فهرست مطالب mohammad reza godarzi

 Social capital, by encouraging people to collaborate and engage in social interactions, has been considered as an effective factor for development of mental disorders. In the preset study, we aimed to investigate the relationship between different aspects of social capital and psychiatric disorders in children and adolescents.

 This study was conducted between 2016 and 2017 in Kohgiloyeh and Boyer-Ahmad province, Iran. A total of 1001 children and adolescents aged 6-18 years and their parents were randomly selected using multistage cluster sampling to participate in the study. The data in the present study were compiled using a Persian translated version of the Kiddie-SADS-Present and Lifetime Version (K-SADS-PL) semi-structured questionnaire as well as the Social Capital Questionnaire of Nahapiet and Ghoshal. The raw data were analyzed statistically using Fisher and chi-square tests. The statistical analysis was performed using SPSS 16.0 version.

 Our results show that better relationship, cooperation, mutual understanding, and commitment are significantly and inversely correlated to psychiatric disorders among children and adolescents. In this regard we found that the mutual understanding (P=0.008) and relationships (P=0.001) are strongly related to social capital, while other components may have more or less effects.

 Our findings show that various aspects of social capital are associated with development of psychiatric disorders in children and adolescents. Some of the social capital components including better relationship, cooperation, mutual understanding, and obligation have significant effects; however, others including networks, values and trust could not exert significant effects on mental health.

 Given the growing rate of psychiatric disorders, especially in young populations, detailed data on frequency of these disorders for further national public health strategiesis of great importance.We aimed to survey the frequency of different psychiatric disorders among children and adolescents in Kohgiloyeh and Boyer-Ahmad province.

 1001 cases were selected using the random cluster sampling method and all cases were interviewed by expert psychologists using a Persian version of semi- structured K-SADS-PL questionnaire. Data were then statistically analyzed by SPSS software.

 20.5% (205 out of 1001) of studied cases showed at least one psychiatric disorder and 79.5 % showed no sign of any disorders. Anxiety disorders were the most frequent disorders  (15.5%) followed by the behavioral disorders (7%), smoking and drug abuse (6%), behavioral disorders (2.4%) and neurodevelopmental disorders (2%), but no case was observed with psychosis.

 in comparison with other studies from Iran or other countries the prevalence of psychiatric disorders in Kohgiloyeh and Boyer-Ahmad is relatively high and special policies and efforts are suggested for enhancement of mental health values in this region.

In the next decades, climate change is likely to have become a serious challenge that will alter flow regimes such as torrential flows (floods), low flows as well as the existing water resources. Climate change impact is increasingly becoming a subject matter for researchers, but the effect of this phenomena on the low flow is still not widely understood. The consequences of climate change have led the international community to further studies, which will affect the changes in the natural resources, ecosystems, and the population. Global climate cycle has been found to be intensified due to climate change, as well as it has led frequent, severe, long-term, and stable droughts in many regions. Changes in the precipitation and temperature as two major variables in the hydrological cycle will unbalance the rainfall. Also, climate change in the future decades will be very effective on high flows and low flows so that it will have a significant impact on the results of the intensity and recurrence Interval of low flows. The aim of this study is to evaluate the effects of climate change on the low flows using HEC-HMS model, as well as changes in the flow regime such as low flow frequency, the probability, and the recurrence Interval of low flow in the future period (2040-2069). Also, the uncertainties related to the downscaling methods are considered by using two statistical methods (SDSM model) and the change factor as well as it has utilized the outputs of the General Circulation Models, which are resulted from the fifth report of the IPCC. Material and methods: The Gharesou Sub-basin is located in the northwest of Karkheh basin. It covers an area of 5354 km2 and its maximum and minimum height is 3364 and 1180 m, respectively. The average annual precipitation varies between 300 and 800 mm. Three major rivers of Merck, Gharesou, and Razavar are flowing into this basin. This study has measured the project of climate change in the Gharesou basin with CANESN2 and RCP scenarios and by using SDSM downscaling model as well as using change factor downscaling. Also, the indices of low flow frequency and FL method on the flows of the future period were analyzed. GCMs are the first tool for understanding past climate variations and predicting the projection for future climate conditions. GCMs demonstrate the atmosphere and ocean in a grid of 1 to 4 latitude degrees and in a longitude from 10 to more than 200 layers vertical in each fluid. Because of the spatial and temporal scale mismatch between the GCMs’ ability and the need of hydrological modelers, the outputs of these models cannot be explicitly used in climate change studies. Various methods of downscaling are used to overcome the problem, which dynamic, statistical, and change factor are three types of downscaling. The low flow selection is done by two different methods that are 7Q10 and FL methods. In fact, FL method is one of the five groups, which has been used in low flows and/or management balances of St. Johns River in Florida. Minimum Flows and/or Levels are low flows or levels that are needed to avoid serious damages to water resources caused by water withdrawals and they are divided into five following groups of flows. The first step in selecting the low flow is done by providing long-term flow data using FL method and then drawing the FDC curve. A low flow is obtained by drawing an FDC curve. FL method was chosen in order to select the low flows on the basis of the following reasons: 1. 7Q10 method for the extreme conditions of low flow, which is appropriate between 95 to 99% of the flow duration curve time. This condition usually occurs during a short-term severe drought and a very high recurrence Interval. 2. FL method is within the low flow selection domain and FL groups are clearly determined the effects of low flow on the floodplain, animal and plant life and ecosystems. The results of statistical method showed that basin flow has been reduced in all of the scenarios during the dry season, including July, August, and September. In addition, the results of the change factor suggested an increase in flow in the November, December, January and February and its decrease in the spring and summer. It is critical to note that both of downscaling methods indicated flow reduction in the low flow period. The value of the 7Q10 index in the statistical method and change factor has reached respectively, about 0.008 m3/s and zero in the future period while this value in the corresponding historic period was respectively 0.724 and 1.429 m3/s. Also, the Q80 index has reached the value between 0.1 and 0.3 m3/s using both of downscaling methods. Generally, the results indicate a severe low flow condition in the future period

Inaccuracy in earth fill dam’s analysis is one of the most important reasons of breaking this huge structures. assuming soil saturated only and disregarding time in rapid drawdown analysis cause errors in results of analyses that this article discuses about them. In this article Gulak earth fill dam has been modeled in three situations named saturated only, saturated-unsaturated with linear and nonlinear functions and the results show that modeling dam in saturated only situation not only effects on seepage results, but also causes about 25 percent error on safety factor of dam. In the fallowing this result achieved that by using nonlinear functions for permeability and vol. water content and choosing required parameters for van genuchten equation from laboratory result accuracy of analyses increases about 13 present than using a linear function. Also In rapid drawdown analysis to avoid shocking to the model, by using a transient analyze, drawdown of the reservoir was modeled as a process depending on time and results show that disregarding the time in rapid drawdown of reservoir analysis cusses about 4.8 percent error that this error increases to 13 percent by reducing drawdown rate.