Peanut agglutinin from callus and cell suspension cultures of Arachis hypogaea L

Synthesis of peanut agglutinin was induced in callus and cell suspension cultures of cotyledons of peanut (Arachis hypogaea L.). The lectin was synthesised in cultures through several passages. Biosynthesis of peanut agglutinin was regulated by the type and concentration of exogenous growth regulators and was positively correlated to the growth of the cultures,indicating that the agglutinin may have a role to play during cell growth. Movement of agglutinin from the cells into the medium not only facilitated easy isolation of the lectin but also provided a clue that it may probably serve as a defence molecule. The synthesized lectin purified from culture, was found to be biologically active, and was found to be comparable with the lectin from seeds, in terms of its electrophoretic mobility.

Ionic Polymer Metal Composite Flapping Actuator Mimicking Dragonflies

In this study, variational principle is used for dynamic modeling of an Ionic Polymer Metal Composite (IPMC) flapping wing. The IPMC is an Electro-active Polymer (EAP) which is emerging as a useful smart material for `artificial muscle' applications. Dynamic characteristics of IPMC flapping wings having the same size as the actual wings of three different dragonfly species Aeshna Multicolor, Anax Parthenope Julius and Sympetrum Frequens are analyzed using numerical simulations. An unsteady aerodynamic model is used to obtain the aerodynamic forces. A comparative study of the performances of three IPMC flapping wings is conducted. Among the three species, it is found that thrust force produced by the IPMC flapping wing of the same size as Anax Parthenope Julius wing is maximum. Lift force produced by the IPMC wing of the same size as Sympetrum Frequens wing is maximum and the wing is suitable for low speed flight. The numerical results in this paper show that dragonfly inspired IPMC flapping wings are a viable contender for insect scale flapping wing micro air vehicles.

Immune responses to hemagglutinin-neuraminidase protein of peste des petits ruminants virus expressed in transgenic peanut plants in sheep

Peste des petits ruminants (PPR) is an acute, highly contagious disease of small ruminants caused by a morbillivirus, Peste des petits ruminants virus (PPRV). The disease is prevalent in equatorial Africa, the Middle East, and the Indian subcontinent. A live attenuated vaccine is in use in some of the countries and has been shown to provide protection for at least three years against PPR. However, the live attenuated vaccine is not robust in terms of thermotolerance. As a step towards development of a heat stable subunit vaccine, we have expressed a hemagglutinin-neuraminidase (HN) protein of PPRV in peanut plants (Arachis hypogea) in a biologically active form, possessing neuraminidase activity. Importantly. HN protein expressed in peanut plants retained its immunodominant epitopes in their natural conformation. The immunogenicity of the plant derived HN protein was analyzed in sheep upon oral immunization. Virus neutralizing antibody responses were elicited upon oral immunization of sheep in the absence of any mucosal adjuvant. In addition, anti-PPRV-HN specific cell-mediated immune responses were also detected in mucosally immunized sheep. (C) 2010 Elsevier B.V. All rights reserved.

Synthesis of amino thiols and isocysteines via regioselective ring opening of sulfamidates with tetrathiomolybdate

Herein we present a simple and highly efficient method for the synthesis of beta and gamma-amino thiols via regioselective ring opening of sulfamidates with tetrathiomolybdate 1. The generality of this methodology has been shown by synthesizing carbohydrate derived beta-amino thiol. The scope and versatility of this methodology has been demonstrated by synthesizing biologically important unnatural amino acids like isocysteines in optically pure form. (C) 2011 Elsevier Ltd. All rights reserved.

GC-MS study of Artabotrys odoratissimus fatty oil (leaves)

GC-MS study of two fatty oil fractions from Artabotrys odoratissimus (leaves) indicated the presence of fifteen compounds namely, nonanoic acid; methyl phenyl propanoate; decanoic acid; diethyl phthalate; dibutyl phthalate; 2 - amino-3-ethyl biphenyl; 5-methyl-9-phenylnonan-3-ol; hexadeca-2,7,11-triene; 2,6-dimethyl-1-phenylhepta-1-one; 2,5-dimethyltetradecahydrophenenthrene; 1-phenylundecane; 1-isopropyl-4,6-dimethyl naphthalene; 5-(2-butyl phenyl)pent-3-en-2-ol; 1-phenyideca-1-one and 1-phenylundecan-1-one. Some of the compounds are rare occurring and biologically active.

