Bharathiar University

About: Bharathiar University is a education organization based out in Coimbatore, Tamil Nadu, India. It is known for research contribution in the topics: Thin film & Adsorption. The organization has 5812 authors who have published 8628 publications receiving 143934 citations. The organization is also known as: BU.

Mycorrhiza in sedges—an overview

Abstract: Most terrestrial plants associate with root-colonising mycorrhizal fungi, which improve the fitness of both the fungal and plant associates. However, exceptions exist both between and within plant families failing to associate with mycorrhizal fungi or in the incidence and the extent of mycotrophy, which may vary greatly. Sedges are important pioneers of disturbed habitats and often dominate vegetations like wetlands, and arctic and alpine vegetations, in which the mycorrhizal inoculum in the soil is often low or absent. In the past, sedges were often designated as non-mycorrhizal, though limited reports indicated the presence of mycorrhiza in certain species. However, studies since 1987 indicate widespread occurrence of mycorrhiza in sedges. Based on these studies, the family Cyperaceae is no longer a non-mycorrhizal family, but the mycorrhizal status of its members is greatly influenced by environmental conditions. Further, sedges appear to have several morphological adaptations to thrive in the absence of mycorrhizal association. Though mycorrhizal associations have been noted in many sedge species, the ecological role of this association is not well documented and no clear generalisation can be drawn. Similarly, the role of mycorrhizal fungi on sedge growth and nutrient uptake or non-nutritional benefits has yet to be fully ascertained. This paper reviews the current information available on the incidence of mycorrhiza in sedges and the possible reasons for low mycotrophy observed in this family.

Exponential H ∞ filtering analysis for discrete-time switched neural networks with random delays using sojourn probabilities

Abstract: This paper is concerned with the exponential $H_{\infty}$ filtering problem for a class of discrete-time switched neural networks with random time-varying delays based on the sojourn-probability-dependent method. Using the average dwell time approach together with the piecewise Lyapunov function technique, sufficient conditions are proposed to guarantee the exponential stability for the switched neural networks with random time-varying delays which are characterized by introducing a Bernoulli stochastic variable. Based on the derived $H_\infty$ performance analysis results, the $H_\infty$ filter design is formulated in terms of Linear Matrix Inequalities (LMIs). Finally, two numerical examples are presented to demonstrate the effectiveness of the proposed design procedure.