Mehdi Bahrami

The prominent characteristic of a delayed-choice effect is to make the choice between complementary types of phenomena after the relevant interaction between the system and measuring instrument has already come to an end. In this paper, we first represent a detailed comparative analysis of some early delayed-choice propositions and also most of the experimentally performed delayed-choice proposals in a coherent and unified quantum mechanical formulation. Taking into the account the represented quantum mechanical descriptions and also the rules of probability theory, we discuss that there are two fundamentally different descriptions concerning the physical mechanism of the delayed-choice between the complementary types of phenomena in these experiments. In this regard, we finally conclude that the delayed-choice experiments can be classified into two main groups where the temporal aspect of each group is characterized differently within their probabilistic descriptions

Nursing, a scientific and practical discipline, faces continuing challenges of finding new direction in order to decipher its core values and develop current ethical codes for nursing practice. In 2009–10, 28 nurses were purposely selected and interviewed using a semi-structured format in focus groups and individually. Thematic Content Analysis helped explore the perception of Iranian nurses on ethical values in patient care. Seven major themes emerged: respect for dignity, professional integrity, professional commitment, developing human relationships, justice, honesty, and promoting individuals and the nursing profession. Iranian nurses revealed a unique and culture-based set of ethical values. This study found that Iranian nurses place a greater emphasis on preserving the dignity of those accompanying the patient and in showing regard for patients' religious beliefs in a gender appropriate environment

Wheat is the most imperative crop for man feeding and is planted in numerous countries under rainfed conditions in semiarid zones. It is necessary for decision-makers and governments to predict the yield of rainfed wheat before harvest and to determine the effect of the major factors on it. Different methods have been suggested for forecasting yield with various levels of accuracy. One of these approaches is the statistical regression model, which is simple and applicable for regions with scarce data available. Since the weather is the most important factor affecting the production of wheat, particularly in rainfed cultivation, regression models using weather parameters are very common. However, the coefficients of these models are location based and should be determined locally. Therefore, in this research, backward multiple linear regression technique based on relative importance metrics was used to determine the most important effective weather parameters on rainfed wheat productions in Fars Province, south of Iran, during 2006–2013. The influence of each parameter in the final model was analyzed using the values of LMG relative importance metric. The result indicated that sunshine hours had the biggest LMG and, therefore, was the most effective parameter. Also, among the other considered parameters, rainy days, minimum relative humidity, and average relative humidity with LMG values of 21.97%, 21.69%, and 21.62%, respectively, had the most effects on rainfed wheat yield in the studied area. All parameters except for the sunshine hours positively affected rainfed wheat yield. The most important reason for the significance of these parameters can be the prevailing dry and semidry climate in the southern areas of Iran. The proposed model for determination of weather parameters effects on rainfed wheat could be a great guidance and aid for different stakeholders such as farmers, decision-makers, and governments.