Subcontracting Relationship of Indian SMEs with a Global TNC: Do SMEs Gain and How?

TNCs having their production bases in developing countries provide increasing opportunity for local SMEs to have subcontracting relationships with these TNCs.Even though some theoretical and a few empirical studies throw light on the nature of assistance provided by TNCs to local SMEs through subcontracting relationships,none of the studies so far analysed the diversity of assistance that subcontracting SMEs of India would be able to obtain from a TNC using quantitative measurement.This paper probes the extent of linkages and diversity of assistance that Indian subcontracting SMEs would be able to obtain from a TNC customer based on primary data from SME subcontractors of a major TNC automobile manufacturer. Statistical analysis of direct assistance revealed that SMEs receive more of product and purchase process assistance. The extent of assistance for their process related,marketing, human resource and financial requirements is low whereas the assistance for their organisational know-how requirements is moderate. The major indirect benefits these SMEs could achieve are knowledge transfer, business volume, superior work culture, reputation and quality improvement.

Convergence problems in a class of model reference adaptive control systems

A class of model reference adaptive control system which make use of an augmented error signal has been introduced by Monopoli. Convergence problems in this attractive class of systems have been investigated in this paper using concepts from hyperstability theory. It is shown that the condition on the linear part of the system has to be stronger than the one given earlier. A boundedness condition on the input to the linear part of the system has been taken into account in the analysis - this condition appears to have been missed in the previous applications of hyperstability theory. Sufficient conditions for the convergence of the adaptive gain to the desired value are also given.

Cerebroprotective activity of Wedelia calendulacea on global cerebral ischemia in rats

The present study was to investigate the effect of W. calendulacea on ischemia and reperfusion-induced cerebral injury. Cerebral ischemia was induced by occluding right and left common carotid arteries (global cerebral ischemia) for 30 min followed by reperfusion for 1 h and 4 h individually. Various biochemical alterations, produced subsequent to the application of bilateral carotid artery occlusion (BCAO) followed by reperfusion viz. increase in lipid peroxidation (LPO), hydrogen peroxide (H(2)O(2)), and decrease in reduced glutathione (GSH), catalase (CAT) and superoxide dismutase (SOD), level in the brain tissue, Western blot analysis (Cu-Zn-SOD and CAT) and assessment of cerebral infarct size were measured. All those enzymes are markedly reversed and restored to near normal level in the groups pre-treated with W. calendulacea (250 and 500 mg/kg given orally in single and double dose/day for 10 days) in dose-dependent way. The effect of W. calendulacea had increased significantly the protein expression of copper/zinc superoxide dismutase (Cu-Zn-SOD) and CAT in cerebral ischemia. W. claendulacea was markedly decrease cerebral infarct damages but results are not statistically significant. It can be concluded that W. calendulacea possesses a neuroprotective activity against cerebral ischemia in rat.

A novel variable resolution global spectral method on the sphere

A variable resolution global spectral method is created on the sphere using High resolution Tropical Belt Transformation (HTBT). HTBT belongs to a class of map called reparametrisation maps. HTBT parametrisation of the sphere generates a clustering of points in the entire tropical belt; the density of the grid point distribution decreases smoothly in the domain outside the tropics. This variable resolution method creates finer resolution in the tropics and coarser resolution at the poles. The use of FFT procedure and Gaussian quadrature for the spectral computations retains the numerical efficiency available with the standard global spectral method. Accuracy of the method for meteorological computations are demonstrated by solving Helmholtz equation and non-divergent barotropic vorticity equation on the sphere. (C) 2011 Elsevier Inc. All rights reserved.

Network properties of protein-decoy structures

Convergence of the vast sequence space of proteins into a highly restricted fold/conformational space suggests a simple yet unique underlying mechanism of protein folding that has been the subject of much debate in the last several decades. One of the major challenges related to the understanding of protein folding or in silico protein structure prediction is the discrimination of non-native structures/decoys from the native structure. Applications of knowledge-based potentials to attain this goal have been extensively reported in the literature. Also, scoring functions based on accessible surface area and amino acid neighbourhood considerations were used in discriminating the decoys from native structures. In this article, we have explored the potential of protein structure network (PSN) parameters to validate the native proteins against a large number of decoy structures generated by diverse methods. We are guided by two principles: (a) the PSNs capture the local properties from a global perspective and (b) inclusion of non-covalent interactions, at all-atom level, including the side-chain atoms, in the network construction accommodates the sequence dependent features. Several network parameters such as the size of the largest cluster, community size, clustering coefficient are evaluated and scored on the basis of the rank of the native structures and the Z-scores. The network analysis of decoy structures highlights the importance of the global properties contributing to the uniqueness of native structures. The analysis also exhibits that the network parameters can be used as metrics to identify the native structures and filter out non-native structures/decoys in a large number of data-sets; thus also has a potential to be used in the protein `structure prediction' problem.

