Influence of subcontracting on innovation and economic performance of SMEs in Indian automobile industry

Trans-national corporations (TNCs) expanding their production bases to developing countries having better conditions of manufacturing and domestic markets provide increasing opportunities for local small and medium enterprises (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 quantitatively analysed the role of this assistance on the innovative performance of SMEs leading to better economic performance This paper probes the extent and diversity of assistance received by SMEs from a TNC through subcontracting and its influence on technological innovations and economic performance of SMEs in the Indian automobile industry Indian SMEs were able to receive mainly product related and purchase process assistance thereby implying that subcontracting is largely confined to purchase-supply relationships However assistance received through subcontracting is beneficial as It promoted technological innovations of SMEs the higher the degree of assistance the higher the level of innovations carried out by these SMEs which in turn facilitated their economic performance Thus this paper substantiates in the Indian context that subcontracting relationship with a TNC can be an important source of technological innovations and enhanced economic performance for SMEs (C) 2010 Elsevier Ltd All rights reserved

Normal mode sound propagation in an ocean with random narrow-band surface waves

Normal mode sound propagation in an isovelocity ocean with random narrow-band surface waves is considered, assuming the root-mean-square wave height to be small compared to the acoustic wavelength. Nonresonant interaction among the normal modes is studied straightforward perturbation technique. The more interesting case of resonant interaction is investigated using the method of multiple scales to obtain a pair of stochastic coupled amplitude equations which are solved using the Peano-Baker expansion technique. Equations for the spatial evolution of the first and second moments of the mode amplitudes are also derived and solved. It is shown that, irrespective of the initial conditions, the mean values of the mode amplitudes tend to zero asymptotically with increasing range, the mean-square amplitudes tend towards a state of equipartition of energy, and the total energy of the modes is conserved.

Breast cancer and human papillomavirus infection: No evidence of HPV etiology of breast cancer in Indian women

Background: Two clinically relevant high-risk HPV (HR-HPV) types 16 and 18 are etiologically associated with the development of cervical carcinoma and are also reported to be present in many other carcinomas in extra-genital organ sites. Presence of HPV has been reported in breast carcinoma which is the second most common cancer in India and is showing a fast rising trend in urban population. The two early genes E6 and E7 of HPV type 16 have been shown to immortalize breast epithelial cells in vitro, but the role of HPV infection in breast carcinogenesis is highly controversial. Present study has therefore been undertaken to analyze the prevalence of HPV infection in both breast cancer tissues and blood samples from a large number of Indian women with breast cancer from different geographic regions. Methods: The presence of all mucosal HPVs and the most common high-risk HPV types 16 and 18 DNA was detected by two different PCR methods - (i) conventional PCR assays using consensus primers (MY09/11, or GP5 +/GP6+) or HPV16 E6/E7 primers and (ii) highly sensitive Real-Time PCR. A total of 228 biopsies and corresponding 142 blood samples collected prospectively from 252 patients from four different regions of India with significant socio-cultural, ethnic and demographic variations were tested. Results: All biopsies and blood samples of breast cancer patients tested by PCR methods did not show positivity for HPV DNA sequences in conventional PCRs either by MY09/11 or by GP5+/GP6+/HPV16 E6/E7 primers. Further testing of these samples by real time PCR also failed to detect HPV DNA sequences. Conclusions: Lack of detection of HPV DNA either in the tumor or in the blood DNA of breast cancer patients by both conventional and real time PCR does not support a role of genital HPV in the pathogenesis of breast cancer in Indian women.

