The purpose of current study was to standardize the Persian version of coach-athlete questionnaire. All athletes and coaches participating in preparation camp prior to the Guangzhou 2010 Asian Games were formed statistical population of this research. They were belonged to group, individual, ball, racket, fighting, competitive and contact sports.80 coaches and 174 athletes were selected as samples by exhaustive sampling non-random design. Measurement tool used was coach-relationship questionnaire. Confirmatory Factor Analysis, Pearson Correlation Coefficient, Cronbakh’s Alpha, Split-half (Spearman-Brown Correction Formula) and test-retest statistical methods were used in order to measure research hypothesis, validity, reliability values, internal consistency and stability of the questionnaire respectively. Finally, Mean and Standard Deviation were used in order to determine the quantitative norm; Cut of Point (quartile deviation) was used to determine the Qualitative norm. The results showed that coach-athlete relationship questionnaire possessed validity, reliability and norm. Constructive equations were used for complementary findings and showed Goodness of fit of the current questionnaire.

Background: Birth spacing, especially the first birth interval (FBI), is a suitable index to investigate the delayed fertility that results in a low fertility pattern. Non-parametric familiar alternatives to the Cox proportional hazard regression (CPH) model include survival trees that can automatically discover certain types of covariate interactions according to the survival length. The aim of this research is to study FBI influential factors by applying survival trees. Materials and Methods: In this cross-sectional study, 610 married women (aged 15-49 years), were selected from different regions of Tehran, Iran in the Winter and Spring of 2017. Classification and regression trees (CART) for the FBI survival tree were fitted by taking into consideration the predictors of each woman’ s age, age at first marriage, educational level, partner’ s educational level, activity, region, house ownership, kinship, partner’ s race, marriage time attitude, and expenditure using R packages. Results: Since the PH assumption of the CPH model was not confirmed for the covariates of age at first marriage (P=0. 001), kinship (P=0. 000), partner’ s race (P=0. 001), and marriage time attitude (P=0. 042), the results of this model were not valid. Thus, a CART survival tree was fitted. The validity of the fitted model in assessing FBI was confirmed by the significant result of the log rank test (P<0. 01) for the terminal nodes and the value of the separation measure, which was greater than 1. The fitted tree had 13 terminal nodes and the most vital FBI predictor was women’ s age. The longest FBI belonged to educated and employed women, ages 30-37 years. Conclusion: Analysing patterns of birth spacing by selecting the appropriate statistical method provides important information for health policymakers. In order to formulate appropriate demographic policies, it is essential to take into consideration age, educational level and job status of the women, all of which have essential roles on their decision to have children.

Extended abstractIntroductionGully erosion is a water erosion that has a great contribution to land degradation and is known as one of the most important environmental hazards in the world and especially in Iran. In recent years, machine learning techniques and geographic information systems have been highly effective in determining areas sensitive to gully erosion and have increased accuracy and speed in the evaluation and potential of gully erosion and in determining effective factors on gully erosion has also been effective. The loess lands of Golestan Province are more susceptible to water erosion due to sufficient depth and almost uniform silty graining, excessive use, cultivation on sloping lands, and wrong land management so that all types of erosion can be observed in these areas. The most common type of erosion in these sediments is gully erosion. The studied watershed is faced with the increase of dry and abandoned land, land use change, the presence of surplus livestock in the forests, and also the population increase. Therefore, this area is facing an increase in sensitivity to gully erosion, and areas with the potential for gully erosion should be identified and managed. Materials and methodsThe studied watershed with an area of 222,000 ha and an elevation range of 58 to 2168 m is located in the northeast of Golestan Province. The average rainfall of the area is between 224 and 736 mm. In this research, first, the location of the gullies was obtained from the General Directorate of Natural Resources and Watershed Management of Golestan Province. Then, from the total of 1127 gullies position, 70% were randomly classified as training data and 30% as validation data. To determine the effective variables in gully erosion sensitivity, 14 factors were identified and in the next step, the collinearity test between the variables was performed using SPSS software. By using the indices of tolerance coefficient and variance inflation factor, if there is collinearity between the variables, they were removed from the modeling process. Considering the importance of the DEM map and its application in the preparation of various factors of the current research, a DEM was prepared using ALOS satellite images. The layers of slope and aspect are prepared by using a digital elevation model and slope and aspect functions respectively. Slope length index in SAGA GIS software, layers of distance from stream based on the map of stream, and distance from roads based on existing roads, and using the Euclidean distance function in the ArcGIS software was prepared. Stream density and road density layers were obtained based on the map of existing streams and roads in the region and using the line density function in ArcGIS. The lithology layer was extracted from the geological map of the region and the land use layer was obtained from the General Directorate of Natural Resources and Watershed Management of Golestan province. The rainfall map has been prepared using the information from 35 rain gauge stations. First, the average rainfall of 26 years was calculated for each station, and then rainfall zoning was done using the global Kriging Method (due to the lowest RMSE) in ArcGIS. The TPI layer was prepared using the DEM and using the SAGA GIS software. The HAND index is a topographic-hydrological index of the DEM of the nearest drain, representing the hydrological behavior of the watershed. To evaluate the models, the relative performance detection curve (ROC) was used for the predictive power of the models.  Results and discussionThe results showed that there is no co-linearity between the variables and therefore all the variables were used in the modeling process. The relationship between gully erosion and elevation showed that lower elevations are more sensitive than higher elevations and more susceptible to gully erosion near waterways. The results showed that with the increase in drainage density, the sensitivity of gully erosion increases, and the possibility of gully erosion increases. The results showed that the old barracks, shale, and loess have the greatest impact on the sensitivity of gully erosion. The results show a decrease in the sensitivity of gully erosion with a decrease in the HAND index. This result indicates that in the areas where the level of saturation in the watershed level increases, the possibility and sensitivity of gully erosion increases. The results showed that among the types of land use, canals, poor pastures, and agricultural land use have the highest sensitivity to gully erosion. This is even though the forest areas have the lowest sensitivity to this erosion. The results showed that in the rainfall range of 220 to 420 mm, the possibility of gully erosion has increased, and the range of 420 to 500 mm has shown the highest level of sensitivity, and with the increase of rainfall from 500 mm to above, a reduction in the sensitivity of gully erosion has been encountered. One of the reasons for reducing the sensitivity of gully erosion in higher rainfalls is the increase in vegetation and the creation of suitable conditions for landslides. The results showed that the depth of the valley up to 235 meters have increased the probability of gully erosion, and from 235 meters above, it has decreased the probability of erosion. The results showed that the sensitivity of gully erosion increases near roads, and this case shows the effects of road construction and the aggravation of conditions for gully erosion. ConclusionThis research was conducted to determine the effective factors on gully erosion and zone its spatial distribution in the northeast of Golestan Province. In this study, by considering 14 important factors and using RF, ANN, and CART models, a sensitivity map of gully erosion was prepared. Because the identification of gully erosion-sensitive areas based on traditional methods and expert opinions do not have acceptable accuracy, it is necessary to use modern machine learning methods. The results showed that the factors of distance from the road and land use are the most important factors affecting the sensitivity of gully erosion, which requires land use management as human activities. The ROC curve showed that the accuracy of the models in estimating areas with gully erosion sensitivity was excellent in the test stage (ANN) and very good in the test and validation stage (RF and CART), which means the excellent performance of the models.

