Nanoclay Performance on Resistance of Clay under Freezing Cycles

This study aims to investigate effect of nanoclay on resistance of the exposed clay soils in freezing in vitro conditions. The clay sample was selected from the considered land. Then they were mixed on water in 1.5, 3, 4.5 and 6 percents as well as without nanoclay. There were prepared cylinders with 3.81 cm diameter and 7.62 cm height, which they have been placed in conditions without freezing, one cycle, two cycles and three cycles of freezing. Then they were tested under uniaxial experiment. Then they were analyzed by SPSS software. The results show that adding nanoclay with 1.5, 3, 4.5 and 6 percents will reduce soil strength during freezing cycles. It can be occurred because adding nanoclay will result to increase special surface of the samples; consequently, increasing electrical load increases water absorption, which it can be partly cause of non-effective increasing nanoclay in soil resistance. There is also a significant difference between pressure strength of soils with lower humidity and those with higher humidity. It confirms that increasing humidity decreases strength level, which increasing water absorption of samples by nanoclay is reason of decreasing strength. There is an inverse significant relationship between increasing nano and soil water absorption, which its reason may be that adding nanoclay because of increasing samples special surface and consequently, increasing electricity load will increase water absorption and samples’ plasticity. It can be expected that samples’ permeability will decline by increasing their plasticity. There is also a significant relationship between increasing nano and soil liquid and doughiness limit that its reason can be increasing rate of water absorption in samples due to presence of nanoclay.© JASEMKeywords: Nanoclay, Resistance, Freezing, Sample, Uniaxia

Prediction of static crack propagation in adhesive joints

In this work, fracture mechanics methodology is used to predict crack propagation in the adhesive joining of aluminum and composite plates. Three types of loadings and two types of glass-epoxy composite sequences: [0/90]2s and [0/45/-45/90]s are considered for the composite plate. Therefore 2 × 3 = 6 cases are considered and their results are compared. The debonding initiation load, complete debonding load, crack face profile and load-displacement diagram have been compared for the six cases

Prediction of static crack propagation in adhesive joints

In this work, fracture mechanics methodology is used to predict crack propagation in the adhesive joining of aluminum and composite plates. Three types of loadings and two types of glass-epoxy composite sequences: [0/90]2s and [0/45/-45/90]s are considered for the composite plate. Therefore 2 × 3 = 6 cases are considered and their results are compared. The debonding initiation load, complete debonding load, crack face profile and load-displacement diagram have been compared for the six cases

ASSESSMENT OF THE ASSOCIATION BETWEEN DUST STORMS AND COVID-19 INFECTION RATE IN SOUTHWEST IRAN

This study assesses a plausible correlation between a dust intrusion episode and a daily increase in COVID-19 cases. A surge in COVID-19 cases was observed a few days after a Middle East Dust (MED) event that peaked on 25th April 2020 in south west Iran. To investigate potential causal factors for the spike in number of cases, cross-correlations between daily combined aerosol optical depths (AODs) and confrmed cases were computed for Khuzestan, Iran. Additionally, atmospheric stability data time series were assessed by covering before, during, and after dust intrusion, producing four statistically clustered distinct city groups. Groups 1 and 2 had diferent peak lag times of 10 and 4-5 days, respectively. Since there were statisti cally signifcant associations between AOD levels and confrmed cases in both groups, dust incursion may have increased population susceptibility to COVID-19 disease. Group 3 was utilized as a control group with neither a signifcant level of dust incursion during the episodic period nor any signifcant associations. Group 4 cities, which experienced high dust incur sion levels, showed no signifcant correlation with confrmed case count increases. Random Forest Analysis assessed the infuence of wind speed and AOD, showing relative importance of 0.31 and 0.23 on the daily increase percent of confrmed cases, respectively. This study may serve as a reference for better understanding and predicting factors afecting COVID-19 transmission and difusion routes, focusing on the role of MED intrusions

Evaluation of image processing technique in identifying rice blast disease in field conditions based on KNN algorithm improvement by K‐means

Nowadays, rice farming is affected by various diseases that are economically significant and worthy of attention. One of these diseases is blast. Rice blast is one of the most important limiting factors in rice yield. The purpose of this study is the timely and rapid diagnosis of rice blast based on the image processing technique in field conditions. To do so, color images were prepared using image processing technique and improved KNN algorithm by K-means was used to classify the images in Lab color space to detect disease spots on rice leaves. Squared classification was based on Euclidean distance, and the Otsu method was used to perform an automatic threshold histogram of images based on shape or to reduce the gray level in binary images. Finally, to determine the efficiency of the designed algorithm, sensitivity, specificity, and overall accuracy were examined. The classification results showed that the sensitivity and specificity of the designed algorithm were 92% and 91.7%, respectively, in the determination of the number of disease spots, and 96% and 95.65% in determining the quality of disease spots. The overall accuracy of the designed algorithm was 94%. Generally, the results obtained showed that the above method has a great potential for timely diagnosis of rice blast