درخت حوزه‌های تخصصی

University students are exposed to stress because of their age and their particular situation. Stress can cause serious problems to the health and academic performance of students. One of the factors affecting stress is the environment. Therefore, finding ways to reduce stress in universities is important and needs to be investigated. Unfortunately, one of the fundamental problems of universities is the lack of features and qualities of a space that reduces the stress of students. This means that university spaces are not designed and constructed for reducing the stress of students and enough attention was not paid to this issue. The relative lack of research in this field makes necessary to pay attention to this issue and carry out studies in this regard. The purpose of this study is to provide effective spatial features to reduce the stress of university students and to determine the effectiveness of each of these features. The research is conducted by survey method and Delphi technique was carried out in three rounds. For this purpose, firstly open-ended questionnaires were distributed among the experts. Then the answers were investigated and the lists of features were extracted. In the next step, based on the information obtained, close-ended questionnaires were made and the importance levels of features were put into question among the experts and then data were analyzed using SPSS software. In the final stage, experts expressed their final opinions considering the statistical results of the previous stage. The results of this study showed that effective spatial features on stress reduction of students are classified by influencing level into four categories of environmental conditions, natural factors, environmental comfort and physical aspects. And among the details of these features, adequate and proper light for spaces”, connecting with outdoor and semi-outdoor spaces and desirable sound in spaces, are of utmost importance.

Background and purpose: Managers’ competencies leave a decisive effect on the mental health of staff. The present research intends to investigate the influence of emotional-social competencies on the mental health of the staff. Method: the current research is practical in its purpose and correlative regarding data gathering. The statistical community included all the staff of Pegah Company in District 3, which were 221 persons selected through simple random sampling. The assessment tools of this study were standard Boyatzis questionnaire for emotional-social competencies of managers from the staff’s point of view and Goldberg general health questionnaire for the mental health of the staff. The validity (content, convergent, divergent) and reliability (load factor, composite reliability, and Cronbach’s alpha coefficient) were employed which indicated that assessment tools have acceptable validity and reliability; and the gathered data were analyzed by SMART-PLS2 and descriptive statistics with SPSS21. Findings: the outcomes of this study indicate that t coefficient ranges between emotional-social competency, emotional competency and social competency with the mental health which were respectively 7.46, 5.21, and 10.46. Also, the values of R2 coefficient of determination were 0.71, 0.67, and 0.54 respectively which are desired results. It shows that emotional-social competency, emotional competency and social competency leave positive and significant impacts on mental health. Conclusion: the results of this study attests to the importance of managers’ emotional-social competency for mental health of staff. Thus, the organizations should employ some strategies for the managers to acquire emotional-social competencies and accordingly improve mental health of staff and attain organizational goals.

Iranian formal censuses indicate that the share of rural population in total population of Iran have been decreasing over the time and many villages are uninhabited. Migration statistics in Iran have also indicated intense migration from villages to the cities during the past half- century. Many researches have been conducted due to the importance of rural-urban migrations, during the past few years. Therefore, the main goals of this study are to criticize and evaluate the written articles using meta-analysis method in rural-urban migrations field and to identify the most important factors affecting rural-urban migrations, widely used theoretical approaches in this area and etc. The findings of this research show that attraction and repulsion viewpoint and Michael Todaro&rsquos theory are appropriate theoretical approaches to state the problem of rural-urban migrations in Iran. Also, urban attraction variables with impact size of 0.75 and occupation with impact size of 0.62 have the most effect on rural-urban migration. Other findings indicate that the most solutions proposed in the reviewed researches are general, vague and non-executive and there is no proportionality between the proposed solutions and the study objectives in most cases.

No unique method has been so far specified for determining the number of neurons in hidden layers of Multi-Layer Perceptron (MLP) neural networks used for prediction. The present research is intended to optimize the number of neurons using two meta-heuristic procedures namely genetic and hill climbing algorithms. The data used in the present research for prediction are consumption data of water subscribers in Fasa City of Fars Province (Iran) between the years 2010 to 2013. Ultimately, using the respective data set, the data of the subsequent year 2014 can be predicted. In the present research it was observed that the mean square errors of per data (MSEPD) for the abovementioned algorithms are less than 0.2, indicating a high performance in the neural networks’ prediction. Correlation coefficients using genetic and hill climbing algorithms were respectively equal to 0.891 and 0.759. Thus, GA was able to leave a better effect on optimization of neural network.

One of the most important issues in today&rsquos urban world is increasing use of cars and its noise pollution, which is now one of the most important affecting pollutants on health and quality of lives of residents in urban areas. Noise pollution effects on various aspects of human and the community health as well as the high cost of treatment, thus more studies in this field is needed. Hence the importance of this study is to measure noise pollution caused by traffic and its impact on public health and mental health of the citizens in Qom. The study method was field studies and library. The data obtained over a period of three months regularly studies from the streets of Qom and using the B & K-2230, Quest-2900 and dosimeter. Overall, the results indicate that almost in all streets, noise pollution rate is higher the standard level. Among these the Imam Khomeini Avenue, 19 Day, Eram, and Enghelab streets have more noise pollutions. Noise pollution reflects is determined by field studies. Analyzing the questionnaires distributed among residents of adjacent streets, the results show that there are mild to severe illness and eventually decrease mental and general health of nearby residents in the streets.