درخت حوزه‌های تخصصی

In the present study, two different models of task complexity; namely, limited attentional capacity model and cognition hypothesis were examined. To this end, the manipulation of cognitive task complexity along +/- single task dimension on Iranian EFL learners’ production in terms of fluency was explored. Based on the results of the writing test of TOFEL (2004), 48 learners were selected as the participants of the study and were divided into two groups, simple task group (STG, n=24) and complex task group (CTG, n=24). The participants in the STG were given an eight-frame picture which had been arranged in the correct sequence before its administration (+ single task). The participants in the CTG were given all the eight frames which were not arranged in their correct order. These participants were required to order the frames in the right sequence first, before starting writing (- single task). Their output was encoded based on the measure of fluency. One independent sample t-tests was run.  The results indicated that the participants significantly generated more words in the complex task. Based on the findings, it can be concluded that in the Iranian context, the predictions of limited attentional capacity model were more accurate.

The agricultural drought, severely affecting human life, occurs unpredictably at different times with different intensities. The conventional methods for assessing drought often relay on indices obtained using meteorological data, but due to the low spatial coverage, incompleteness and inaccuracy of these data, meteorological indices cannot be considered as a comprehensive method. Therefore, it is suggested that remote sensing constitute more versatile approach, as it allows to assess the drought using the adequate spatial and temporal coverage for the study area. In the study, performed for the Panjshir river basin in Afghanistan, the 2010-2019 period is used to evaluate vegetation rate using NDVI data from MODIS. To calculate agricultural drought indices (DSI, VCI and TCI), May and June were selected, as the peak vegetation time occurs for these months. On the base of the remote sensing indicators it was shown that during the study period the drought conditions were normal in the region, except for 2011, 2017, and 2018, which were the driest years, and for 2019, which was the wettest year. Agricultural drought indices were compared to SPI index calculated using winter and spring precipitation data recorded at the meteorological stations. It was observed that the remote sensing indices showed the highest correlation with data from Kabul meteorological station, which is located at the same altitude and climate as the dense vegetation zone. Furthermore, the comparison showed that the ground precipitation data is characterized by higher amplitudes than the remote sensing data. From the above it steams that the vegetation in the Panjshir basin is influenced by both seasonal rainfall and rivers that continuously flood the area.

Rent-seeking in the trade sector is an outcome of restrictions imposed on tariffs and import quotas by a government. In an effort to acquire more privilege in foreign trade, labor allocates a part of its time-effort to rent-seeking activity, while cutting down on production work. Given the importance of rent-seeking activity due to restrictions imposed by the government in the Iranian economy, this paper has attempted to calculate the size of rent-seeking activity in the foreign trade sector of the Iranian economy. Hence, a version of the DSGE model has been specified and the related parameters have been estimated in order to calculate the rent-seeking rate. We have applied quarterly data from 1998:1 to 2015:4 for Iran’s trade sector, to obtain the empirical results through calibrating the specified DSGE model. The results have indicated that rent-seeking of Iran’s trade sectors amounted to 0.45, which looks considerably high. Moreover, labor has shared 24 % of its effort time to rent-seeking activity and 76 % to ordinary work.