentration, solid content of the tumor and rate of cell proliferation and death. The evolved stresses during growth and interactions between tumor and the surrounding host could be evaluated using the presented model. The results show that the exerted stresses on tumor increase as time passes which lead to reduction of tumor growth rate until it gradually reaches an asymptotic radius. The effects of variation of the bulk modulus which is a determinant of compressibility are investigated. Since biological tissues consist mainly of water so we should impose the condition of incompressibility. It is found that the increase of bulk modulus which leads to more incompressibility causes stress elevation.

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Nowadays, cities as a place of living and human activity are facing serious challenges in providing human needs. Increasing in population growth, vehicle ownership and communication development has led to complexity of the transportation system and its problems, including congestion, environmental pollution and the consumption of non-renewable resources. Therefore, changes in urban transport policies and efforts to develop and more use of the public transport, especially the bus, are one of the most important concerns in urban transport planning. A review of various studies suggests that planning for efficient use of bus infrastructures and enhancing the efficiency of public transportation operation in the world, require information on the infrastructure and passenger demand for lines and bus stations. Accordingly, it is necessary to carry out studies to predict passenger demand for bus stations in Tehran. Thus, this study predicts bus stations passenger demand for future short-term periods, using data gathered by AFC (Automated Fare Collection) and AVL (Automatic Vehicle Location). For this purpose, firstly AFC and AVL data was sorted according to the time for each bus line. Since passengers use their smart card while they are getting off the bus it means at the exit station thus identifying their origin station is vital, so that in second step, data of two data bases is compared and matched by writing computer code in Matlab software to determine the origin stations of passengers and then forming origin-destination demand matrix for each bus line in terms of its stations. This matrix is considered as the main data base of the study, a time series analysis, a seasonal autoregressive integrated moving average (SARIMA) and neural network as an artificial model are calibrated based on the available data. Both models’ goodness of fit indices are compared in terms of learning and generalization capabilities. For this purpose, initial data is divided into two subsets called learning and test data sets and comparison indices are computed for both aforementioned sets. The models’ results show that the multi-layer perceptron neural network model in terms of goodness of fit indices in both learning and generalization capabilities in prediction of bus station passenger demand is better than SARIMA model; however, the manner of influencing different factors such as day of week or month of year in passenger demand in each station is more clear in time series analysis. The passenger demand for each stations in first month in spring is different from the rest months in this season. Months in summer is also show different trends for passenger demand, while all months in fall and the first two months in winter have similar passenger demand in various stations. Official holidays has also significant influence on passenger demand so that reduce passenger demand by approximately 256 persons on average. All days in week have meaningful effects on passenger demand in comparison with Friday so that Monday and Thursday have the highest and the lowest effect on weekday passenger demand in bus stations in comparison with Friday, respectively. This analysis comparison show that if the precision of future prediction is important then neural network outweigh time series regression, while the identification of influential variables on passenger demand is better done by time series analysis.

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In this research work, using the recently introduced entropic constant speed kinetic model and employing the Pseudo-Potential model of Shan and Chen (SC), two phase flow of incompressible and immiscible fluids through porous media is studied. Applications of the entropic kinetic models in simulating multi-phase and multi-component flows have been thoroughly investigated, during the past decade. Lack of an entropy function, in a kinetics based model, implies that the existence of a unique equilibrium state, under all flow conditions and for all positions and times, cannot be guaranteed by the model. Hence, simulation of two multi-phase flows with high density ratios, using the conventional kinetic models (which do not satisfy the second law of thermodynamics) may not yield proper results, due to numerical instabilities. In this research, performing numerical simulations, the accuracy and stability of the recently introduced constant speed kinetic model and the conventional lattice Boltzmann models have been compared with each other. The present simulations include the verification of the Laplace Law and the contact angles and two phase flow through simple channels. In addition to the above, two phase flow in porous media has been simulated and the relative permeability vs wettability has been reported. The obtained results are in excellent agreement with previous results reported by others researchers.

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Industrial sector is always recognized as one of the largest energy consumers in each country. Besides the high energy consumption of industrial sector, a significant amount of energy is lost due to inefficient use and old machines. Combined heat and power (CHP) systems have always been considered as an efficient system to reduce energy consumption and increase productivity in the industry. The aim of this paper is techno-economic analysis of application of CHP systems in a few samples of different types of almost high energy consumer industries, considering the different approaches, on which the electrical capacity of the system is designed. In this study, a combination of various parameters such as different types of prime movers (gas turbine or reciprocating engine), different types of fuel (natural gas and diesel fuel), and guaranteed selling of generated electric power (GSGEP) in different industries are considered. Finally, after determining the capacity of the simultaneous production system for the selected factories, some important economic indicators like net present value (NPV), simple payback periods (SPB), and levelized cost of electricity (LCOE) were considered by two coupled software, MATLAB and Excel. The results showed that in all scenarios, the use of reciprocating engine as the prime mover and natural gas as its fuel is the best choice to satisfy the techno-economical goals.
 

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Concerns for climate change, reduction of greenhouse gas emission and environmental pollution, besides economically dependency on fossil fuels and political aspect motivate governments and policy makers to take into account replacing usual vehicle with alternative fuel vehicles (AFVs) such as Compressed Natural Gas Vehicles (CNGV) and Gasoline-Electric Hybrid Vehicles (GEHV). The air pollution in Tehran is a serious concern that based on this problem, CNGV has been introduced to Iranian market from 10 years ago. On the other hand, with the approval and notification of the removal of the electric vehicle importation’s tariff law, GEHV has been entered into the market of Iran as a new entrant. The purposes of this paper is to identify the effective factors to choose AFVs for drivers in Tehran and the assessment of effects of the incentive policies that increase AFV shares and computing their willingness to pay (WTP) for AFV under different incentives. This study designed a questionnaire which includes 3 parts: current vehicle features, dominant travel characteristics, socio-economic properties and the prioritization of effective factors on new vehicle purchase, and the tendency of AFVs choice with different scenarios representing different features. A random sample of 365 respondents was interviewed in a face-to-face survey in February 2016 in the technical inspection centers and in compressed natural gas stations. Finally, for the determination of effective factors on current and new vehicle purchase with revealed preference information and the assessment of AFVs usage tendency with stated preference information, the Multinomial Logit models have been used and WTPs are calculated. The incentive policy in Tehran, like previous studied countries, was the most influential factor in motivating consumers to buy AFVs in comparison to improvement of AFV specifications. The results show that drivers’ WTP is 5 MT for free access to even-odd area for CNGV and 12 MT for GEHV, also WTP for free access to pricing area in Tehran central business district is equal to 10 MT for CNGV; i.e. people tend to pay this extra cost for AFVs to access to pricing areas. These values are comparable with similar studies in cities located in developed countries. However, the results of this study show that WTP for fuel cost in Iran is considerably less than WTP of people driving in developed countries. The fuel cost and access time to gas stations are influential variables on CNGV choice. The vehicle acceleration and driving range are influential variables on GEHV choice.