Islamic Azad University North Tehran Branch

About: Islamic Azad University North Tehran Branch is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Adsorption & Catalysis. The organization has 868 authors who have published 968 publications receiving 9987 citations.

Comparison of effect of intraperitoneal vs. intra-accumbal injection of memantine on response to acute stress in female NMRI mice

Abstract: Introduction: In this study, the effect of memantine administration into the nucleus accumbens on the metabolic changes induced by acute stress in female mice was evaluated. Methods: Intra-accumbens unilateral or bilateral canulation was performed. One week after recovery, a group of animals were given memantine (1, 0.5, and 0.1 μg/mouse) five min before stress induction intra-accumbally, and the other group received it (1, 0.5 and 0.1 mg/kg) 30 min before stress intraperitoneally. Food and water intake, weight of fecal material, and the delay time before eating were measured as metabolic parameters after stress induction. Results: Acute stress reduced water and food intake, fecal matter, and the delay time before eating. Intraperitoneal memantine injections augmented the stress effect on water intake, but inhibited its effect on food intake at dose of 0.1 mg/kg and had no impact on defecation. The drug induced anorexia especially at dose of 1 mg/kg. On the other hand, intra-accumbens memantine injections reduced water intake when the drug was injected in the left side. Moreover, memantine injections inhibited or enhanced the effects of stress on water intake, food intake and defecation in a doseand location-dependent manner, and also increased the delay time before eating. Conclusion: Memantine inhibits or enhances the effects of acute stress dose-dependently. In addition, it seems that there is asymmetry in nucleus accumbens response. Key

Travel management optimization based on air pollution condition using Markov decision process and genetic algorithm (case study: Shiraz city)

Abstract: Currently, air pollution and energy consumption are the main issues in the transportation area in large urban cities. In these cities, most people choose their transportation mode according to corresponding utility including traveller's and trip’s characteristics. Also, there is no effective solution in terms of population growth, urban space, and transportation demands, so it is essential to optimize systematically travel demands in the real network of roads in urban areas, especially in congested areas. Travel Demand Management (TDM) is one of the well-known ways to solve these problems. TDM defined as a strategy that aims to maximize the efficiency of the urban transport system by granting certain privileges for public transportation modes, Enforcement on the private car traffic prohibition in specific places or times, increase in the cost of using certain facilities like parking in congested areas. Network pricing is one of the most effective methods of managing transportation demands for reducing traffic and controlling air pollution especially in the crowded parts of downtown. A little paper may exist that optimize urban transportations in busy parts of cities with combined Markov decision making processes with reward and evolutionary-based algorithms and simultaneously considering customers’ and trip’s characteristics. Therefore, we present a new network traffic management for urban cities that optimizes a multi-objective function that related to the expected value of the Markov decision system’s reward using the Genetic Algorithm. The planned Shiraz city is taken as a benchmark for evaluating the performance of the proposed approach. At first, an analysis is also performed on the impact of the toll levels on the variation of the user and operator cost components, respectively. After choosing suitable values for the network parameters, simulation of the Markov decision process and GA is dynamically performed, then the optimal decision for the Markov decision process in terms of total reward is obtained. The results illustrate that the proposed cordon pricing has significant improvement in performance for all seasons including spring, autumn, and winter.

2-(2-Quinol-yl)quinolinium nitrate.

Abstract: In the cation of the title compound, C18H13N2+·NO3−, the two bicyclic ring systems form a dihedral angle of 3.84 (4)°. The nitrate anion is disordered over two orientations in a 0.9:0.1 ratio. In the crystal structure, the cations form stacks along the a axis, with short inter­molecular contacts [C⋯C = 3.330 (3) and 3.345 (4) A], and link to the anions via N—H⋯O hydrogen bonds.

State-of-the-art adaptive mesh generator implementation for dynamic asphaltene deposition in four-phase flow simulator in near well-bore region

Abstract: Asphaltene deposition leads to rigorous problems in petroleum industry such as relative permeability reduction, wettability alterations, and blockage of the flow with additional pressure drop in wellbore tubing, etc . Many attempts have been undertaken to develop reliable and accurate models to predict phase behavior of asphaltene. However, previously published models cannot couple static and dynamic behaviors of reservoir and its fluids. In this communication, a novel four-phase flow simulator has been developed considering asphaltene deposition as one of the phases, using finite volume formulation. A novel adaptive unstructured mesh generator technique has been introduced in which dynamic properties of reservoir are combined with static field parameters. The results of this study illustrated that the proposed methodology can accurately predict the oil sample properties, and the amount of asphaltene precipitation. Moreover, it was found that the proposed approach is faster and computationally less expensive compared to fine structured model. The proposed strategy can be applied in any reservoir simulator and provides asphaltene phase behavior and reservoir properties with high degree of accuracy.

A Novel and an Efficient 3-D High Nitrogen Doped Graphene Oxide Adsorbent for the Removal of Congo Red from Aqueous Solutions

Abstract: The current study both synthesizes and uses four compounds of graphene oxide (GO), nitrogen doped graphene oxide (ND-GO), high nitrogen doped graphene oxide (HND-GO), and three dimensional high nitrogen doped graphene oxide (3D-HND-GO) in order to remove a model anionic dye, Congo red (CR) from wastewaters. It also compares their carbon nano-structure, with regard to removal efficiency and finds out that 3D-HND-G yields higher efficiency in removal of CR, especially at lower pHs. This is due to its better dispersibility and greater surface area. Also, batch adsorption technique has been utilized and all involved parameters that affect the removal efficiency, e.g. initial pH, adsorbent dosage, initial CR concentration, and contact time are examined. The study applies Central Composite Design (CCD) to figure out their efficacies, with the results showing the following optimum conditions for removal of 100 ppm of CR: 4 mg/mL of the adsorbent, pH = 3, and 25 min of contact time. Furthermore, it studies the adsorption activity of the synthesized adsorbent, including kinetics, isotherm, and desorption comprehensibly. The adsorption isotherm is well-fitted through the Langmuir model, exhibiting high CR adsorption capacity. Also, CR adsorption kinetics shows that it has obeyed a pseudo-second-order kinetic model, indicating that adsorption has made the rate-limiting step. In addition, the proposed adsorbent has successfully been applied to reduce the concentration of CR as hazardous dye materials in the water and wastewater samples.