Quantum spin models with exact dimer ground states

Inspired by the exact solution of the Majumdar-Ghosh model, a family of one-dimensional, translationally invariant spin Hamiltonians is constructed. The exchange coupling in these models is antiferromagnetic, and decreases linearly with the separation between the spins. The coupling becomes identically zero beyond a certain distance. It is rigorously proved that the dimer configuration is an exact, superstable ground-state configuration of all the members of the family on a periodic chain. The ground state is twofold degenerate, and there exists an energy gap above the ground state. The Majumdar-Ghosh Hamiltonian with a twofold degenerate dimer ground state is just the first member of the family. The scheme of construction is generalized to two and three dimensions, and illustrated with the help of some concrete examples. The first member in two dimensions is the Shastry-Sutherland model. Many of these models have exponentially degenerate, exact dimer ground states.

A model for tool-use traditions in primates: implications for the coevolution of culture and cognition

Inspired by the demonstration that tool-use variants among wild chimpanzees and orangutans qualify as traditions (or cultures), we developed a formal model to predict the incidence of these acquired specializations among wild primates and to examine the evolution of their underlying abilities. We assumed that the acquisition of the skill by an individual in a social unit is crucially controlled by three main factors, namely probability of innovation, probability of socially biased learning, and the prevailing social conditions (sociability, or number of potential experts at close proximity). The model reconfirms the restriction of customary tool use in wild primates to the most intelligent radiation, great apes; the greater incidence of tool use in more sociable populations of orangutans and chimpanzees; and tendencies toward tool manufacture among the most sociable monkeys. However, it also indicates that sociable gregariousness is far more likely to produce the maintenance of invented skills in a population than solitary life, where the mother is the only accessible expert. We therefore used the model to explore the evolution of the three key parameters. The most likely evolutionary scenario is that where complex skills contribute to fitness, sociability and/or the capacity for socially biased learning increase, whereas innovative abilities (i.e., intelligence) follow indirectly. We suggest that the evolution of high intelligence will often be a byproduct of selection on abilities for socially biased learning that are needed to acquire important skills, and hence that high intelligence should be most common in sociable rather than solitary organisms. Evidence for increased sociability during hominin evolution is consistent with this new hypothesis. (C) 2003 Elsevier Science Ltd. All rights reserved.

Wetlands of Greater Bangalore, India: Automatic Delineation through Pattern Classifiers

Wetlands are the most productive and biologically diverse but very fragile ecosystems. They are vulnerable to even small changes in their biotic and abiotic factors. In recent years, there has been concern over the continuous degradation of wetlands due to unplanned developmental activities. This necessitates inventorying, mapping, and monitoring of wetlands to implement sustainable management approaches. The principal objective of this work is to evolve a strategy to identify and monitor wetlands using temporal remote sensing (RS) data. Pattern classifiers were used to extract wetlands automatically from NIR bands of MODIS, Landsat MSS and Landsat TM remote sensing data. MODIS provided data for 2002 to 2007, while for 1973 and 1992 IR Bands of Landsat MSS and TM (79m and 30m spatial resolution) data were used. Principal components of IR bands of MODIS (250 m) were fused with IRS LISS-3 NIR (23.5 m). To extract wetlands, statistical unsupervised learning of IR bands for the respective temporal data was performed using Bayesian approach based on prior probability, mean and covariance. Temporal analysis of wetlands indicates a sharp decline of 58% in Greater Bangalore attributing to intense urbanization processes, evident from a 466% increase in built-up area from 1973 to 2007.