Reducing convergence times of self-propelled swarms via modified nearest neighbor rules

Vicsek et al. proposed a biologically inspired model of self-propelled particles, which is now commonly referred to as the Vicsek model. Recently, attention has been directed at modifying the Vicsek model so as to improve convergence properties. In this paper, we propose two modification of the Vicsek model which leads to significant improvements in convergence times. The modifications involve an additional term in the heading update rule which depends only on the current or the past states of the particle's neighbors. The variation in convergence properties as the parameters of these modified versions are changed are closely investigated. It is found that in both cases, there exists an optimal value of the parameter which reduces convergence times significantly and the system undergoes a phase transition as the value of the parameter is increased beyond this optimal value. (C) 2012 Elsevier B.V. All rights reserved.

The Contribution of Rare Species to Community Phylogenetic Diversity across a Global Network of Forest Plots

Niche differentiation has been proposed as an explanation for rarity in species assemblages. To test this hypothesis requires quantifying the ecological similarity of species. This similarity can potentially be estimated by using phylogenetic relatedness. In this study, we predicted that if niche differentiation does explain the co-occurrence of rare and common species, then rare species should contribute greatly to the overall community phylogenetic diversity (PD), abundance will have phylogenetic signal, and common and rare species will be phylogenetically dissimilar. We tested these predictions by developing a novel method that integrates species rank abundance distributions with phylogenetic trees and trend analyses, to examine the relative contribution of individual species to the overall community PD. We then supplement this approach with analyses of phylogenetic signal in abundances and measures of phylogenetic similarity within and between rare and common species groups. We applied this analytical approach to 15 long-term temperate and tropical forest dynamics plots from around the world. We show that the niche differentiation hypothesis is supported in six of the nine gap-dominated forests but is rejected in the six disturbance-dominated and three gap-dominated forests. We also show that the three metrics utilized in this study each provide unique but corroborating information regarding the phylogenetic distribution of rarity in communities.

An operator-splitting Galerkin/SUPG finite element method for population balance equations : stability and convergence

We present a heterogeneous finite element method for the solution of a high-dimensional population balance equation, which depends both the physical and the internal property coordinates. The proposed scheme tackles the two main difficulties in the finite element solution of population balance equation: (i) spatial discretization with the standard finite elements, when the dimension of the equation is more than three, (ii) spurious oscillations in the solution induced by standard Galerkin approximation due to pure advection in the internal property coordinates. The key idea is to split the high-dimensional population balance equation into two low-dimensional equations, and discretize the low-dimensional equations separately. In the proposed splitting scheme, the shape of the physical domain can be arbitrary, and different discretizations can be applied to the low-dimensional equations. In particular, we discretize the physical and internal spaces with the standard Galerkin and Streamline Upwind Petrov Galerkin (SUPG) finite elements, respectively. The stability and error estimates of the Galerkin/SUPG finite element discretization of the population balance equation are derived. It is shown that a slightly more regularity, i.e. the mixed partial derivatives of the solution has to be bounded, is necessary for the optimal order of convergence. Numerical results are presented to support the analysis.

Computational algorithms inspired by biological processes and evolution

In recent times computational algorithms inspired by biological processes and evolution are gaining much popularity for solving science and engineering problems. These algorithms are broadly classified into evolutionary computation and swarm intelligence algorithms, which are derived based on the analogy of natural evolution and biological activities. These include genetic algorithms, genetic programming, differential evolution, particle swarm optimization, ant colony optimization, artificial neural networks, etc. The algorithms being random-search techniques, use some heuristics to guide the search towards optimal solution and speed-up the convergence to obtain the global optimal solutions. The bio-inspired methods have several attractive features and advantages compared to conventional optimization solvers. They also facilitate the advantage of simulation and optimization environment simultaneously to solve hard-to-define (in simple expressions), real-world problems. These biologically inspired methods have provided novel ways of problem-solving for practical problems in traffic routing, networking, games, industry, robotics, economics, mechanical, chemical, electrical, civil, water resources and others fields. This article discusses the key features and development of bio-inspired computational algorithms, and their scope for application in science and engineering fields.

