Different antioxidants and salicylic acid were tested to overcome pericarp browning and to maintain the postharvest quality of the litchi fruits at ambient storage. It was found that 0.5% salicylic acid, 1% isoascorbic acid and 1% N-acetyl cysteine performed better over sulphur dioxide (SO2) fumigation for most of the parameters under study. Application of 0.5% salicylic acid found superior to reduce the pericarp browning, relative leakage rate, and decay percentage. It was effective in reduction of polyphenol oxidase activity and improvement of anthocyanin pigments of the fruit pericarp over other treatments. Total soluble solid, titratable acidity and ascorbic acid of the litchi fruits were recorded highest with the application of 1% isoascorbic acid followed by 0.5% salicylic acid treatment. Therefore, 0.5% salicylic acid and 1% isoascorbic could be used as an alternative of SO2 fumigation for quality retention of litchi fruits.
Industrial emissions of ozone depleting substances (ODSs) during the second half of the twentieth century have led to one of the most visible human impacts on the Earth: the Antarctic ozone hole. The ozone loss intensified in the 1980s and reached the level of saturation (i.e., complete loss of ozone) due to the high levels of ODSs in the atmosphere. Significant changes in the southern hemispheric climate have been observed in the past decades due to this unprecedented ozone loss. Although the most recent studies suggest healing in the Antarctic ozone hole, the status of ozone in the loss saturation layer (~13-21 km) has not been discussed in detail. Here, a comprehensive analysis of vertical, spatial and temporal evolution of ozone loss saturation (ozone mixing ratio ≤ 0.1 ppmv) in the Antarctic vortex using high resolution measurements for the 1979-2017 period reveals that the loss saturation began in 1987 and continued to occur in all winters thereafter, except in the major warming winters of 1988 and 2002. However, our analysis shows a clear reduction in the frequency of occurrence of ozone loss saturation over the period 2001-2017 consistently throughout various datasets (e.g., ozonesonde and satellite measurements of ozone profiles and total columns), thereby revealing the emergence of an important milestone in ozone recovery.
In recent years, heart disease is one of the leading cause of death for both women and men. So, heart disease prediction is considered as a significant part in the clinical data analysis. Standard data mining techniques like Support Vector Machine (SVM), Naïve Bayes and other machine learning techniques used in the earlier research for heart disease prediction. These methods are not sufficient for effective heart disease prediction due to insufficient test data. In this research, Bi-directional Long Short Term Memory with Conditional Random Field (BiLSTM-CRF) has been proposed to increase the efficiency of heart disease prediction. The input medical data were analyzed in a bidirectional manner for effective analysis, and CRF provided the linear relationship between the features. The BiLSTM-CRF method has been tested on the Cleveland dataset to analyze the performance and compared with existing methods. The results showed that the proposed BiLSTM-CRF outperformed the existing methods in heart disease prediction. The average accuracy of the proposed BiLSTM-CRF is 90.04%, which is higher than the existing methods.
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