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Writing assessment literacy(WAL) for second or foreign language (L2) teachers, which refers to teachers’ knowledge, conceptions, and practice of writing assessment in L2 contexts, has lately received attention from scholars. Although there has been significant debate about the impact of contextual and conceptual factors on teachers’ assessment literacy, studies focusing on how such factors influence teachers’ WAL are lacking. The purpose of this qualitative study was to explore the way Iranian English writing teachers' conception of assessment, and macro, meso, and micro contextual variables impact their writing assessment practice. It also looked at how writing teachers make assessment decisions in order to negotiate and find a compromise when their assessment views and beliefs diverge from the assessment policies in their local contexts. The data was collected through semi-structured interviews with ten in-service l2 writing teachers in Iran. The findings show that participants had positive conceptions about formative writing assessments but they stated that they mostly used summative assessment in writing classes. Macro level contextual factors turned out to mostly impacted teachers’ writing assessment practices and conceptions. The results underscored the role of school and work experience in shaping and changing writing assessment conceptions. The findings of this study contribute to our current understanding of WAL development and provision of more efficient assessment training for language teachers in teacher education programs.

 

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Problem: This article unfolds a collective educational journey that while initially faced by serious doubts, ultimately received positive feedback from the students in an online urban design workshop.  During a rampant global pandemic, one of the two instructors communicating from overseas, who is experienced in teaching face-to-face courses, raised initial pedagogical concerns.
Aims: To remedy these, the two instructors dedicated the first part of the workshop to theorizing urban complexity.  Exposure to theory, while less common if not uncommon in design studios, removed the students’ initial misgivings.  Gaining student confidence boosted their spirit in crafting idiosyncratic interpretations based on personal memories, and paved the way toward assuming agency, and subsequently integrative learning.
Methods: This technique enabled students to connect discrete structural learning domains to produce more complicated outcomes, and by doing so experienced three states of mind.  Melting away initial doubts coincided with thematic arrangement.  Boosting confidence through conceptual connectivity and self-discovery, then, resulted in ebullience in designing through purposeful action.
Result: This article contributes to the scanty literature on coping mechanisms in the face of looming uncertainties both for students and instructors in teaching studios.

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Research subject: In recent decades, hybrid optimizations methods based on natural phenomenon have placed special position according to their capabilities in finding optimal solutions without expensive computational loads and disassociation on choosing initial points. Artificial Neural Network is used as one of the powerful tools of Artificial Intelligence for process simulation. The employment of the neural network in the modeling of m-Cresol alkylation process of with isopropanol as well as meta-heuristic methods in obtaining the optimal conditions for the catalyst and the reaction can prepare an effective step towards a high efficiency process.
Research approach: In the present study, the artificial neural network is applied to model alkylation of m‐Cresol with isopropanol process. In addition, the bee colony is employed in order to optimize the process yield. To verify its performance, the proposed method is used in prediction of the m‐Cresol conversion and Thymol selectivity of the alkylation process with isopropanol 120 data. In this process, the input variables are Weight Hourly Space Velocity (WHSV), pressure and temperature; m-cresol conversion and thymol selectivity are considered as the output variables of the neural network. Five hidden neurons are considered for the proposed neural network. 120 data is used to train the neural network. The meta-heuristic approach based on bee colony (BC) is applied to maximize the yield of the process.
Main results: The results confirm that the proposed method develops the accurate model with an R² value of greater than 97.5%. The maximum yield is obtained 28.9% by bee colony algorithm with adjustable variables that are WHSV of 0.062 hr^-1, the pressure of 1.5 bar and the temperature of 300^oC. In addition, in order to achieve the better performance of the optimization algorithm, the appropriate values of acceleration coefficient and population size are chosen 100 and 10 during the trial-and-error phase.

