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Classroom interaction improves the learning process by enhancing opportunities for learning since both instructors and learners are involved in various speech acts. Speech act refers to a functional unit in the form of an act assisting individuals to perceive or promote things with words in interaction. Thus, the current study investigated classroom interaction in terms of types and functions of speech acts performed by Iranian English as a foreign language (EFL) teachers and learners. The data for the study came from audio-recording of twelve 90-minute sessions taught by six experienced Iranian teachers. To analyze the conversational data, Finocchiaro and Brumfit’s (1983) model was used to examine various types of speech acts and Walsh’s (2006) SETT was employed as a framework to explore the functions of speech acts. Following the data analysis, it was unfolded that directives were the most frequent speech acts, including suggestions, requests, warning, and giving instruction, accompanied by interpersonal and personal ones. As to the functions of speech acts, the most frequent mode was the materials mode (42%), followed by skills and systems mode (34%), classroom context mode (16%), and managerial mode (8%). The overall findings indicate the central role of the teacher in teacher-fronted classes in Iran as the most speech acts, i.e. about 79%, were performed by teachers in the form of requestive, suggestive, and advisory to control and promote the learning process. By carrying out the current study, it is hoped that readers gain more insight regarding the pragmatics territory, most notably speech acts.
 

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During a study on fauna of the frit flies (Diptera: Chloropidae) in Khorasan Razavi province (Iran) in 2014 and 2015, nine species of six genera were collected and identified. Platycephala rugosa (Nartshuk, 1964) is recorded for the first time for Iranian fauna. Geographical distribution and biological notes are provided.

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Cellular energy allocation (CEA) test was performed in order to investigate the effects and costs of bare carbon nanotubes (CNTs) and CNTs in combination with titanium dioxide nanoparticles (CNTs/TiO₂-NPs) on Glyphodes pyloalis Walker after 24, 48 and 72 hours of exposure to 100, 200, 300, 400 and 500 ppm of the treatments. Results showed the negative correlation between total lipid amounts and concentrations of treatments (i.e. CNTs and CNTs/TiO₂-NPs) as well as exposure time. Contrary to CNTs treatments, carbohydrate contents were affected by both of CNTs/TiO₂-NPs concentration and time of exposure. Results showed that the effect of bare CNTs in the enhancement of glycogen content appeared significantly faster than that of CNTs/TiO₂-NPs. Increasing time of exposure to all concentrations of CNTs, except for 100 ppm, prevented enhancement of protein content. The effect of bare CNTs on the reduction of protein contents was faster and greater than that of CNTs/TiO₂-NPs. The results indicated that G. pyloalis cannot regulate internal CNTs and CNTs/TiO₂-NPs concentrations efficiently without considerable impact on the energy reserves (Ea). The comparison of energy consumed (Ec) in treated larvae showed that CNTs/TiO₂-NPs reflected the higher energy demand of the stress response than CNTs. Generally, CEA was significantly decreased as the concentration of CNTs treatments increased. More reduction in CEA amount of all treatments by CNTs/TiO₂-NPs than that of the control is also probably considered as a cost to deal with detoxification when the concentration increased and at all the tested time points. Therefore, CEA test might be considered as an early biochemical biomarker for assessing immediate response of organisms after acute exposure to stressors and thus could be applied to risk assessment of nanomaterials.

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Organophosphates (OPs), one of the most important pesticide groups, are used worldwide to control pests. Acetylcholinesterase (EC 1.14.18.1) (AChE), an enzyme from insects’ nervous systems, is the leading target site of this group of pesticides, such as Acephate. Inhibition of enzyme activity through Acephate-derived compounds can control both resistant and non-resistant pests to OPs. In this research, the toxicity of these compounds was assayed regarding the control of Xanthogaleruca luteola (Muller). Results of the in vivo screening test revealed that two derived compounds of phosphorhydrazides (PHA) (i.e., NH₂-C(O) NH-NH P(O)(OC₆H₅) and OC₄H₃-C(O)NH-NHP(S)(OCH₃)₂) showed the most significant insecticidal potential. AChE was purified and isolated from the third instar larvae of elm leaf beetle, X. luteola, using affinity chromatography. IC₅₀ values, inhibition mechanisms, and inhibitory constant (Ki) of NH₂-C(O) NH-NH P(O)(OC₆H₅) and OC₄H₃-C(O)NH-NHP(S)(OCH₃)₂ as inhibitors were calculated for the purified AChE. These compounds inhibited acetylcholinesterase (AChE) and general esterases of third instar larvae of elm leaf beetle. These compounds, by mix inhibition mechanism, inhibited AChE enzyme, and K_i obtained was 1.16 and 0.88 µM^-1 min^-1 for NH2-C(O) NH-NH P(O)(OC6H5) and OC4H3-C(O)NH-NHP(S)(OCH3)2, respectively. QSAR study based on multiple linear regressions (MLR) and principal component analysis (PCA) showed that the non-descriptor net charge of the nitrogen atom influenced by the polarization of N-H group had the most significant effect on the insecticidal potential. Therefore, designing new compounds that control the N-H polarization of the nitrogen atom could be an excellent option to study insecticidal properties of Acephate-derived compounds.
 