Biomonitoring of Lotic habitats through Diatoms

Freshwater ecosystems vary in size and composition and contain a wide range of organisms which interact with each other and with the environment. These interactions are between organisms and the environment as nutrient cycling, biomass formation and transfer, maintenance of internal environment and interactions with the external environment. The range of organisms present in aquatic communities decides the generation and transfer function of biomass, which defines and characterises the system. These organisms have distinct roles as they occupy particular trophic levels, forming an interconnected system in a food chain. Availability of resources and competition would primarily determine the balance of individual species within the food web, which in turn influences the variety and proportions of the different organisms, with important implications for the overall functioning of the system. This dynamic and diverse relationship decides the physical, chemical and biological elements across spatial and temporal scales in the aquatic ecosystem, which can be recorded by regular inventorying and monitoring to maintain the integrity and conserve the ecosystem. Regular environmental monitoring, particularly water quality monitoring allows us to detect, assess and manage the overall impacts on the rivers. The appreciation of water quality is in constant flux. Water quality assessments derived through the biotic indices, i.e. assessments based on observations of the resident floral and faunal communities has gained importance in recent years. Biological evaluations provide a description of the water quality that is often not achievable from elemental analyses alone. A biological indicator (or bioindicator) is a taxon or taxa selected based on its sensitivity to a particular attribute, and then assessed to make inferences about that attribute. In other words, they are a substitute for directly measuring abiotic features or other biota. Bioindicators are evaluated through presence or absence, condition, relative abundance, reproductive success, community structure (i.e. composition and diversity), community function (i.e. trophic structure), or any combination thereof.Biological communities reflect the overall ecological integrity by integrating various stresses, thus providing a broad measure of their synergistic impacts. Aquatic communities, both plants and animals, integrate and reflect the effects of chemical and physical disturbances that occur over extended periods of time. Monitoring procedures based on the biota measure the health of a river and the ability of aquatic ecosystems to support life as opposed to simply characterising the chemical and physical components of a particular system. This is the central purpose of assessing the biological condition of aquatic communities of a river.Diatoms (Bacillariophyceae), blue green algae (Cyanophyceae), green algae (Chlorophyceae), and red algae (Rhodphyceae) are the main groups of algae in flowing water. These organisms are widely used as biological indicators of environmental health in the aquatic ecosystem because algae occupy the most basic level in the transfer of energy through natural aquatic systems. The distribution of algae in an aquatic ecosystem is directly related to the fundamental factors such as physical, chemical and biological constituents. Soft algae (all the algal groups except diatoms) have also been used as indicators of biological integrity, but they may have less efficiency than diatoms in this respect due to their highly variable morphology. The diatoms (Bacillariophyceae) comprise a ubiquitous, highly successful and distinctive group of unicellular algae with the most obvious distinguishing characteristic feature being siliceous cell walls (frustules). The photosynthetic organisms living within its photic zone are responsible for about one-half of global primary productivity. The most successful organisms are thought to be photosynthetic prokaryotes (cyanobacteria and prochlorophytes) and a class of eukaryotic unicellular algae known as diatoms. Diatoms are likely to have arisen around 240 million years ago following an endosymbiotic event between a red eukaryotic alga and a heterotrophic flagellate related to the Oomycetes.The importance of algae to riverine ecology is easily appreciated when one considers that they are primary producers that convert inorganic nutrients into biologically active organic compounds while providing physical habitat for other organisms. As primary producers, algae transform solar energy into food from which many invertebrates obtain their energy. Algae also transform inorganic nutrients, such as atmospheric nitrogen into organic forms such as ammonia and amino acids that can be used by other organisms. Algae stabilises the substrate and creates mats that form structural habitats for fish and invertebrates. Algae are a source of organic matter and provide habitat for other organisms such as non-photosynthetic bacteria, protists, invertebrates, and fish. Algae's crucial role in stream ecosystems and their excellent indicator properties make them an important component of environmental studies to assess the effects of human activities on stream health. Diatoms are used as biological indicators for a number of reasons: 1. They occur in all types of aquatic ecosystems. 2. They collectively show a broad range of tolerance along a gradient of aquatic productivity, individual species have specific water chemistry requirements. 3. They have one of the shortest generation times of all biological indicators (~2 weeks). They reproduce and respond rapidly to environmental change and provide early measures of both pollution impacts and habitat restoration. 4. It takes two to three weeks before changes are reflected to a measurable extent in the assemblage composition.

An Efficient Scheme for Establishing Pairwise Keys for Wireless Sensor Networks

This paper addresses the problem of secure path key establishment in wireless sensor networks that uses the random key pre-distribution technique. Inspired by the recent proxy-based scheme in the work of Ling and Znati (2005) and Li et al. (2005), we introduce a friend-based scheme for establishing pairwise keys securely. We show that the chances of finding friends in a neighbourhood are considerably more than that of finding proxies, leading to lower communication overhead. Further, we prove that the friend-based scheme performs better than the proxy-based scheme both in terms of resilience against node capture as well as in energy consumption for pairwise key establishment, making our scheme more feasible.

