Rainfall characteristics, which include spatial Variability, exert a major influence on runoff properties. Many techniques have been proposed for determining the spatial distribution of daily rainfall. One of these techniques is spatial Modeling, based on rainfall data measured by rain-gauge networks. In this study, application of different interpolation methods in the GIS environment, for estimating the spatial distribution of daily rainfall in the southwest of Iran with low rain-gauge density, have been compared on a regional scale. The cross validation technique was selected as an accuracy index and statistical parameters, such as MAE (Mean Absolute Error) and MBE (Mean Bias Error), were used for comparing the results of cross validation. The ranking of MAE and MBE values was used for determining the best interpolation method. The interpolation methods that were studied for mappingthe spatial distribution of daily rainfall include nearest point, moving average, moving surface, trend surface and kriging. Since the spatial pattern of daily rainfall is random, the moving average method, with inverse distance weight function, was determined as the best method for interpolating daily rainfall data in the region of study.

To model the spatial Variability of groundwater chemical characteristics, our research was performed using Geostatistic and deterministic methods. In our study, Na+, CI-, HCO3-2, total Cations, TH, SAR, EC and TDS from ground water characteristics were selected. At first, normality of data tested using Kolmogorov-Smirnov test, then we transformed EC, total Cations and TDS using logarithmic transformation. Variography and interaction variogram of data calculated. The result of estimated and expected amount using MAE and MBE were presented. Result showed significance of Geostatistical methods in comparison to deterministic methods and Cokriging increased result's precision. Cokriging is the best method for Modeling of Cl-, total Cations and TH. Disjunctive Kriging is the suitable methods for Modeling of HCO3-2 and Na+. Universal Kriging resulted best model for TDS. On the other hand ordinary Kriging is the best method for SAR Modeling.

Background and Aim: In patients with complete denture, some clinicians have used modelling plastic impression compound (MPIC) along tissue conditioner (TC) materials simultaneously. Little information is available on the composition of these materials and the interaction between them. The purpose of this study was to evaluate the influence of two components of MPIC on the structure and chemical composition of TC.Materials and Methods: In this experimental study, MPIC specimens were provided in 25×2 mm discs. Specimens were randomly divided into three groups and were immersed in ethanol 70%, plasticizer (dibutyl phthalate) and a mixture of them (ethanol 70% and dibutyl phthalate). All of the discs were weighed with a digital balance before and 2, 4, 6 and 24 hours after immersion. Values were analyzed by non parametric Kruskal-Wallis (a= 0.05) and SPSS 16 for Windows (SPSS Inc., Chicago, IL) was used for statistical analysis.Results: Statistical analysis indicated significant differences among all groups (p>.05).Conclusion: Dibutyl phthalate (DBP) had high impact on the solubility of MP, while the mixture of dibutyl phthalate (DBP) and ethanol demonstrated the highest impact.

Background and Aim: There are different methods of oral health education for child population. Theater show is a method that has not received enough attention until now. The aim of this study was to evaluate the effect of using theater show on dental health education in Yazd female elementary students.Materials and Methods: This was a quasi experimental study performed by using pre- and post-test method in Iran over the year 2004. One elementary school from each region of the city was selected. Twenty students from each grade of each school were included in the study (n=200). The information on knowledge, attitudes and practice of oral health were collected by using a valid and reliable questionnaire before and after theater show performance. Data were analyzed using SPSS and Wilcoxon signed rank test.Results: This study showed that the theater show could improve knowledge, attitude and proper oral health practice of children. The effect of the theater show on knowledge was more than attitude and was more on attitude than practice (P<0.001). Only literacy on the part of mothers was significantly correlated with practice (P=0.021). There were significant correlations between Knowledge (P=0.020), Attitude (P=0.0001) and oral health Practice (P=0.022) with students' grade level.Conclusion: This study showed that using theater show for oral health education, could improve the oral health related knowledge, attitude and proper oral health practice by elementary school students.

Severe and sudden floods have always led to irreparable damages, including the deaths of thousands and significant economic losses. Rapid flood zoning is one of the most important and fundamental aspects of crisis management and reducing flood-related damages. To mitigate risks, damages, and take timely action, it is essential to quickly identify areas prone to flooding and inundation and take necessary measures. In this study, a new user-friendly module of STE software was developed to solve shallow water equations more rapidly. By introducing and examining new grid discretization and subgrid Variability methods, the process of flood zoning and simulation has been accelerated. To evaluate the proposed methods, flood Modeling was conducted for the flooding event caused by Hurricane Harvey in 2017 in the vicinity of Hempstead city, Texas, USA, along a 22-kilometer stretch of the Brazos River. The comparison of results obtained from accurate and long-term flood Modeling using shallow water equations with the rapid methods presented in the study demonstrates that subgrid Variability methods can significantly reduce the Modeling time for flood simulation from 1090 minutes to 17 to 36 minutes (a 97% reduction) while maintaining Modeling accuracy. This is achieved with a flood zone accuracy of 94% and a root mean square error (RMSE) of 0.14 for flow depth Modeling.

Different types of contact, including contact between node pairs, any-contact of nodes, and contacts of the entire network, are used to characterize social relations in mobile social networks. Different modes of routing, from the point of view of message delivery semantics, encompass unicasting, multicasting, any-casting, and broadcasting. Studies have shown that using probability distribution functions of contact data, which is mainly assumed to be homogeneous for nodes, improves the performance of these networks. However, there exists an important challenge in studies on distributions. A lot of works apply the distribution of one type of contact to other types. Hence in routing applications, it causes to use of the distribution of one type of contact for any mode of routing. This study provides a complete solution to model each type of homogeneous contact data distribution and to use them in different modes of routing. We propose a routing algorithm that uses this new model. Results show that our solution improves the average latency of comparing methods Epidemic, TCCB, and DR about 3.5-times, 30%, and 45%, respectively. It achieves a delivery rate of about 5% and 6%, and average latency about 6% and 8% better than that of DR and TCCB, respectively.

