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Semiotics is an approach that studies the signs and their hidden meanings. This article is a social semiology of Bivatan—amodern novelwritten by Reza Amirkhani. The novel struggles with fundamental issues such as identity, culture, and social traditions. Like most other postmodern novels, Bivatan is a combination of reality and imagination. Most parts of the story happen outside of Iran and show the conflict between Islamic-Persian culture and the Western culture. The conflict between humans and their surrounding is another major aspect of this novel. This article elaborates on the identity-related signs such as religion, food, costume, job, social relations, and so forth. The fundamental role of religion, drawing on Quranicverses, identity crisis, and differences in social class are among the other subjects which will be discussed in this paper.  

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The evolution of financial data shows a high degree of volatility of the series, coupled with increasing difficulties of forecasting financial variables. Some alternative forecasting methods, based on the literature review, have been developed, which can be particularly useful in the analysis of financial time series. Despite of the numerous time series forecasting models, the accuracy of time series forecasting is fundamental to many decision processes. Selecting an efficient technique in unique situations is very difficult task for forecasters. Many researchers have integrated linear and nonlinear methods in order to yield more accurate results. In practice, it is difficult to determine the time series under study are generated from a linear or nonlinear underlying process while many aspects of economic behavior may not be pure linear or nonlinear. Although both ARIMA and Artificial Neural Networks (ANNs) models have the flexibility in modeling a variety of problems, none of which is universally the best model used indiscriminately in every forecasting situation. In this paper, based on the foundations of ARIMA and ANNs models, a hybrid method is proposed to forecast exchange rate. Empirical results indicate that integrating linear and nonlinear ARIMA and Artificial Neural Networks (ANNs) models can be an effective way to improve forecasting accuracy achieved by either of the above linear and nonlinear models used separately.

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Micromechanical resonators are miniature devices that vibrate at high frequencies. Nowadays, with the recent advances in micro-electro-mechanical systems (MEMS) fabrication technology, micromechanical resonators are used widely in sensors, wireless communication and navigation systems. The commonly encountered energy loss mechanisms in micromechanical resonators include air damping, thermoelastic dissipation and anchor loss. In this paper, with regard to the dominated quality factor by anchor loss in some important applications including oscillators, electrical filters and gyroscopes, the closed-form expression is obtained for anchor loss quality factor in the plunging-mode vibrations of micromechanical rectangular-plate resonator with two support beams. The findings are validated by comparing with experimental data. As far as there is an acceptable match between the analytical and experimental results, the proposed model is confirmed. The results also show that the anchor loss quality factor increases with increasing substrate thickness. Moreover, a new design is proposed to enhance the anchor loss quality factor in the plunging-mode vibrations of micromechanical rectangular-plate resonators. For this purpose, the conventional support beams are replaced with T-shaped support beams. Besides, the results show that the anchor loss quality factor at the same resonant frequency is enhanced about 1.5 times.

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This study was performed to determine the effect of copper on growth performance, blood metabolites and claw health in young Holstein bulls in a humid area in north of Iran. One hundred and two young Holstein bulls (Initial body weight= 377.3±17.1 kg) were randomly allocated to two treatments in a completely randomized design for 56 days. The treatment groups received: (1) the basal diet of no supplemental Cu (control; n= 50); (2) basal diet plus 30 mg of Cu kg^-1 of Dry Matter (DM) as CuSO₄ (n= 52). Animals received fresh total mixed ration for ad libitum feeding allowing 10% refusals. The groups’ Dry Matter Intake (DMI) was assessed daily. The Body Weights (BW) were recorded and jugular blood samples collected on days 0, 28 and 56. All claws of young bulls were examined every two weeks for an identification of claw lesions. Copper supplementation improved Average Daily Gain (ADG) and gain:feed (G:F;P < 0.05). Serum cholesterol decreased with Cu supplementation (P< 0.001). Serum Zn, Cu, and urea N were not affected by supplementation of Cu; however, plasma total protein (P< 0.001), and albumin (P< 0.001) were increased by a supplementation of Cu. The prevalence of lameness was 19.6% and control group had the highest Odds ratio (OR= 2.43). As a result, it is concluded that supplemental Cu might improve growth performance in the finishing bulls and decrease the prevalence of lameness.