Germline BRCA1 mutation analysis in Indian breast/ovarian cancer families

Most of the predisposition to hereditary breast and ovarian cancer has been attributed to inherited defects in two tumor suppressor genes BRCA1 and BRCA2. To explore the contribution of BRCA1 mutations to hereditary breast cancer among Indian women, we examined the coding sequence of the BRCA1 gene in 14 breast cancer patients with a positive family history of breast and/or ovarian cancer. Mutation analysis was carried out using conformation sensitive gel electrophoresis (CSGE) followed by sequencing. Three mutations (21%) in the BRCA1 gene were identified. Two of them are novel mutations of which one is a missense mutation in exon 7 near the RING finger domain, while the other is a one base pair deletion in exon 11 which results in protein truncation. The third mutation, 185delAG, has been previously described in Ashkenazi Jewish families. To our knowledge this is the first report of a study of germline BRCA1 mutation analysis in familial breast cancer in India. Our data from 14 different families suggests a lower prevalence but definite involvement of germline mutations in the BRCA1 gene among Indian women with breast cancer and a family history of breast cancer.

Total Factor Productivity Growth and Output Growth in Indian Electronics Industry in the Liberalization Era: An Empirical Examination

This paper analyses the efficiency and productivity growth of Electronics industry, which is considered one of the vibrant and rapidly growing manufacturing industry sub-sectors of India in the liberalization era since 1991. The main objective of the paper is to examine the extent and growth of Total Factor Productivity (TFP) and its components namely, Technical Efficiency Change (TEC) and Technological Progress (TP) and its contribution to total output growth. In this study, the electronics industry is broadly classified into communication equipments, computer hardware, consumer electronics and other electronics, with the purpose of performing a comparative analysis of productivity growth for each of these sub-sectors for the time period 1993-2004. The paper found that the sub-sectors have improved in terms of economies of scale and contribution of capital.The change in technical efficiency and technological progress moved in reverse directions. Three of the four industry witnessed growth in the output primarily due to TFPG and the contribution of input growth to output growth had been negative/negligible, except for Computer hardware where contribution from both input growth and TFPG to output growth were prominent. The paper explored the possible reasons that addressed the issue of low technical efficiency and technological progress in the industry.

Cramer-Rao bounds for source localization in shallow ocean with generalized Gaussian noise

Localization of underwater acoustic sources is a problem of great interest in the area of ocean acoustics. There exist several algorithms for source localization based on array signal processing.It is of interest to know the theoretical performance limits of these estimators. In this paper we develop expressions for the Cramer-Rao-Bound (CRB) on the variance of direction-of-arrival(DOA) and range-depth estimators of underwater acoustic sources in a shallow range-independent ocean for the case of generalized Gaussian noise. We then study the performance of some of the popular source localization techniques,through simulations, for DOA/range-depth estimation of underwater acoustic sources in shallow ocean by comparing the variance of the estimators with the corresponding CRBs.

Mutations in WDR62, encoding a centrosomal and nuclear protein, in Indian primary microcephaly families with cortical malformations

Primary microcephaly is an autosomal recessive disorder characterized by smaller than normal brain size and mental retardation. It is genetically heterogeneous with seven loci: MCPH1-MCPH7. We have previously reported genetic analysis of 35 families, including the identification of the MCPH7 gene STIL. Of the 35 families, three families showed linkage to the MCPH2 locus. Recent whole-exome sequencing studies have shown that the WDR62 gene, located in the MCPH2 candidate region, is mutated in patients with severe brain malformations. We therefore sequenced the WDR62 gene in our MCPH2 families and identified two novel homozygous protein truncating mutations in two families. Affected individuals in the two families had pachygyria, microlissencephaly, band heterotopias, gyral thickening, and dysplastic cortex. Using immunofluorescence study, we showed that, as with other MCPH proteins, WDR62 localizes to centrosomes in A549, HepG2, and HaCaT cells. In addition, WDR62 was also localized to nucleoli. Bioinformatics analysis predicted two overlapping nuclear localization signals and multiple WD-40 repeats in WDR62. Two other groups have also recently identified WDR62 mutations in MCPH2 families. Our results therefore add further evidence that WDR62 is the MCPH2 gene. The present findings will be helpful in genetic diagnosis of patients linked to the MCPH2 locus.

