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The term “social responsibility” bears different meanings among nations. Most studies on corporate social responsibility are conducted in Western countries, and literature shows a dearth of scientific research on the subject in developing countries. Meanwhile, the public sector, with its essential role in national development and social welfare, has been the focus of limited studies on social responsibility. In Iran, as a developing country, the concept of social responsibility has not yet found its rightful place inside organizations and companies. Therefore, the purpose of this paper is to design a multi-level social responsibility model in the Iranian Social Security Organization (SSO), the largest public organization in the country.

In this paper, the thematic analysis was used along with interpretive structural modeling (ISM) to design a multi-level social responsibility model in a specific context. It was a field survey with 20 open interviews. The direct relationships between variables of different levels, identified via thematic analysis and ISM, were investigated in a study population of 510 SSO stakeholders using structural equation modeling (SEM).

In the designed model, service improvement and optional and voluntary activities variables were identified in the first level; economic and financial activities in the second level; political activities and education and research variables in the third level; and finally, laws and regulations, organizational components and organizational culture variables were identified in the fourth level. The results of SEM revealed the direct influence of all lower-level variables on their higher level counterparts, except the influence of laws and regulations on political activities. Based on the results, organizational components had direct effects on education and research (ß = 0.630), and political activities (ß = 0.341), the variable of organizational culture affected education and research (ß = 0.176) and political activities (ß = 0.613), the variable of political activities affected economic and financial activities (ß = 0.633), the variable of education and research affected economic and financial activities (ß = 0.381), the variable of economic and financial activities affected service improvement (ß = 0.925) and optional and voluntarily activities (ß = 0.877) and the variable of laws and regulations affected education and research (ß = 0.151).

The research results showed that social responsibility was a dynamic and context-based phenomenon, which should be used in accordance with the Iranian organizations and national conditions. According to the results, a qualitative research plan can give new insights into social responsibility through the phenomenological constructivism approach. Policymakers could perceive the subject better and take more effective actions by identifying the activities of social responsibility at the Iranian SSO from the perspective of key stakeholders and analyzing the interplay between them.

This model is the first designed and developed at the Iranian SSO by considering the expectations of major stakeholders affecting the SSO. Another advantage of this model is the use of qualitative approaches in model development, which increased integrity of the proposed model. Dimensions of the model showed the main bottlenecks hindering the realization of SSO responsibilities. Finally, this study recommends to the empirical researchers of social responsibility to consider the institutionalized conditions of every society in their work.

In May 2014, a new reform in the health sector of Iran was implemented called “health evolution plan.” In the first phase of this reform, the government reduced out-of-pocket payments for service delivery by paying subsidies to the services and after that a revision was done to the medical services values book to improve equity and increase motivation of health professions. One of the affected services in this reform was coronary artery bypass surgery. The purpose of this paper is to show the effects of HEP on costs of coronary artery bypass surgery.

A before-after study was done for this purpose and 167 patients’ total costs and out-of-pocket payments were calculated for the years 2013 (before) and 2014 (after) the reform in three private hospitals of Rasht city, Iran. Econometrics models were estimated after adjustment of confounding variables.

The results of this study showed that surgery costs increased significantly from $1,643.3 to 2,119.5. Nursing and other costs increased significantly from $290.3 to 414.2 and anesthetize costs increased from $619.2 to 947.01. The results of regression model showed that total costs increased $3,008.6 after adjustment of confounders (p-value=0.037). However, no significant changes were found for out-of-pocket payments and out-of-pocket percentage.

The study findings revealed that HTP was not successful enough in financial protection in the private sector.

Mental health is one of the most important factors for evaluating the health of different age groups in the community. The most common forms of mental health disorders are depression and anxiety. Health status of students as an important age group has positive consequences in the community. To provide special recommendations for preventing mental disorders, the purpose of this paper is to determine the correlations among the individualism and family orientation and mental health.

A meta-analysis was conducted to find scores of mental health. International databases of Scopus and PubMed as well as Iranian databases of IranMedex and SID were systematically searched in September 2014 for studies conducted on Iranian students. Of 379 reviewed studies, 58 were selected for meta-analysis. A meta-regression model was estimated to show the effects of individualism and family orientation on mental health.

Eight studies were conducted in Tehran. Eight studies were published in English. In nine studies, school students, and in one study both school and university students were surveyed. General Health Questionnaire-28 score varied from 13.77 in Arak to 47.78 in Tehran. The results of this study showed that the pooled mental health score for Iranian students was 23.725, indicating that Iranian students had poor mental health. In meta-regression, the coefficient of family orientation was −0.2893 and it was significant. Other variables did not have any significant relationship with mental health scores.

Improvement of living conditions and enabling the youth to positively communicate with different social groups are recommended.

The study aims to predict a low-velocity impact on a plate reinforced with carbon nanotubes (CNTs) using machine learning models.

The first-order shear deformation plate theory (FSDT) is used to express the plate displacements filed. The Hertz nonlinear contact law is used to predict the contact between impactor and plate. Using the energy method and Hamilton’s principle, the motion equations are extracted. The six main parameters considered as inputs to machine learning models are CNTs percentage, impactor radius, plate thickness, plate length and width, CNTs distribution profile and impactor initial velocity. These input parameters are used to predict two impact targets including contact force and contact time.

As the values of the targets are continuous, the machine learning task is considered a regression problem. Therefore, this study uses different regression models to predict the targets. These regression models include linear regression, stochastic gradient descent regressor, Bayesian regression, partial least squares regression, Gaussian process regression, multilayer perceptron regressor, support vector regression and decision tree regression. To validate the effectiveness of the regression models, experiments are designed based on different evaluation metrics. The results of the experiments demonstrate that the machine learning models achieve promising performance in predicting the contact force and contact time based on the input parameters.

Due to the volume of high numerical calculations of impact mechanics to reach the response, the targets of the impact problem are predicted using a variety of machine learning methods.

The purpose of this paper is to study the flow, heat and mass transfer of MHD Casson nanofluid due to an inclined stretching sheet using similarity transformation, the governing PDE’S equations of flow, heat and mass transfer are converted into ODE’S. The resulting non-linear ODE’S are solved numerically using an implicit finite difference method, which is known as Kellor-box method. The effects of various governing parameters on velocity, temperature and concentration are plotted for both Newtonian and non-Newtonian cases. The numerical values of skin friction, Nusselt number and Sherwood number are calculated and tabulated in various tables for different values of physical parameters. It is noticed that the effect of angle of inclination enhances the temperature and concentration profile whereas velocity decreases. The temperature decreases due to the increase in the parametric values of Pr and Gr due to thickening in the boundary layer.

Numerical method is applied to find the results.

Flow and heat transfer analysis w.r.t various flow and temperature are analyzed for different values of the physical parameters.

The numerical values of skin friction, Nusselt number and Sherwood number are calculated and tabulated in various tables for different values of physical parameters.

The study of the boundary layer flow, heat and mass transfer is important due to its applications in industries and many manufacturing processes such as aerodynamic extrusion of plastic sheets and cooling of metallic sheets in a cooling bath.

Here in this paper the authors have investigated the MHD boundary layer flow of a Casson nanofluid over an inclined stretching sheet along with the Newtonian nanofluid as a limited.