Golestan Province is one of the most vulnerable areas to catastrophic flood events in Iran. The flood severity in this region has grown dramatically during the last decades, demanding a major investigation. Accordingly, an authentic map providing detailed information on floods is required to reduce future flood disasters. Three ensemble models produced by the combination of Evaluation Based on Distance from Average Solution (EDAS) and Multilayer Perceptron Neural Network (MLP) with Frequency Ratio (FR), and Weights of Evidence (WOE) are used to quantify the map flood susceptibility in Golestan Province, in the north of Iran. Ten flood effective criteria, namely altitude, slope degree, slope aspect, plan curvature, distance from rivers, Topographic Wetness Index (TWI), rainfall, soil type, geology, and land use, are considered for the modeling process. The flood zonation maps are validated by the receiver operating curve (ROC). The results show that the most precise model is MLP-FR (AUROC = 0.912), followed by EDAS-FR-AHP (AUROC = 0.875), and EDAS-WOE-AHP (AUROC = 0.845). The high accuracies of all methods applied to illustrate their capability in predicting flood susceptibility in future studies.

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This study investigates the distributions of velocity and Reynolds stress in an artificial pool-riffle sequence for two entrance slopes of 5° and 20° in a laboratory and compares the results with a similar pool-riffle sequence in a gravel-bed river in central Iran. Quadrant analysis is applied to find out the contributions of different events on turbulent flow structures. At an entrance slope of 5°, the velocity distribution follows an exponential trend without flow separation, but for the entrance slope of 20°, the velocity distribution indicates a S-shaped pattern with flow separation. Variation of entrance slope does not influence the convex form of Reynolds stress (RS) distribution, but it influences the location of the maximum value of RS and the flow separation zone length. The results reveal that outward and ejection are the dominant events for both field and laboratory settings. The sweep displays a decreasing trend from near the bed toward the water surface, however, the outward contribution indicates an increasing trend from the bed toward the water surface. The agreement between laboratory and field results in velocity and Reynolds stress will help the river engineers to better manage complex fluvial processes. Bursting process events depend on the aspect ratio for the same entrance pool slope. The agreement in the results of velocity and Reynolds stress distributions and the dominant events of bursting process in the laboratory and field are encouraging for better restoration of rivers and decreasing the cost of projects.

Background & Objective: Long non-coding RNAs play critical roles in the initiation and development of gastric cancer (GC). The aim of this study was to assess the expression of NKILA and NFKB genes and the relationship between their expressions with clinical characteristics in gastric cancer. Also, relative expression of lncRNAsNKILA, compared NFKB in GC tissues was evaluated. Materials & Methods: This cross-sectional study was performed on 50 gastric formalin-fixed paraffin-embedded tumor tissue samples and 50 normal tissues. The RNA level of lncRNAsNKILA and NFKB genes was assessed using the quantitative real-time polymerase chain reaction. B2M was used as an internal control. The 2 -ΔΔCq method was used to determine the expression fold changes. Results: A significant association was observed between the levels of NKILA, in gastric tumor tissues compared with normal tissues (Mean = 2.087, p= 0.0484). The relative expression of the NFKB gene revealed no statistically significant difference between the gastric tumor tissues compared with normal tissues (P=0.3728). In addition, clinicopathologic data compared with NKILA and NFKBmRNA expression levels in gastric cancer tissues showed no significant association. Here, we found no significant association between the level of NKILA expression compared with NFKB mRNA level in gastric cancer tissues (R=0.03; P=0.2355). Conclusion: Our results showed that NKILA had a significant association with GC. Our findings also revealed that NKILA expression was not correlated with NFKB mRNA level in GC tissues.