A decidable temporal logic with repeating values

Various logical formalisms with the freeze quantifier have been recently considered to model computer systems even though this is a powerful mechanism that often leads to undecidability. In this paper, we study a linear-time temporal logic with past-time operators such that the freeze operator is only used to express that some value from an infinite set is repeated in the future or in the past. Such a restriction has been inspired by a recent work on spatio-temporal logics. We show decidability of finitary and infinitary satisfiability by reduction into the verification of temporal properties in Petri nets. This is a surprising result since the logic is closed under negation, contains future-time and past-time temporal operators and can express the nonce property and its negation. These ingredients are known to lead to undecidability with a more liberal use of the freeze quantifier.

A Unified Approach to Encoding and Classification Using Bimodal Projection-Based Features

In general the objective of accurately encoding the input data and the objective of extracting good features to facilitate classification are not consistent with each other. As a result, good encoding methods may not be effective mechanisms for classification. In this paper, an earlier proposed unsupervised feature extraction mechanism for pattern classification has been extended to obtain an invertible map. The method of bimodal projection-based features was inspired by the general class of methods called projection pursuit. The principle of projection pursuit concentrates on projections that discriminate between clusters and not faithful representations. The basic feature map obtained by the method of bimodal projections has been extended to overcome this. The extended feature map is an embedding of the input space in the feature space. As a result, the inverse map exists and hence the representation of the input space in the feature space is exact. This map can be naturally expressed as a feedforward neural network.

Interference Alignment Algorithms for the K User Constant MIMO Interference Channel

This paper considers the degrees of freedom (DOF) for a K user multiple-input multiple-output (MIMO) M x N interference channel using interference alignment (IA). A new performance metric for evaluating the efficacy of IA algorithms is proposed, which measures the extent to which the desired signal dimensionality is preserved after zero-forcing the interference at the receiver. Inspired by the metric, two algorithms are proposed for designing the linear precoders and receive filters for IA in the constant MIMO interference channel with a finite number of symbol extensions. The first algorithm uses an eigenbeamforming method to align sub-streams of the interference to reduce the dimensionality of the interference at all the receivers. The second algorithm is iterative, and is based on minimizing the interference leakage power while preserving the dimensionality of the desired signal space at the intended receivers. The improved performance of the algorithms is illustrated by comparing them with existing algorithms for IA using Monte Carlo simulations.

Kannada WordNet - a lexical database

This paper presents the preliminary analysis of Kannada WordNet and the set of relevant computational tools. Although the design has been inspired by the famous English WordNet, and to certain extent, by the Hindi WordNet, the unique features of Kannada WordNet are graded antonyms and meronymy relationships, nominal as well as verbal compoundings, complex verb constructions and efficient underlying database design (designed to handle storage and display of Kannada unicode characters). Kannada WordNet would not only add to the sparse collection of machine-readable Kannada dictionaries, but also will give new insights into the Kannada vocabulary. It provides sufficient interface for applications involved in Kannada machine translation, spell checker and semantic analyser.

Evolutionary Algorithm for the Determination of Optimal Mode of Bioreactor Operation

Stirred tank bioreactors, employed in the production of a variety of biologically active chemicals, are often operated in batch, fed-batch, and continuous modes of operation. The optimal design of bioreactor is dependent on the kinetics of the biological process, as well as the performance criteria (yield, productivity, etc.) under consideration. In this paper, a general framework is proposed for addressing the two key issues related to the optimal design of a bioreactor, namely, (i) choice of the best operating mode and (ii) the corresponding flow rate trajectories. The optimal bioreactor design problem is formulated with initial conditions and inlet and outlet flow rate trajectories as decision variables to maximize more than one performance criteria (yield, productivity, etc.) as objective functions. A computational methodology based on genetic algorithm approach is developed to solve this challenging multiobjective optimization problem with multiple decision variables. The applicability of the algorithm is illustrated by solving two challenging problems from the bioreactor optimization literature.