Involvement of the Global Regulator H-NS in the Survival of Escherichia coli in Stationary Phase

Long-term batch cultures of Escherichia coli grown in nutrient-rich medium accumulate mutations that provide a growth advantage in the stationary phase (GASP). We have examined the survivors of prolonged stationary phase to identify loci involved in conferring a growth advantage and show that a mutation in the hns gene causing reduced activity of the global regulator H-NS confers a GASP phenotype under specific conditions. The hns-66 allele bears a point mutation within the termination codon of the H-NS open reading frame, resulting in a longer protein that is partially functional. Although isolated from a long-term stationary-phase culture of the parent carrying the rpoS819 allele that results in reduced RpoS activity, the hns-66 survivor showed a growth disadvantage in the early stationary phase (24 to 48 h) when competed against the parent. The hns-66 mutant is also unstable and reverts at a high frequency in the early stationary phase by accumulating second-site suppressor mutations within the ssrA gene involved in targeting aberrant proteins for proteolysis. The mutant was more stable and showed a moderate growth advantage in combination with the rpoS819 allele when competed against a 21-day-old parent. These studies show that H-NS is a target for mutations conferring fitness gain that depends on the genetic background as well as on the stage of the stationary phase.

Albedo enhancement over land to counteract global warming: impacts on hydrological cycle

A recent modelling study has shown that precipitation and runoff over land would increase when the reflectivity of marine clouds is increased to counter global warming. This implies that large scale albedo enhancement over land could lead to a decrease in runoff over land. In this study, we perform simulations using NCAR CAM3.1 that have implications for Solar Radiation Management geoengineering schemes that increase the albedo over land. We find that an increase in reflectivity over land that mitigates the global mean warming from a doubling of CO2 leads to a large residual warming in the southern hemisphere and cooling in the northern hemisphere since most of the land is located in northern hemisphere. Precipitation and runoff over land decrease by 13.4 and 22.3%, respectively, because of a large residual sinking motion over land triggered by albedo enhancement over land. Soil water content also declines when albedo over land is enhanced. The simulated magnitude of hydrological changes over land are much larger when compared to changes over oceans in the recent marine cloud albedo enhancement study since the radiative forcing over land needed (-8.2 W m(-2)) to counter global mean radiative forcing from a doubling of CO2 (3.3 W m(-2)) is approximately twice the forcing needed over the oceans (-4.2 W m(-2)). Our results imply that albedo enhancement over oceans produce climates closer to the unperturbed climate state than do albedo changes on land when the consequences on land hydrology are considered. Our study also has important implications for any intentional or unintentional large scale changes in land surface albedo such as deforestation/afforestation/reforestation, air pollution, and desert and urban albedo modification.

An estimate of equilibrium sensitivity of global terrestrial carbon cycle using NCAR CCSM4

Increasing concentrations of atmospheric CO2 influence climate, terrestrial biosphere productivity and ecosystem carbon storage through its radiative, physiological and fertilization effects. In this paper, we quantify these effects for a doubling of CO2 using a low resolution configuration of the coupled model NCAR CCSM4. In contrast to previous coupled climate-carbon modeling studies, we focus on the near-equilibrium response of the terrestrial carbon cycle. For a doubling of CO2, the radiative effect on the physical climate system causes global mean surface air temperature to increase by 2.14 K, whereas the physiological and fertilization on the land biosphere effects cause a warming of 0.22 K, suggesting that these later effects increase global warming by about 10 % as found in many recent studies. The CO2-fertilization leads to total ecosystem carbon gain of 371 Gt-C (28 %) while the radiative effect causes a loss of 131 Gt-C (10 %) indicating that climate warming damps the fertilization-induced carbon uptake over land. Our model-based estimate for the maximum potential terrestrial carbon uptake resulting from a doubling of atmospheric CO2 concentration (285-570 ppm) is only 242 Gt-C. This highlights the limited storage capacity of the terrestrial carbon reservoir. We also find that the terrestrial carbon storage sensitivity to changes in CO2 and temperature have been estimated to be lower in previous transient simulations because of lags in the climate-carbon system. Our model simulations indicate that the time scale of terrestrial carbon cycle response is greater than 500 years for CO2-fertilization and about 200 years for temperature perturbations. We also find that dynamic changes in vegetation amplify the terrestrial carbon storage sensitivity relative to a static vegetation case: because of changes in tree cover, changes in total ecosystem carbon for CO2-direct and climate effects are amplified by 88 and 72 %, respectively, in simulations with dynamic vegetation when compared to static vegetation simulations.