Governing the local networks in Indian agrarian societies-an MAS perspective

In a networked society, governing advocacy groups and networks through decentralized systems of policy implementation has been the interest of governance network literature. This paper addresses the topic of governing networks in the context of Indian agrarian societies by taking the case example of a welfare scheme for the Indian rural poor. We explore context-specific regulatory dynamics through the situated agent based architectural framework. The effects of various regulatory strategies that can be adopted by governing node are tested under various action arenas through experimental design. Results show the impact of regulatory strategies on the resource dependencies and asymmetries in the network relationships. This indicates that the optimal feasible regulatory strategy in networked society is institutionally rational and is context dependent. Further, we show that situated MAS architecture is a natural fit for institutional understanding of the dynamics (Ostrom et al. in Rules, games, and common-pool resources, 1994).

Mutation analysis of the SLC4A11 gene in Indian families with congenital hereditary endothelial dystrophy 2 and a review of the literature

Purpose: Congenital hereditary endothelial dystrophy 2 (CHED2) is an autosomal recessive disorder caused by mutations in the solute carrier family 4, sodium borate transporter, member 11 (SLC4A11) gene. The purpose of this study was to identify the genetic cause of CHED2 in six Indian families and catalog all known mutations in the SLC4A11 gene. Methods: Peripheral blood samples were collected from individuals of the families with CHED2 and used in genomic DNA isolation. PCR primers were used to amplify the entire coding region including intron-exon junctions of SLC4A11. Amplicons were subsequently sequenced to identify the mutations. Results: DNA sequence analysis of the six families identified four novel (viz., p.Thr262Ile, p.Gly417Arg, p.Cys611Arg, and p.His724Asp) mutations and one known p.Arg869His homozygous mutation in the SLC4A11 gene. The mutation p.Gly417Arg was identified in two families. Conclusions: This study increases the mutation spectrum of the SLC4A11 gene. A review of the literature showed that the total number of mutations in the SLC4A11 gene described to date is 78. Most of the mutations are missense, followed by insertions-deletions. The present study will be helpful in genetic diagnosis of the families reported here.

Narrowband signal detection techniques in shallow ocean by acoustic vector sensor array

This paper presents the formulation and performance analysis of four techniques for detection of a narrowband acoustic source in a shallow range-independent ocean using an acoustic vector sensor (AVS) array. The array signal vector is not known due to the unknown location of the source. Hence all detectors are based on a generalized likelihood ratio test (GLRT) which involves estimation of the array signal vector. One non-parametric and three parametric (model-based) signal estimators are presented. It is shown that there is a strong correlation between the detector performance and the mean-square signal estimation error. Theoretical expressions for probability of false alarm and probability of detection are derived for all the detectors, and the theoretical predictions are compared with simulation results. It is shown that the detection performance of an AVS array with a certain number of sensors is equal to or slightly better than that of a conventional acoustic pressure sensor array with thrice as many sensors.

Automatic Tonic Identification in Indian Art Music: Approaches and Evaluation

The tonic is a fundamental concept in Indian art music. It is the base pitch, which an artist chooses in order to construct the melodies during a rg(a) rendition, and all accompanying instruments are tuned using the tonic pitch. Consequently, tonic identification is a fundamental task for most computational analyses of Indian art music, such as intonation analysis, melodic motif analysis and rg recognition. In this paper we review existing approaches for tonic identification in Indian art music and evaluate them on six diverse datasets for a thorough comparison and analysis. We study the performance of each method in different contexts such as the presence/absence of additional metadata, the quality of audio data, the duration of audio data, music tradition (Hindustani/Carnatic) and the gender of the singer (male/female). We show that the approaches that combine multi-pitch analysis with machine learning provide the best performance in most cases (90% identification accuracy on average), and are robust across the aforementioned contexts compared to the approaches based on expert knowledge. In addition, we also show that the performance of the latter can be improved when additional metadata is available to further constrain the problem. Finally, we present a detailed error analysis of each method, providing further insights into the advantages and limitations of the methods.