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The green synthesis of nanoparticles is performed in a low-cost, environmentally friendly, and efficient manner. Compared to other methods of nanoparticle production, green synthesis has proven its superiority and unique benefits, eliminating the need for expensive, toxic, time-consuming, and undesirable methods. In this study, the green synthesis of silver nanoparticles using the extract of Tribulus terrestris was investigated. Tribulus terrestris is a medicinal plant used in traditional medicine to treat urinary and reproductive tract infections, especially burning, kidney stone elimination, relief of rheumatic pains, reduction of blood pressure, and stimulation of the liver. In this research, the morphology, size, and structural properties of nanoparticles were investigated using XRD, UV-visible, FT-IR, and SEM. Given the antibacterial and anticancer properties of the Tribulus terrestris extract and the importance of silver nanoparticles, the antimicrobial effects of silver nanoparticles were examined against a number of standard strains, as well as gram-negative and gram-positive bacteria. UV-visible spectroscopy revealed a peak in the 429 nm, indicating the presence of synthesized silver nanoparticles. The results of X-ray diffraction (XRD) also confirmed the formation of the crystalline structure of nanoparticles. The results of the non-growth halo diameter for Bacillus subtilis bacterium were more than that of Escherichia coli, in other words, Escherichia coli showed more resistance against synthesized nanoparticles. The results of this research show that the green synthesis of silver nanoparticles using milk thistle seed extract can be used as a suitable antibacterial agent against clinical pathogens.
 

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Metal bipolar plates are key components in fuel cells that are considered as the best alternative to replace graphite plates. Material selection in bipolar plates depends on its weight and corrosion resistance. Metallic bipolar plate can be considered as the best alternative instead of graphite and composite plates. One of the new processes in order to produce this plat is gas blow forming process. In this study, forming of AA8111 bipolar plates with 200 µm thickness in concave groove dies is investigated by gas blow forming process at various pressures (20, 30 and40 bar) and temperatures (300 and 400 ° C). The filling percent of die at various wall angles and depth to width ratios are examined. According to the dimension of channels, maximum and minimum thinning percentage at high temperature and pressure are investigated. Results show that at wall angle of ∝=0, and the depth to width ratio of h/w=0.5, rupture occurs at pressure of 20bar and at temperature of 300° C and at pressures of 20 and 40 bar at temperature of 400° C. The best channel filling with lowest thinning obtained at ∝=15 and h/w=0.5.

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In the present study, a new thermal comfort model based on cutaneous thermoreceptors has been developed by using non-Fourier heat transfer in biological tissue. The new model considers the concept of finite propagation speed of thermal disturbance by using non-Fourier equations. Since biological tissues consist of complicated and nonhomogeneous structure, the heat process is different from other materials. The dual phase lag (DPL) bioheat transfer model describes two time relaxations is a case of non-Fourier heat transfer application in biological tissue. In this study, the mentioned model has been utilized to evaluate the temperature distribution at the depth of skin thermoreceptors. The new thermal comfort model has been verified by comparisons with experimental data where a good agreement has found. As thermal response of the human cutaneous thermoreceptors depends on temperature and its change rate at the depth of thermoreceptors; therefore, it is very important to estimate these parameters with a good accuracy. In this paper, the previous models improved and effect of non-Fourier heat transfer on temperature derivative is investigated. It is found that the DPL model has a significant effect on change rate of temperature and thermal response of cutaneous thermoreceptors.