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It is commonly thought that when a work goes through retranslation process, the latest ones are expected to contribute to a better understanding of the text. However, it is not always the case, at least in Iran.  The book market of Iran is replete with retranslated versions of classic works most of which are not genuine translation but plagiarized version of previous translations. One famous example is George Orwell’s Animal Farm which has been translated into Persian more than 70 times by different translators since 1348. Regarding this issue, the present study attempts to investigate four Persian translations of Animal Farm based on forensic linguistics framework. The main goal of the present research is to demonstrate the patterns of plagiarism detection between different versions of translations of the same original piece of work based on textual similarities and differences. The project primarily centers on this question: what linguistic criteria are determinant in detecting plagiarism in translated texts? For our analysis, the data of the present research has been elicited from four Persian translations of this novel chosen by a time-lapse of 20 years between translations. Data were analyzed based on plagiarism detection patterns introduced by Turell (2004). The results of the study revealed a case of plagiarism among investigated translations. Disputed text overlaps 73.5% and 42.6% with plagiarized text in terms of vocabulary and phrasal similarity, respectively. In terms of unique vocabulary, they show the proportion of 17.6% to 15.16%. The disputed and plagiarized texts also have 35 shared-once only words and 22 shared-once only phrases. The article concludes that the proposed quantitative criteria of Turell’s model perform well in plagiarism detection which replicates the results of previous studies. We believe that science society of Iran must pay more attention to plagiarism in order to find a solution to suppress publication and proliferation of the plagiarized texts.
 

 
 
 
 
 

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The cabbage aphid, Brevicoryne brassicae L. (Hemiptera: Aphididae), is an important pest of canola that can considerably limit crop production through direct or indirect damage. In this study, the effects of Azadirachtin, Tondexir, Palizin, and Thiamethoxam, common insecticides used in managing the cabbage aphid, were investigated on the population growth parameters of this pest. Based on the results, the LC₅₀ values for Thiamethoxam, Palizin, Azadirachtin, and Tondexir were 0.19, 0.63, 1.00, and 3.82 g/L, respectively. Moreover, LC₃₀ concentrations of Thiamethoxam, Palizin, Azadirachtin, and Tondexir were 0.11, 0.10, 0.41, and 1.68 g/L, respectively, applied in the sublethal studies. The cabbage aphids reared on the plants treated with these insecticides had lower longevity, fecundity, and reproductive period than the control treatment. The intrinsic rate of increase (r_m), finite rate of increase (λ), net reproductive rate (R₀), and generation time (T) were lower on Thiamethoxam treatment. Tondexir and Palizin treatments had lower values than Azadirachtin. However, there was no significant difference between the Tondexir and Palizin treatments. The population treated by Azadirachtin had the highest values of growth parameters. According to the results and available information in the context of risk assessment of the studied insecticides, this research recommends the application of Thiamethoxam in the integrated pest management of cabbage aphid.

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 The toxicity of chlorpyrifos to three Iranian populations of two-spotted spider mite, collected from Isfahan (ISR), Yazd (Yz) and Guilan (GUS2) Provinces were surveyed using the residual contact vial bioassay. The bioassay results showed that resistance ratios of ISR and Yz populations were 176.90 and 9.78 fold compared to the GUS2 population, respectively. Determination of esterase and glutathione-S-transferase activity and their kinetic parameters showed that ISR population had the highest specific activity and specificity constant among the studied populations. Besides, the content of mixed function oxidases in ISR population was the highest. However, synergistic effects of Piperonyl Butoxide, Diethyl Maleate and Triphenyl Phosphate showed that metabolic enzymes did not play an important role in resistance to chlorpyrifos in ISR and Yz populations and enhanced activity of esterase, glutathione-S-transferase and content of mixed function oxidases in these populations were probably due to resistance to some other acaricides. To determine the role of acetylcholinesterase insensitivity in resistance mechanisms, kinetic parameters and inhibitory effect of chlorpyrifos-oxon on this enzyme were investigated. The K_m value of acetylcholinesterase was determined as 0.036, 0.04, and 0.050 mM using acetylthiocholine iodide for GUS2, Yz, and ISR populations, respectively. In addition, the insensitivity ratios of chlorpyrifos-oxon on acetylcholinesterase activity were estimated at 23.30 and 2.96 for ISR and Yz populations, respectively. These results confirmed amino acid substitutions in active site of this enzyme and also indicated that resistant population possed qualitatively altered AChE.

