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The purpose of this paper is to measure the degree of item difficulty in translation multiple-choice items in terms of 1-parameter logistic (1-PL) model of the item response theory (IRT). Also, the paper proposes a hypothesis in which a participant who answers a translation test possesses some amount of translation competence which affects the end-result.

In total, 150 translation students from the Bachelor of Arts in Translation Studies from the three Iranian universities participated in this research paper. The translation participants were requested to answer the questions. The items were formulated in such a way that the question was stated in English and the four choices were written in Farsi. To interpret the obtained results, this research paper employed 1-PL and 2-parameter logistic (2-PL) models using Stata (2016). In addition, to demonstrate results in terms of 1-PL, item characteristic curves (a graphical representation showing the degree of difficulty of each item) was used.

Using Stata platform, the findings of this research paper showed that through the application of IRT, evaluators were able to calculate the difficulty degree of each items (1-PL) and correspondingly the translation competence (2-PL) of each participant.

One of the limitations is the proportionately small number of translation participants at the Bachelor of Arts.

Although a few number of studies concentered on the role of translation competence, there did not exist any research focusing on translation competence empirically in higher education.

Increasing heat transfer rate in spiral heat exchangers is possible by using conventional methods such as increasing number of fluid passes and counter flowing. In addition, newer ideas such as using pillows as baffles in the path of cold and hot fluids and using nanofluids can increase heat transfer rate. The purpose of this study is to simulate turbulent flow and heat transfer of two-phase water-silver nanofluid with 0-6 Vol.% nanoparticle concentration in a 180° path of spiral heat exchanger with elliptic pillows.

In this simulation, the finite volume method and two-phase mixture model are used. The walls are subjected to constant heat flux of q″ = 150,000 Wm⁻². The inlet fluid enters curves path of spiral heat exchanger with uniform temperature T_in = 300 K. After flowing past the pillows and traversing the curved route, the working fluid exchanges heat with hot walls and then exits from the section. In this study, the effect of radiation is disregarded because of low temperature range. Also, temperature jump and velocity slipping are disregarded. The effects of thermophoresis and turbulent diffusion on nanofluid heat transfer are disregarded. By using finite volume method and two-phase mixture model, simulations are performed.

The results show that the flow and heat transfer characteristics are dependent on the height of pillows, nanoparticle concentration and Reynolds number. Increasing Reynolds number, nanoparticle concentration and pillow height causes an increase in Nusselt number, pressure drop and pumping power.

Turbulent flow and heat transfer of two-phase water-silver nanofluid of 0-6 per cent volume fraction in a 180° path of spiral heat exchanger with elliptic pillows is simulated.

In the present study, laminar steady flow of nanofluid through a trapezoidal channel is studied by using of finite volume method. The main aim of this paper is to study the effect of changes in geometric parameters, including internal and external dimensions on the behavior of heat transfer and fluid flow. For each parameter, an optimum ratio will be presented.

The results showed that in a channel cell, changing any geometric parameter may affect the temperature and flow field, even though the volume of the channel is kept constant. For a relatively small hydraulic diameter, microchannels with different angles have a similar dimensionless heat flux, while channels with bigger dimensions show various values of dimensionless heat flux. By increasing the angles of trapezoidal microchannels, dimensionless heat flux per unit of volume increases. As a result, the maximum and minimum heat transfer rate occurs in a trapezoidal microchannel with 75° and 30 internal’s, respectively. In the study of dimensionless heat flux rate with hydraulic diameter variations, an optimum hydraulic diameter (Dh) was observed in which the heat transfer rate per unit volume attains maximum value.

This optimum state is predicted to happen at a side angle of 75° and hydraulic diameter of 290 µm. In addition, in trapezoidal microchannel with higher aspect ratio, dimensionless heat flux rate is lower. Changing side angles of the channels and pressure drop have the same effect on pressure drop. For a constant pressure drop, if changing the side angles causes an increase in the rectangular area of the channel cross-section and the effect of the sides are not felt by the fluid, then the dimensionless heat flux will increase. By increasing the internal aspect ratio (t_2/t_3), the amount of t_3 decreases, and consequently, the conduction resistance of the hot surface decreases.

The effects of geometry of the microchannel, including internal and external dimensions on the behavior of heat transfer and fluid flow for pressure ranges between 2 and 8 kPa.

COVID-19 has affected most business activities, including technology-based business. The higher the business vulnerability rating, the greater the impacts. After identifying three dimensions of vulnerability (exposure, business sensitivity and response capacity), this study aims to determine the potential components and indicators of the vulnerability of technology-based businesses.

Using the indicator approach, a comprehensive vulnerability model was developed for assessing the vulnerability of the technology-based business against COVID-19.

In this study, COVID-19, as a biological threat and an exogenous shock, was considered the exposure dimension. Business characteristics, job characteristics, business owner-manager demographics, product and supplier characteristics were identified as the sensitivity dimension, while resources, human capital, technological capitals, social capitals, institutional capitals, infrastructures, management capacity and supply chain capabilities were defined as the adaptive business capability or response capacity. To determine vulnerability and response capacity against exogenous shocks and a pandemic crisis, the framework can act as a useful checklist for managers and owners of technology-based businesses.