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Subject
Petroleum coke calcination is a chemical process during which the petroleum coke loses moisture and volatile combustible materials due to the increase in temperature and ultimately improves the physical properties of the calcined coke. In this study, A 2-Dim model was developed for the petroleum coke calcination process via rotary kiln using the CFD approach. Understanding the temperature, concentration, and fluid movement behavior are the main goals for developing the simulation model, by using which the rotary kiln control and design can be performed.
Methodology
Comsol Multiphysics was applied to develop the simulation model. Petroleum coke rotary kiln calcination consists of two solid and gas phases, which cross each other counter-currently. All governing physics in the system, including chemical reactions, heat transfer via conduction, convection, and radiation, intra-phase and interphase mass transfer, evaporation or evolution of components from the solid phase into the gas phase, fluid turbulency and all complex relationships were considered. Using the finite element method, the governing equations of the model were solved, and consequently, the variation of temperature, components concentration, and fluid velocity was calculated.
The main results
It is concluded that tertiary air injection significantly affects the temperature profile and combustion reactions in the bed (About 100 degrees increase in temperature). In addition, the maximum temperature of 1910 °C has been achieved in the kiln. Concentration changes of components in the gas phase were also seen mainly in the bed entrance and in the areas near the tertiary air injection. Comparing the results with similar works showed the high accuracy of the developed model

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Based on the early theories of the foreign direct investment (FDI), trade and FDI are substitutes while the new international trade theories emphasize the complementary relationship between trade and FDI. This introduces new aspects to model fundamental concepts such as increasing returns to scale, product differentiation, and technology differences among countries. This paper is an empirical study of the interaction between trade and FDI using data on inward FDI to the ECO and D8 countries. To end this, we use instrumental variable and generalized two-stage least squares (G2SLS) techniques for panel data models. The results show that there is a complementary relationship between trade and FDI. Moreover, GDP, exchange rate, population, inflation, and some convergences variables have significantly influence on trade and FDI.

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In this investigation, for the first time, used from Cross Accumulative Roll Bonding to produced Al/Cu/SiC composite. Microstructure and mechanical properties of produced composite were evaluated by using of optic microscopy, scanning electron microscopy, uni-axial tensile test, microhardness, respectively. Results of microstructure showed that after eight pass, has a perfectly uniform distribution of reinforcing and strong bond between particles. Tensile strength fell at the first and then continuously increased. Also trend of tensile strength and elongation was similar. Microhardness value for aluminum and copper layers of produced composite 1469% and 163% enhanced compare to annealed samples, respectively. Investigation of tensile fracture surface after eight pass showed that the mechanism of fracture in shear ductile for Al matrix.

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Expansion, utilization and distribution of potential economic opportunities among people have important impacts on the prosperity of each country. Simon Kuznets was the first researcher who systematically examined the relationship between economic growth and income distribution based on the statistical data. According to Kuznets, income inequality will decrease by economic growth in the long term. Therefore, economists focused on economic growth in order to reduce income inequality. However, the Kuznets hypothesis was faced with a serious challenge by publication of Piketty's “Capital” in the twenty-first century. Since, according to Piketty, not only income inequality has not diminished, but also it has increased unprecedentedly in the advanced stages of economic growth and development. In this regard, the aim of this study is to investigate the Thomas Piketty's hypothesis based on the statistical evidence of Iran by using the ARDL econometric method during the period 1975-2015. The results confirm Thomas Piketty's hypothesis according to statistical evidence of Iran. In addition, the effect of non-oil GDP on income inequality is negative and significant, but the impact of oil revenues is positive and significant. War has also led to increased income inequality.

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In this research, vinyl ester matrix composite coatings reinforced by E-glass fibers, Nano TiO_2, and Carbon Nanofiber were prepared by hand lay-up method and their mechanical properties were investigated. The mechanical properties of fiber-reinforced composites were investigated by the tensile, impact, hardness, shear test, and wear tests. Scanning electron microscopy was employed in order to study the fracture surface of the prepared samples. The results of the tensile test showed that the presence of the E-glass fibers in the vinyl ester matrix increases the strength about 4 times and the elongation about 8 times. There was no change in the fiber-reinforced composite strength by reinforcing the composite with nanoparticles of TiO₂ and carbon Nanofiber, but the elongation of the fiber-reinforced composite increased by 1.6 times. Impact resistance of fiber-reinforced composite and fiber-reinforced nanocomposite relative to vinyl ester resin increased about 20 and 29 times. The presence of glass fiber and Nanoparticles in the vinyl ester matrix increases the hardness of the samples about 1.5 to 2 times. The results of the adhesion test demonstrated that the presence of nanoparticles in fiber-reinforced nanocomposite improves adhesion to concrete surfaces. Also, the results of the wear test showed that the presence of glass fiber in the matrix of vinyl ester reduces wear resistance and the presence of Nanoparticles in fiber-reinforced nanocomposite improves wear resistance of the fiber-reinforced composite.