Investigation and modeling on protective textiles using artificial neural networks for defense applications

Kevlar 29 is a class of Kevlar fiber used for protective applications primarily by the military and law enforcement agencies for bullet resistant vests, hence for these reasons military has found that armors reinforced with Kevlar 29 multilayer fabrics which offer 25–40% better fragmentation resistance and provide better fit with greater comfort. The objective of this study is to investigate and develop an artificial neural network model for analyzing the performance of ballistic fabrics made from Kevlar 29 single layer fabrics using their material properties as inputs. Data from fragment simulation projectile (FSP) ballistic penetration measurements at 244 m/s has been used to demonstrate the modeling aspects of artificial neural networks. The neural network models demonstrated in this paper is based on back propagation (BP) algorithm which is inbuilt in MATLAB 7.1 software and is used for studies in science, technology and engineering. In the present research, comparisons are also made between the measured values of samples selected for building the neural network model and network predicted results. The analysis of the results for network predicted and experimental samples used in this study showed similarity

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Not AvailableThe composition of the cuticular wax varies from species to species as well as the developmental stage of the organ. In the present study, the variation in the pattern of accumulation of C28 and > C28 chain length of the cuticular wax compounds in the two contrasting Musa species for wax content has been examined—Musa balbisiana ‘Bee heekela’ (BB genome) (with high wax content) and Musa acuminata ssp. Burmannicoides Colla—‘Calcutta-4’ (AA genome) (with low wax content). These two species are the progenitors for the modern cultivated banana. Using GC–MS analysis, 40 different cuticular wax compounds from five different leaf developmental stages in these two musa species were identified. Around tenfold higher accumulation of C28 length compounds was found in ‘Calcutta-4’ as compared to that of ‘Bee hee kela’. In case of ‘Bee hee kela’,  > C28 length compounds were in large proportion compared to C28 length wax compounds. The qPCR analysis was carried out for the gene CUT1/CER6/KCS6 which are involved in the fatty acid elongation step of cuticular wax biosynthesis. A higher expression in the 2nd (young), 4th and 6th (old) fully expanded leaves of high wax genotype ‘Bee hee kela’ with 1.57083, 9.71512, and 1.44963 fold change, whereas a lower expression of 0.9151, 4.8785, and 1.2321 fold change in low wax genotype ‘Calcutta-4’, respectively, was observed. A negative relationship between the gene expression and C28 wax compounds’ accumulation was observed, indicating the importance of the expression of CUT1/CER6/KCS6 gene for elongation of C28 to > C28 cuticular wax compounds. The current study suggest that CUT1/CER6/KCS6 from ‘Bee heekela’ would be a good contributor for higher cuticular wax with higher > C28 compounds, thus, finally, contributing for higher leaf water retention capacity their by conferring drought tolerance helping in the future banana improvement programs.icar nptc functional genomics projec