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It is important to understand professors’ beliefs to promote better teacher preparation and professional development, as well as to understand the potential discrepancy between stated versus observed beliefs. The purpose of this study was to describe the faculty members' beliefs about the teaching-learning process.

A qualitative method was used to study the professors’ beliefs by selecting the faculty participants via a purposeful sampling strategy. The study was conducted at one of the biggest universities in Iran. In total, 20 professors were interviewed.

Analysis of the interviews indicates that professors’ beliefs about teaching and learning activities fall under four main themes (beliefs about teaching methods, beliefs about curriculum design, beliefs about students and beliefs about evaluation) and nine sub-themes.

Our findings reveal that professors have a deductive approach to teaching and learning, and due to the centralized educational system, they do not play a significant role in effectively presenting the curriculum. It seems necessary to direct professional development programs in rebuilding the professors' professional beliefs and identity.

The purpose of this study was to provide a model for informal workplace learning. Despite the prevalence and recognized importance of informal learning in the workplace, scattered literature and different perspectives have caused a lack of shared understanding about its nature, and little research effort has been made in this direction so far.

This paper identified the most significant components of informal workplace learning using the qualitative meta-synthesis method. For this purpose, after searching sources from different databases and screening them, 17 sources were selected due to compatibility with the research criteria. The texts extracted from the sources were analyzed using a thematic analysis method and synthesized using an aggregation approach. Finally, a themes network was created as a model with 8 main components and 11 sub-components.

The results indicated that eight components were considered significant to informal workplace learning, including learning stimulus, awareness and intent to learn, action or experience, critical reflection on action, facilitators, collective learning, self-directed and context.

This meta-synthesis contributes to the coherence and integration of the informal workplace learning literature. The obtained conceptual model, in addition to the general components of informal workplace learning, provides an explanation of the characteristics of each and the relationships between its components to achieve a complete understanding of the nature of informal workplace learning. Since no study has been done so far to comprehensively identify the most significant components of informal workplace learning, it is not possible to refer to their results in comparison with the results of this study.

The aim of this study was to determine the number of shelters, specify some optimal paths among building blocks towards shelters, and assign population to shelters.

Imperialist competition algorithm (ICA) and particle swarm optimization (PSO) were used to optimize the objectives of this study.

The optimal value for PSO objective function was with the number of function evaluations (NFE) of 5300 and the optimal value of ICA objective function was with NFE of 1062. Repetition test for both algorithms showed that imperialist competition algorithm enjoys better stability and constancy and higher speed of convergence compared to particle swarm algorithm. This has been also shown in larger environments. 92% of the existing populations have access to shelters at a distance of less than600 meters. This means that evacuation from the building blocks to shelters takes less than 8 minutes. The average distance from a block (for example, a residential complex) to an optimal shelter is approximately273meters. The greatest risk of route and shelter has been 239 and 121, respectively.

To address these goals, four following objective functions were considered: a) minimization of the distance for getting all the people to shelters b) the lowest total risk of the discharge path c) minimization of the total time required to transfer people to shelters or hospitals if necessary, and d) the lowest total risk in shelters.

Over the recent decades, the frequency of so-called ‘natural’ disasters has increased significantly worldwide and resulted in escalating human and economic losses. Among them, the earthquake is one of the major concerns of the various stakeholders related to urban planning.

In addition, the maximum time of discharge from the helter to the hospital has been 17 minutes, which means the presence of good access to selected shelters.

The purpose of this paper is to provide a Monte Carlo variance reduction method based on Control variates to solve Fredholm integral equations of the second kind.

A numerical algorithm consisted of the combined use of the successive substitution method and Monte Carlo simulation is established for the solution of Fredholm integral equations of the second kind.

Owing to the application of the present method, the variance of the solution is reduced. Therefore, this method achieves several orders of magnitude improvement in accuracy over the conventional Monte Carlo method.

Numerical tests are performed in order to show the efficiency and accuracy of the present paper. Numerical experiments show that an excellent estimation on the solution can be obtained within a couple of minutes CPU time at Pentium IV‐2.4 GHz PC.

This paper provides a new efficient method to solve Fredholm integral equations of the second kind and discusses basic advantages of the present method.

This study investigates consumers' willingness to adopt genetically modified foods (GM) and the role of innovation and behavioral determinants.

A new integrated model that expands the Health Belief Model (HBM) into the Innovation Diffusion Theory (IDT) was developed and examined. A total of 241 consumers were selected from the capital of Iran, Tehran, through a multistage random sampling. The data were analyzed using SEM-PLS modeling.

The extended HBM model was able to predict about 84% of the variance changes in consumers' willingness to adopt GM foods. The effects of net benefit and perceived compatibility on the willingness were also significant. In addition, the mediating effect of compatibility on the relationship between net benefit/self-efficacy and willingness to adopt GM foods was also significant.

This study contributes to the literature by developing the HBM into the IDT to assess consumers' willingness to adopt GM foods.