A B S T R A C TFor choosing suitable place multiple methods are introduced, which examine the qualities, methods and patterns of location selection. The current methods use global approach and do not pay attention to spatial differences, environmental variation in variables, local changes modeled by local weighting indicators. It has been selected as a case study to evaluate the EMS center of Fars province and to evaluate the indicators of distance from the power plant, distance from logistics centers, industries, transportation terminals, hospitals, hotels and tourism, cities, rural areas and custom centers. has been used, using the AHP method to weight the qualities, and then for local weights, non-overlapping neighborhood filtering within a radius of 25 km are used and calculate the corresponding changes, quantity, ratio Presented in this article, the obtained weights, then the compute local weighted layers, and then local weight was multiplied in the normalized layers and the final layer were obtained. In the next step, it was combined and calculated to compare the data using the global method. The results of the two methods were transferred to the points of the EMS and the results were analyzedExtended AbstractIntroductionIn geographical studies and spatial planning, there are different approaches to choosing the right place for all kinds of applications and uses, and a process is followed to choose the best places. This process includes stating the research problem (cognition), choosing the criteria and preferences of decision makers and how to determine the weight of indicators, combining criteria (design) and finally, choosing the best option. In the current methods of spatial decision, the criteria are given a fixed weight, while in geographical locations, the distribution of geographical phenomena is not uniform. In this case, attention should be paid to the spatial distribution pattern of geographical phenomena based on the principle of sensitivity of the range of changes, the size of the range of changes affects the outputs, and the data with a smaller range of changes also have a lesser effect on the output. The data with a larger range of changes will have a more significant effect on the output. Therefore, in spatial analysis, indicators that have small changes are less important. Local models have been presented to model local changes in spatial multi-criteria decision-making; in this research, the main issue is how to model the local changes that affect the expected outputs. MethodologyThe research process is based on multi-criteria spatial decision-making methods (national and local). First, spatial patterns of indicators were analyzed through exploratory analyzes of ESDA spatial data. Then based on the review of the research criteria, the direct weighting method was used to calculate the weight of the indicators, and the experts were asked to specify the weight of the criteria in the range of 1 to 10. The opinions were combined, and the final weight was obtained. First, the data were spatially modelled to model and calculate the local weights. Then Block Statistics spatial filter without overlap was used to determine the neighborhood. The range of local changes, maximum and minimum values, were calculated, and local weights were obtained based on that. Finally, the information layers were descaled. After that, the unscaled criterion layers were multiplied by the national weights and the final national scores were obtained. In the next step, the data of the evaluated information layers (local and national) were transferred to the points of emergency databases. Based on the analysis, the fit was done. Results and discussionGeneral or global weights pay attention to the relative importance of indicators, which is the starting point for calculating local weights. Based on the research results, the most critical indicators are industries, cities and hospitals, which are more important in the location of road emergency stations. However, in order to achieve better results, it is necessary to build a local weight layer. The results of the research show that the indicators' weight and the difference in the criteria (general weight) are not equal in the entire geographical area, and the areas with a larger range of changes have a higher coefficient.Because, unlike general weights that are obtained based on different methods, local weights are estimated based on the principle of sensitivity of the range of changes and are changed spatially, and a fixed value is not considered for all areas. According to the research findings, the highest level in the general and local evaluation method corresponds to 0.5 to 0.7. Based on the local (geographic) weight method, it is less than the national or general method in the range of 0.9 to 1. Furthermore, this is due to the more precise nature of this method, which models the effects of local changes. To evaluate the compliance of the emergency centers with the final maps of suitability assessment, the information on the suitability maps was transferred to the map of the emergency center points of Fars province. Based on the evaluation of 207 emergency stations, according to the general method, 14 percent are in the high group (0.9-1), and according to the local or geographical method (16.9), percent are in this group. ConclusionAt the level of space and geographical regions, phenomena and geographical complications are not uniformly distributed, some phenomena have a homogeneous distribution, and some have a heterogeneous distribution. On the one hand, the phenomena and decision issues are affected by the context in which they are formed and evolve; on the other hand, these phenomena are placed in the network of mutual relations. Furthermore, the results of the set of phenomena may differ from the results of the phenomena individually and separately; in this article, an attempt has been made to address the issue that in spatial analysis and planning, it is necessary to pay attention to geographical differences in decision-making. Furthermore, it should not be evaluated in general terms of spatial decision problems; one of the methods of modelling these differences and spatial changes is to consider the local weight of the criteria. Based on the research findings, local (geographical) and national analysis results are different and can better show these changes. On the other hand, the pattern of spatial differences also has its spatial pattern, and paying attention to these differences in spatial differences can be the subject of further studies. FundingThere is no funding support. Authors’ ContributionAuthors contributed equally to the conceptualization and writing of the article. All of the authors approved the content of the manuscript and agreed on all aspects of the work declaration of competing interest none. Conflict of InterestAuthors declared no conflict of interest. Acknowledgments We are grateful to all the scientific consultants of this paper.

In this study, a robust computational method involving exponential cubic spline for solving singularly perturbed parabolic convection-diffusion equations arising in the Modeling of neuronal Variability has been presented. Some numerical examples are considered to validate the theoretical findings. The proposed scheme is shown to be an ε, −,uniformly convergent accuracy of order O((Δ, t) + h2) .