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Large-scale spatial skeletal structures belong to a special kind of 3D structures widely used in exhibition centers, supermarkets, sport stadiums, airports, etc., to cover large surfaces without intermediate columns. Space structures are often categorized as grids, domes and barrel vaults. Double layer grid structures are classical instances of prefabricated space structures and also the most popular forms which are frequently used nowadays.Topology optimization of large-scale skeletal structures has been recognized as one of the most challenging tasks in structural design. In topology optimization of these structures with discrete cross-sectional areas, the performance of meta-heuristic optimization algorithms can be increased if they are combined with continuous-based topology optimization methods. In this article, a hybrid methodology combining evolutionary structural optimization (ESO) and harmony search algorithm (HSA) methods is proposed for topologyoptimization of double layer grid structures subject to vertical load. In the present methodology, which is called ESO-HSA method, the size optimization of double layer grid structures is first performed by the ESO. Then, the outcomes of the ESO are used to improve the HSA. In fact, a sensitivity analysis is carried out using an optimization method (ESO) to determine more important members based on the cross-sectional areas of members. Then, the obtained optimum cross-sectional areas of members are used to enhance the HSA through two modifications. Structural weight is minimized against constraints on the displacements of nodes, internal stresses and element slenderness ratio. In topology optimization of double layer grid structures, the geometry of the structure, support locations and coordinates of nodes are fixed and this structure is assumed as a ground structure. Presence/absence of bottom nodes, and element cross-sectional areas are selected as design variables. In topology optimization of the ground structure, tabulating of nodes is carried out based on structural symmetry: this leads to reduce complexity of design space and nodes are removed in groups of 8, 4 or 1. The presence or absence of each node group is determined by a variable (topology variable) which takes the value of 1 and 0 for the two cases, respectively. The ground structure is assumed to be supported at the perimeter nodes of the bottom grid. Therefore, these supported nodes will not be removed from the ground structure. In order to achieve a practical structure, the existence of nodes in the top grid will not be considered as a variable. This causes the load bearing areas of top layer nodes to remain constant. Also, discrete variables are used to optimize the cross-sectional area of structural members. These variables are selected from pipe sections with specified thickness and outer diameter. Therefore, in topology optimization problem, the number of design variables is the summation of the number of compressive and tensile element types and the number of topology variables. The proposed approach is successfully tested in topology optimization problem of double layer grid structure. In particular, ESO-HSA is very competitive with other metaheuristic methods recently published in literature and can always find the best design overall. Also, it is determined that HSA method can find better answer in the topology optimization of large-scale skeletal structures, in comparison to optimum structures attained by the GSA and ICA.

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Mesoporous activated carbon production from lignocellulose waste for removing reactive dyes Blue 19 and Blue 21 from aqueous solution Introduction. Reactive dyes have been increasing in textile industries for dyeing natural and synthetic fibers. Discharge of dye- bearing waste-water makes an adverse effect on aquatic environment because the dyes give water undesirable color. The major environmental and health problems associated with water pollution caused by the discharge of untreated textile effluent are due to disorders in the aquatic environment because of use of toxic chemicals. The aim of this study was to investigate the adsorption potential of as-produced activated carbon from grape wood residue (Vitis Vinifera) in order to remove Reactive Blue 19 (RB19) and Reactive Blue 21 (RB21) dyes from aqueous solution. Activated carbon is the most common adsorbent for the removal of many dyes.Activated carbons are made from various agricultural wastes by physical and chemical activation. The preparation of activated carbon from agricultural waste could increase economic return and also provides an excellent method for the solid waste disposal thereby reduce pollution. Method: The adsorbates in this study included three reactive dyes, Reactive Red 23 (RR23), Reactive Blue 19 and Reactive Blue 21. All dyes were commercial grade and employed without further purification. The activated carbon was synthesized from grape wood biomass by activation of phosphoric acid (H3PO4) with impragnation ratios of 1:1 1:2,1:3, 1:4. The FTIR, BET, and SEM techniques were used to characterize the as-prepared carbon materials. In addition, dye adsorption experiments were carried out, which measurements are taken for all of the samples under in the same condition, at pH of 2, adsorbent dose of 0.01 g/l, initial dye concentration of 250 mg/l, sworking volume of 100 ml, and contact time of 120 min. Results and discussion: The results showed that the carbon sample activated under imprenation ratio of 1:4 and temperature of 600oC, that obtained a special surface area of 1850 m2/g, and total pore volume of 2.40 cm3/g, and pore size distribution of mesoporous at 86%, had maximum adsorption capacity of 1932 and 908 mg/g for RB19 and RB21 dyes, respectively. The adsorption behaviors of three reactive dyes (Reactive Blue 19 23, Reactive Blue 21) onto this biomass activated carbon were investigated in batch systems. The experimental data were analysed by the Langmuir, Freundlich and Sips models of adsorption. Equilibrium data of dyse fitted well with the Sips model. The rates of adsorption were found to conform to the pseudo-second-order kinetics with good correlation. The equilibrium adsorption capacity of the Activated carbon was determined with the Langmuir equation found to be 1914 mg/g for Reactive Blue 19 and 1195 mg/g for Reactive Blue 21. Conclusion: This study showed that activated carbon produced from annual pruning vineyards waste has a high potential in the treatment of textile wastewater. Also results indicate that Activated carbon from grape wood could be employed as low-cost alternative to commercial activated carbon in wastewater treatment for the removal of acid dyes. Keywords: Activated carbon, lignocellulose waste, Grape wood, Blue 19, Blue 21