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Application of chemical pesticides has increased significantly worldwide and has raised serious concerns about environmental pollutions. One of the encouraging trends to minimize pesticide risk is production of resistant plants containing toxic proteins against insect pests. Considering the importance of purification and characterization of digestive enzymes in the production of resistant plants, in this study an α-glucosidase from the Naranga aenescens Moore's midgut was purified by ammonium sulfate precipitation, ion exchange chromatography on DEAE-sepharose, and concentrating through ultrafiltration. The apparent molecular mass of the enzyme was 48 kDa determined by SDS-PAGE. The optimum pH and temperature of the enzyme were 6.0 and 45°C, respectively. The irreversible thermoinactivation of the enzyme showed that it was highly stable at 35ºC but moderately stable at 40 and 45ºC. Zn²⁺, Hg²⁺, Co²⁺ at 10 and 20 mM, and Ba⁺²only in 20 mM strongly inhibited the α-glucosidase activity. Ba²⁺ and Ca²⁺ only at 10 mM, EDTA and Hg₂²⁺ only at 20 mM and Mg²⁺ at 10 and 20 mM significantly increased the enzyme activity. The K_m and K_cat values for the α-glucosidase were 0.54 mM and 3.62 min^-1, respectively, when p-Nitrophenyl-α-D-glucopyranoside (pNαG) was used as a substrate.

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Air pollution as a silent murderer of metropolitan areas demanded huge amounts of attractions. During the past few decades, after London 1954 black days, the world encountered a novel problem which was made by anthropologic actions. Scientific researches for scrutinizing the air pollution and its effects on humankind and the environment, started and improved after chronic influences of contaminations which in this era prognostication of pollutants and finding the relationships between parameters out, seems to be undeniable. Ozone as a tropospheric gas, has severe impacts on the all creatures while the human beings are more delicate in conjunction with this gas where it can destroy ability lungs and cause asthma and other pulmonary diseases. In the present article, the two most prevailing approaches for prediction, applied to the forecast tropospheric ozone value considering eight other photochemical precursors and meteorological parameters. Sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO) and particulate matters (PM2.5, PM10) as photochemical precursors, and also humidity, air temperature and wind speed as meteorological parameters, after data preparation, used for ground level ozone prognostication in Tehran, Iran, with a condensed population where suffers from severe air contaminations and high rate of daily death, related to the air pollution. Used data series, have been collected from 22 regions of the cited city during 2 years (2014 and 2015). Two evaluation criteria, root mean square error (RMSE) and correlation coefficient (R), selected for comparison of applications. Support vector machine (SVM) and artificial neural networks (ANN) as capable soft computing approaches which have been used in numerous areas of science, opted in this research. Support vector machine with classification of other eight parameters and by 286 vectors as a classifier and 97 border vectors, sorted the 70 percent of data sets as training and the residual amount of parameters used as testing data sets. Radial basis function (RBF) selected as Kernel function. Artificial neural network works as like as human brains and neurons between layers transfer datasets and process them during the run time, where in the recent paper the layer number of the created network is one for hidden layer and one for the output layer and 10 neurons have been selected for hidden layer and one for the output layer. Network type of this system is feed-forward with back propagation and TRAINLM used as training function and LEARNGDM used for adaption learning function. Both approaches depicted reliable and acceptable results, where RMSE and R values for support vector machine, respectively 0.0774 and 0.8456, also artificial neural network resulted 0.0914 for RMSE and 0.8396 for R, which are reasonable outcomes. As the outcomes for training datasets were better than the results for testing datasets, both approaches showed acceptable performances because of over-training controlling, which is a serious and prevalent difficulty of soft computers. Support vector machine, with lower root mean square error and higher correlation coefficient selected as better application for ground level ozone prediction. These series of studies are supportive for calibration of measuring systems and due to their expensiveness, soft computing is the most reliable and affordable substitute for the past machines. Also the analysis of tolerances among the parameters illustrated that CO, Temperature and NO2 are the most effective where, PM2.5 had the least amount impact on O3 forecasting process.