Background and Objective: Discriminant analysis and logistic regression are classical methods for classifying data in several studies. However, these models do not lead in valid results due to not meeting all necessary assumptions. The purpose of this study was to classify the number of Children Ever Born (CEB) using decision tree model in order to present an efficient method to classify demographic data.Methods: In the present study, CART tree model with Gini splitting rule was fitted to classify the number of CEB in fertility behavior of at least once married 15-49 year-old women, in Semnan-2012. 405 women aged 15-49 years old comprised the survey sample.Results: Women in first and second birth cohorts who had married at an early age had 3 CEB while women who had married at an older age had 2 CEB. Women in third birth cohort who had married at an early age and were employed, had 2 CEB while unemployed women in this cohort whose type of marriages were familial and non-familial had 0 and 1 CEB respectively. Women in the third birth cohort who were married in older age had 1 CEB.Conclusion: Among important advantages of CART model are the simplicity in interpretation, using distribution-free measures, considering missing data and outliers for construction trees which has increased the usage of this method. Therefore, this method is a suitable way for classifying demographic data in comparison to other classical modeling methods in the conditions that necessary assumptions are not met.

Bridge pier scouring is one of the most important fields in hydraulics and river engineering, especially due to loss of life and property caused by bridge failure. Many experimental equations have been previously proposed to evaluate bridge pier scouring, most of which could not accurately simulate scoring depth because of complexity of the phenomenon. The present study, in this regard, compares two nonparametric CART and M5’ models having tree-structure and dividing the problem space into several branches. CART model offers a scalar quantity for each branch while M5’ model could provide equations as a result of bridge scour for different branches. Mixture densimetric particle Froude number, pier shape factor and ratio of flow depth to pier width were taken into account as input parameters in this research. Pier shape factor has been chosen as the first decision variable in both models that reflects the importance of this parameter on scour depth, corresponded to previous equations from the literature. Statistical analysis on proposed models and previous equations indicated that the nonparametric models could predict scour depth around piers with more precision. Discrepancy ratio was one of the statistical tests used in this research, indicating more than 65% accuracy for the tree-based models against other equations having less than 50% accuracy. Same results were observed from other statistical tests such as RMSE and R2. Finally, in comparison with CART model, M5’ was recommended for estimating of scour depth according to its simple structure. Also based on sensitivity analysis on M5’ model, pier width, flow depth and velocity had the highest impact on scour depth, respectively.

Communities Advancing Resilience Toolkit (CART) is a comprehensive surveying tool for assessing the community's resilience and identifying the strength and challenges of the community towards resilience capacity. The study assessed the community resilience of the hazard-induced urban community in Nigeria. The version of CART adopted enlisted 27 items of core community resilience and community attributes which represented critical components in an urban community and were randomly administered among urban dwellers. Survey outcome deduced that the domain "connection and caring" was deduced as the community resilience strength domain (mean= 3.18, SD= 0.38). In contrast, the item deduced as the strength of the community was "people feeling of belonging in the community", with the highest agreement of 63.3% (mean= 3.63, SD= 1.35). The domain "disaster management" was deduced as the community resilience challenge (mean= 3.06, SD= 0.63), while the item deduced as the challenge of the community was "community has services and programs to help people after a disaster", which recorded the lowest agreement and highest disagreement of 69.3% (mean= 2.13, SD= 1.13). The community attribute assessment items indicated that "necessary healthcare services availability" has the highest agreement (61.3%, Mean= 3.48, SD= 1.25) while the item "availability of leadership opportunities in the community" has the lowest agreement (42.7%, Mean= 3.32, SD= 1.24). Expanding the surveying process of the CART application can provide key information in a resilient building; hence, the need for continuous improvement on such application to further improve the study of community resilience.