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In order to understand the intricate mechanism of differential immunity against Karnal bunt (KB), basal levels of carotenoids, abscisic acid (ABA), total protease and protease inhibitor were determined in resistant and susceptible genotypes during transition from vegetative to developing stages of wheat spikes. The lower levels of carotenoid precursor of ABA in resistant genotype than in susceptible genotype could be explained by more inter-conversion of carotenoids into ABA pool which was evident from the results of determining ABA by enzyme-linked sorbent assay. The ABA was significantly higher in resistant genotype at all stages than in susceptible genotype, while a sharp increase was observed at S2 stage. The activity of total protease was higher at initial stages of resistant genotype and gradually declined in later stages after anthesis. In contrast to the protease activity, a reverse trend was observed for the levels of cysteine protease inhibitor, suggesting a negative correlation with each other. Level of cysteine protease inhibitor was observed to be three-folds higher at S2 stage in the resistant genotype than in the susceptible genotype. The results provided the clue for the involvement of ABA-dependent pathways in upregulation of cystatin that leads to induction of differential immunity against the KB pathogen. [ABSTRACT FROM PUBLISHER]

Washing durability of natural and synthetic antimicrobial finishes against Escherichia coli, Staphylococcus aureus, Aspergillus niger and Aspergillus fumigates was compared. Antimicrobial agents were applied on the cotton fabric by pad-dry-cure and exhaustion method. Antimicrobial activity was determined using AATCC test method-100-1998 and AATCC test method-30-1993. The results indicate that the samples treated with antimicrobial agents considerably retained antimicrobial properties up to 15 washes. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a computationally efficient artificial neural network (ANN) model for system identification of unknown dynamic nonlinear discrete time systems. A single layer functional link ANN is used for the model where the need of hidden layer is eliminated by expanding the input pattern by Chebyshev polynomials. Thus, creation of nonlinear decision boundaries in the multidimensional input space and approximation of complex nonlinear systems becomes easier. These models are linear in their parameters and nonlinear in the inputs. The recursive least squares method with forgetting factor is used as on-line learning algorithm for parameter updation. The good behaviour of the identification method is tested on Box and Jenkins Gas furnace benchmark identification problem, single input single output (SISO) and multi input multi output (MIMO) discrete time plants. Stability of the identification scheme is also addressed. [Copyright &y& Elsevier]