Background and Aim: Myocardial infarction (MI) is one of the leading causes of mortality worldwide. This disease imposes a high socio-economic burden on patients. Since the Spatio-temporal analysis of diseases plays an essential role in the design of prevention and management programs. The present study aimed to identify regional clusters of MI and also analyze the time trend of the disease among an Iranian military community. Methods: In this ecological study, all registered cases of MI from different provincial centers of the military community were studied during the period 2015 to 2018. The Getis-Ord Gi statistics were used to identify the hot spots of MI and the Spearman correlation coefficient to the trend of the disease. Results: The incident cases of MI in military officers and conscripts during the study period were 103 and 4, respectively. Gilan and Golestan provinces (90% confidence level) in 2015, Gilan, Golestan, Semnan, and Zanjan provinces (95% CI) and Isfahan province (90% CI) in 2016, Golestan province (95% CI), and Gilan province (90% CI) in 1396 and Golestan province (95% CI) in 1397 were identified as hot spots of the disease. The results of the temporal analysis also indicated a significant increasing trend of MI in military officers. Conclusion: The Northern regions of Iran are at high risk of MI, and the trend of the disease also demonstrates a significant increase. The findings of this study can be considered in policymaking in the field of public health of military communities for control strategies and preventive programs. In future studies, the risk factors and nonecological parameters should be addressed in hotspot regions.

Background and Objective: Having information about qualitative and quantitative parameters distribution of groundwater supplies is one of most important parameters in integrated groundwater management. Thus, in this study it has been attempted to determine a proper model and input combination for estimation of quality parameters including electrical conductivity (EC), calcium (Ca) and sodium (Na) ions in aquifers of Guilans plain. Method: In this study, the data from 132 observation wells during 2001 to 2013 were used and artificial neural network (ANN) and support vector model (SVM) were applied. In the first approach, estimations were conducted according to five different combinations, including water level, distance from see, total precipitation of six months and coordinates of observation wells. In the second approach, estimations were conducted based on combination of the selected qualitative parameters of gamma test with combinations of the best input in the first part. Findings: Comparison of the results from the first part indicated that SVM model outperformed the ANN mode in the estimation of Ca, Na and EC parameters. Support vector machine error values for estimating Ca, Na and EC variables at the test period were 1. 218 (meq/l), 0. 867(meq/l), and 175. 742 (μ mos/cm), while for artificial neural network these values were 1. 268 (meq/l), 0. 933 (meq/l), and 186/448 (μ mos/cm) respectively. The results from this part showed that adding the distance from see input improves the estimation of models in all cases. In the second part, using gamma test for measuring the nine quality parameters, the best combination of quality parameters was determined to estimate the three parameters: Ca, Na and EC. The results from the second part show that both ANN and SVM models have an excellent performance in the estimation of the three qualitative parameters. ANN model error values in estimating Ca, Na and EC variables in validation period were 0. 662 (meq/l), 0. 305(meq/l), and 47. 346 (μ mos/cm), while these values were 0. 671 (meq/l), 0. 356 (meq/l), and 55. 412 (μ mos/cm) for SVM model respectively. Obviously, the results from ANN model in this section were better than those from SVM model. Discussion and Conclusion: Results showed that both ANN and SVM models have a great ability in predicting qualitative parameters in the aquifers. Also, in less inputs, the results of SVM model are better than those of ANN model and in more inputs it is vice versa. Results of the second section showed that gamma test is fully practical and accurate in determining the effective input combinations.

In this paper, simulation-based (software-based) teaching of a 4-channel optical demultiplexer based on photonic crystal is presented by using the R-Soft software. The teaching of the demultiplexer structure is based on the use of a photonic crystal filter. In this analysis, with the variation of the radius of the cylindrical nano-ring resonator and the radius of the scattering rods, the critical length parameter of 1573. 6 nm is improved in the design of the filter. The advantages of the 4-channel demultiplexer include the mean quality factor of 4525, mean channel power transfer factor of 95%, and maximum and minimum channel cross-talk of-19. 6 and-40. 4, respectively. Also, mean channel width is obtained as 0. 375 nm. Moreover, the proposed 4-channel demultiplexer can be used in WDM systems. The simulation-based teaching of these structures is very important to develop and improve the multiplexers performance. Therefore, the related syllabus is suggested for master of science (MSc) students in Electronic Engineering major. This syllabus can be considered as a part of Photonic Crystal or Photonics courses.

Background and Objective: Surveying of Balekhloo River’ s water is necessary because it is one of the main branches of Gharasoo River in Ardabil and supplying water for Yamchi dam Due to the presence of contaminant sources such as wastewater, residential areas, and industrial, agricultural and mineral water, river morphology. Today evaluation of water quality based on macro invertebrates variety has completed chemical methods of pollution recognizes. Method: In this study water quality examination of Balekhloo River in Ardebil, macro invertebrates were sampled in 5 stations along the river in 2 times of year (low water season and high water season). For results’ simulation measuring of some physico chemical parametres were perfomed. Macro invertebrates were identified and evaluated with Shannon winner variety index, Margalef biotic index and Pielou similarity index. Findings: In this study, ten orders of invertebrates in 23 categories were identified and counted and result simulation laboratory measured of physico chemical parameters like DO, Nitrate, PH, Debi and velocity. Discussion and Conclusion: Results showed that there are similarities between physical, chemical and biological indexes and Margalef biotic index was known more suitable bio assessment index to determine water quality in Balekhloo River. Finally, by comparison of physical, chemical and bio index parameters of Balekhloo River’ s water quality was classified into three region low, moderate and high pollution.

Background and Objective: Vegetation that is commonly used in urban design has a significant impact on air quality in the urban canyons. Thus, planners should be aware of vegetation impacts. In Isfahan metropolis, though vegetation covers a considerable portion of the city, the streets are encountered with pollution problems. In this study, distribution of pollution in urban canyons is evaluated using an optimal model for pollution reduction. Method: A three-dimensional modeling software called ENVI-met along with local and sub-climatic air quality model based on CFD-computational fluid dynamics-is used to study the influence of vegetation on pollution level in urban canyons. In this study, first a sample of real field and next a simpler version of the selected area are simulated. Findings: Different parameters such as height to width ratio in urban canyons, density of trees, location of trees in the streets and gaps between the trees are evaluated. Conclusion: The obtained results show that the increase of wind velocity in the shallow valleys is at the the lower level and the absence of natural obstacles such as trees reduces the level of pollution due to the high velocity of wind at this condition. When trees are located in the center of urban canyons, pollution and tree distances are inversely correlated and pollution level reduces by increasing the distance between the trees. In the other words, the pollution that is caught by the tree canopies decreases with the reduction in tree canopies.