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Wind as a major source of renewable energy has received tremendous attentions due to its unique features to reduce carbon emission and also to keep the environment safe. Nevertheless, to use wind energy properly, the environmental circumstances and geographical location related to wind intensity should be considered as a priority. Different factors may affect the selection of a suitable location for developments of wind power plants; thus, these factors should be considered concurrently to identify the optimum location of wind plants.

In this study, first, basic data envelopment analysis (DEA) was used, then dual DEA was used and, finally, Anderson Petersen (AP) model of dual DEA was selected to prioritize cities or decision-making units (DMUs). Numerical Taxonomy (NT) method was also used to assess the validity of AP dual model in DEA. The prescribed approach was applied for five cities in East Azerbaijan province of Iran.

The results indicate that wind power as a renewable energy can be harnessed in few cities, and the ranking by DEA illustrated that the city of Tabriz is the first priority.

Low environmental degradation effects in comparison to other methods and the ability to utilization at a widespread level include the benefits of using wind energy in the generation of electricity. In this regard, the study of relevant potentials and finding suitable locations for the deployment of wind energy utilization equipment are essential. Using DEA method helps us to choose optimal locations according to different criteria.

Wind energy is justifiable in reducing social costs in comparison with fossil fuel plants, which includes negative effects, and its electricity can be used as a sustainable energy in the country's economic, social and cultural development.

For identifying the most proper location for development of wind power plants in Iran, DEA is applied for the first time to prioritize the suitable locations for installations of wind turbines among five different cities in the East Azerbaijan region. A number of crucial factors including land price, distance to power, rate of natural hazards, wind speed and topography are considered for location optimization of wind turbines for the first time. Also, to validate the results of DEA method, NT method is used to assess the validity of AP dual model in DEA.

The aim of present study was to integrate vital noncommunicable diseases (coronary artery disease, hypertension, diabetes mellitus and mental health disorders) into Prison-Based Active Health Services Provision (PAHSP).

On Jan 1, 2018, there were 230,000 prisoners in Iran. Timely and systematic detection and diagnosis of chronic health conditions among this population are imperative. The collaboration between healthcare providers in prison and members of the multidisciplinary team of the healthcare community outside prison initiated an active health service provision approach for HIV and tuberculosis (TB). Guidelines for the control of HIV and TB in prison were piloted, and the finalized version was named “Prison-based Active Health Services Provision” (PAHSP), which has been scaled up in 16 of 260 Iranian prisons.

The PAHSP approach emphasizes the importance of early identification of key symptoms and risk factors. This approach provides an opportunity for improved prevention and treatment, enabling prisoners identified at risk or those who have been diagnosed with a target disease to be followed up and receive the appropriate health care.

Initiatives such as screening for chronic health conditions coupled with treatment will reduce the burden of chronic illness among prisoners and the broader community, thereby saving on healthcare costs and lives.