Research on the COVID-19, especially in the technology-based business, is still at the emergent stage. This study is a pioneering effort to review the literature on business vulnerability and provide a framework to reduce business vulnerability using the indicator-based approach.

In recent years, neurophysiological tools have been vastly applied in sport marketing research. Eye tracking, a pervasive sensor technology, has received a growing interest to examine the effects of advertising through sport on viewer attention. While there is a plethora of evidence in advertising that supports the positive effects of various advertising types and locations on viewer attention in various sport contexts, little is known about the role of a prosocial overlay ad on viewer attention when watching televised football matches. Therefore, this research aims to examine the differences in viewers' attention (i.e. fixation and duration) with regard to game attractiveness and colors of the prosocial message during televised football matches.

To identify the research gap, the authors first reviewed the relevant sport marketing and neuroscience research on advertising effectiveness. The authors selected a prosocial message displayed. Adopting an experimental research design and using eye tracking, this study examined the impacts of game attractiveness and colors of message on viewer attention to the prosocial message displayed on an overlay advertisement during a football match.

The authors found that the colors of prosocial messages and game attractiveness had significant effects on viewer attention to the prosocial message.

In this study, the authors sought to add advertisement color, as well as game attractiveness, to the extant knowledge in marketing literature as effective advertising factors in capturing viewers' attention. These variables can offer marketers new insights in designing effective advertisements for the context of televised sports events in a specialized field.

Recognising the as-built state of construction elements is crucial for construction progress monitoring. Construction scholars have used computer vision-based algorithms to automate this process. Robust object recognition from indoor site images has been inhibited by technical challenges related to indoor objects, lighting conditions and camera positioning. Compared with traditional machine learning algorithms, one-stage detector deep learning (DL) algorithms can prioritise the inference speed, enable real-time accurate object detection and classification. This study aims to present a DL-based approach to facilitate the as-built state recognition of indoor construction works.

The one-stage DL-based approach was built upon YOLO version 4 (YOLOv4) algorithm using transfer learning with few hyperparameters customised and trained in the Google Colab virtual machine. The process of framing, insulation and drywall installation of indoor partitions was selected as the as-built scenario. For training, images were captured from two indoor sites with publicly available online images.

The DL model reported a best-trained weight with a mean average precision of 92% and an average loss of 0.83. Compared to previous studies, the automation level of this study is high due to the use of fixed time-lapse cameras for data collection and zero manual intervention from the pre-processing algorithms to enhance visual quality of indoor images.

This study extends the application of DL models for recognising as-built state of indoor construction works upon providing training images. Presenting a workflow on training DL models in a virtual machine platform by reducing the computational complexities associated with DL models is also materialised.

The current study aims to advance the research on the extra-industry network, innovativeness and performance of small and medium enterprises (SMEs) by examining the mediation role of proactiveness. The study also aims to examine the mediating role innovativeness between extra-industry network and performance.

This study used the proportionate stratified random sampling method to select the study sample and the questionnaire survey approach to 580 SMEs. A total of 150 completed questionnaires were returned. Partial least squares structural equation modeling was administered to analyze data via Smart PLS 3.0 software.

The results reflect that proactiveness is mediated by the relationship between the extra-industry network and the performance of Iranian SMEs. In addition, the results illustrated that proactiveness is mediated by the relationship between innovativeness and the performance. The findings also address the limitation of previous studies on Iranian SMEs through the independent examination of the mediating role of innovativeness between firm extra-industry network and performance.

This article is one of few attempts that have addressed the significance of proactiveness as the key mechanism to transform the advantages of extra-industry network and innovativeness relationships to enhance performance.

The purpose of this study is simulation of of polymer electrolyte membrane fuel cell. Proton-exchange membrane fuel cells are promising power sources for use in power plants and vehicles. These fuel cells provide a high level of energy efficiency at low temperature without any pollution. The convection inside the cell plays a key role in the electrochemical reactions and the performance of the cell. Accordingly, the transport processes in these cells have been investigated thoroughly in previous studies that also carried out functional modeling.

A multi-phase model was used to study the limitations of the reactions and their impact on the performance of the cell. The governing equations (conservation of mass, momentum and particle transport) were solved by computational fluid dynamics (CFD) (ANSYS fluent) using appropriate source terms. The two-phase flow in the fuel cell was simulated three-dimensionally under steady-state conditions. The flow of water inside the cell was also simulated at high-current density.

The simulation results suggested that the porosity of the gas diffusion layer (GDL) is one of the most important design parameters with a significant impact on the current density limitation and, consequently, on the cell performance.

This study was mainly focused on the two-phase analysis of the steady flow in the fuel cell and on investigating the impacts of a two-phase flow on the performance of the cell and also on the flow in the GDL, the membrane and the catalyst layer using the CFD.