The role of competition and habitat in structuring small mammal communities in a tropical montane ecosystem in southern India

Small mammals were sampled in two natural habitats (montane stunted evergreen forests and montane grassland) and four anthropogenic habitats (tea, wattle, bluegum and pine plantation) in the Upper Nilgiris in southern India. Of the species trapped, eight were in montane evergreen forests and three were in other habitats. Habitat discrimination was studied in the rodents Rattus rattus and Mus famulus and the shrew Suncus montanus in the montane forest habitat. Multivariate tests on five variables (canopy cover, midstorey density, ground cover, tree density, canopy height) showed that R. rattus uses areas of higher tree density and lower canopy cover. Suncus montanus and M. famulus use habitat with higher tree density and ground cover and lower canopy height. Multivariate tests did not discriminate habitat use between the species. Univariate tests, however, showed that M. famulus uses areas of higher tree density than R. rattus and S. montanus. Rattus rattus was the dominant species in the montane forest, comprising 60.9% of total density, while the rodent Millardia meltada was the dominant species in the grassland. Studies of spatial interaction between these two species in habitats where they coexisted showed neither overlap nor avoidance between the species. Rattus rattus, however, did use areas of lower ground cover than did M. meltada. The analysis of spatial interactions between the species, habitat discrimination and use, and the removal experiments suggest that interspecific competition may not be a strong force in structuring these small mammal communities. There are distinct patterns in the use of different habitats by some species, but microhabitat selection and segregation is weak. Other factors such as intraspecific competition may play a more important role in these communities.

Heat shock protein 70 on Neuro2a cells is a putative receptor for Japanese encephalitis virus

Japanese encephalitis virus (JEV) envelope (E) protein has been shown to play a critical role in attachment to cells. However, the receptor interacting with envelope protein has not been conclusively identified. Using mouse neuroblastoma (Neuro2a) cells and purified JEV-E protein in `Virus Overlay Protein Binding Assay' followed by MALDI-TOF analysis, we identified `heat shock protein 70' (Hsp70) as a possible receptor for JEV. Indirect immunofluorescence and flow-cytometry analysis demonstrated localization of Hsp70 on Neuro2a cell surface. Co-immunoprecipitation followed by Western blot analysis reconfirmed the interaction between Hsp70 and JEV-E protein. Further, anti-Hsp70 polyclonal-antibodies were able to block JEV entry into Neuro2a cells. Additionally, using the bioinformatic tool - FTDOCK, clocking between the proteins was performed. Amongst six interacting structural poses studied one pose involving RGD motif on JEV-E and leucine(539) on Hsp70 displayed stable interaction. These observations indicate that Hsp70 serves as putative receptor for JEV in Neuro2A cells.

A new intelligent algorithm for online voltage stability assessment and monitoring

This paper presents a new approach for assessing power system voltage stability based on artificial feed forward neural network (FFNN). The approach uses real and reactive power, as well as voltage vectors for generators and load buses to train the neural net (NN). The input properties of the NN are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The performance of the trained NN is investigated on two systems under various voltage stability assessment conditions. Main advantage is that the proposed approach is fast, robust, accurate and can be used online for predicting the L-indices of all the power system buses simultaneously. The method can also be effectively used to determining local and global stability margin for further improvement measures.

Baker's yeast expressing the Japanese encephalitis virus envelope protein on its cell surface: induction of an antigen-specific but non-neutralizing antibody response

Live recombinant Saccharomyces cerevisiae yeast expressing the envelope antigen of Japanese encephalitis virus (JEV) on the outer mannoprotein layer of the cell wall were examined for their ability to induce antigen-specific antibody responses in mice. When used as a modelantigen, parenteral immunization of mice with surface-expressing GFP yeast induced a strong anti-GFP antibody response in the absence of adjuvants. This antigen delivery approach was then used for a more stringent system, such as the envelope protein of JEV, which is a neurotropic virus requiring neutralizing antibodies for protection.Although 70% of cells were detected to express the total envelope protein on the surface by antibodies raised to the bacterially expressed protein, polyclonal anti-JEV antibodies failed to react with them. In marked contrast, yeast expressing the envelope fragments 238-398, 373-399 and 373-500 in front of a Gly-Ser linker were detected by anti-JEV antibodies as well as a monoclonal antibody but not by antibodies raised to the bacterially expressed protein. Immunization of mice with these surface-expressing recombinants resulted in a strong antibody response. However, the antibodies failed to neutralize the virus, although the fragments were selected based on neutralizing determinants.

An Online Implementable Differential Evolution Tuned Optimal Guidance Law

This paper proposes a novel application of differential evolution to solve a difficult dynamic optimisation or optimal control problem. The miss distance in a missile-target engagement is minimised using differential evolution. The difficulty of solving it by existing conventional techniques in optimal control theory is caused by the nonlinearity of the dynamic constraint equation, inequality constraint on the control input and inequality constraint on another parameter that enters problem indirectly. The optimal control problem of finding the minimum miss distance has an analytical solution subject to several simplifying assumptions. In the approach proposed in this paper, the initial population is generated around the seed value given by this analytical solution. Thereafter, the algorithm progresses to an acceptable final solution within a few generations, satisfying the constraints at every iteration. Since this solution or the control input has to be obtained in real time to be of any use in practice, the feasibility of online implementation is also illustrated.

Dynamic Space Warping Of Strokes For Recognition Of Online Handwritten Characters

This paper suggests a scheme for classifying online handwritten characters, based on dynamic space warping of strokes within the characters. A method for segmenting components into strokes using velocity profiles is proposed. Each stroke is a simple arbitrary shape and is encoded using three attributes. Correspondence between various strokes is established using Dynamic Space Warping. A distance measure which reliably differentiates between two corresponding simple shapes (strokes) has been formulated thus obtaining a perceptual distance measure between any two characters. Tests indicate an accuracy of over 85% on two different datasets of characters.