Competitive Priorities and Strategic Consensus in Emerging Economies: Evidence from India

Purpose – The purpose of this paper is to understand the competitive priorities of manufacturers in India, and examine the level of agreement or strategic consensus between senior executives and manufacturing managers on manufacturing competitive priorities in light of the prevalent culture. Design/methodology/approach – Survey data collected from 156 respondents from 78 manufacturing units based on a national sample in India are used to test the hypotheses using the paired samples t‐tests and multivariate analysis of variance. Findings – A relatively high emphasis by both levels of managers on quality, compared to the other three competitive priorities, is noteworthy and consistent with the global trends. The emphasis on delivery is a close second. Differences in competitive priorities exist across managerial levels in India despite the high power distance and low individualism. Research limitations/implications – The effect of ownership as private or public company was examined and no significant differences found, but data could not be collected on the ownership structure such as wholly owned domestic firms, foreign subsidiaries, or joint ventures. and whether a firm is a supplier to a multinational company. It may also be noted that a majority of the manufacturing companies in this paper came from three industries – chemicals, fabricated metals, and electronic and electrical equipment – and, hence, the findings of the paper might have been unduly influenced by the prevalent practices in these industries. Practical implications – The paper informs global managers and firms seeking to outsource to, or invest in, India that the Indian managers place significantly high emphasis on quality and delivery, but not as much on product variety or ability to make frequent changes to product design and production volume. The managers in India need to take note of prevailing differences in managerial priorities and efforts need to be made such that the priorities are aligned and manufacturing strategy may be unified and coordinated. Originality/value – In the Indian context, this is the first study that deployed multiple respondents to understand the manufacturing competitive priorities, and also the first to examine strategic consensus in operations strategy

Studies on the cytokinins in fruits I. Occurrence and levels of cytokinin-like substances in grape berries at different developmental stages

The occurrence and levels of cytokinin-like substances in the berries of Bangalore Blue grapes were studied at different stages of growth. The concentration of cytokinins was maximum cluring anthesis ancl the first rapid growth period. The level of cytokinins cleclined markedly cluring the lag and subsequent rapid growth phase. Two growth promoting zones were cletectecl by soybean callus bioassay in the thin layer chromatographs of berry extracts, at all stages of sampling. Although the identity of cytokinin-like substances has not been establishecl, the present study supports the hypothesis that besides auxins, gibberellins, abscisic acid and ethylene, cytokinins are also involvecl in the growth and development of grape berries.Untersuchungen über die Cytokinine in FrüchtenI. Vorkommen und Gehalt cytokininartiger Substanzen in Traubenbeeren verschiedenen EntwicklungszustandesIn verschiedenen Entwicklungsstadien der Beeren von Bangalore Blue wurden das Auftreten und die Menge cytokininartiger Substanzen untersucht. Die Cytokininkonzentration war während der Anthese und der ersten Phase raschen Wachstums am höchsten. Während der anschließenden Phase verlangsamten Wachstums und der darauf folgenden Phase erneuten starken Wachstums fiel die Cytokininkonzentration deutlich ab. Mit Hilfe des Sojabohnenkallus-Tests wurden auf den Dünnschichtchromatogrammen von Beerenextrakten aller Entwicklungsstadien zwei wachstumsfördernde Zonen nachgewiesen. Obgleich die cytokininartigen Substanzen nicht identifiziert wurden, wird durch die vorliegende Untersuchung doch die Hypothese gestützt, daß neben Auxinen, Gibberellinen, Abscisinsäure und Äthylen auch Cytokinine in das Wachstums- und Entwicklungsgeschehen der Traubenbeeren eingeschaltet sind

Bioreactor analyses of tissue ingrowth, ongrowth and remodelling around implants: an alternative to live animal testing

Introduction: Preclinical assessment of bone remodelling onto, into or around novel implant technologies is underpinned by a large live animal testing burden. The aim of this study was to explore whether a lab-based bioreactor model could provide similar insight. Method: Twelve ex vivo trabecular bone cylinders were extracted from porcine femora and were implanted with additively manufactured stochastic porous titanium implants. Half were cultured dynamically, in a bioreactor with continuous fluid flow and daily cyclic loading, and half in static well plates. Tissue ongrowth, ingrowth and remodelling around the implants were evaluated with imaging and mechanical testing. Results: For both culture conditions, scanning electron microscopy (SEM) revealed bone ongrowth; widefield, backscatter SEM, micro computed tomography scanning, and histology revealed mineralisation inside the implant pores; and histology revealed woven bone formation and bone resorption around the implant. The imaging evidence of this tissue ongrowth, ingrowth and remodelling around the implant was greater for the dynamically cultured samples, and the mechanical testing revealed that the dynamically cultured samples had approximately three times greater push-through fixation strength (p < 0.05). Discussion: Ex vivo bone models enable the analysis of tissue remodelling onto, into and around porous implants in the lab. While static culture conditions exhibited some characteristics of bony adaptation to implantation, simulating physiological conditions with a bioreactor led to an accelerated response

Properties of Piezoelectric Pzt Thin Films for Microactuator Applications

The piezoelectric properties of lead zirconate titanate (PZT) thin films deposited on thick silicon substrates and thin silicon membranes were investigated using optical interferometry. The effect of the geometrical constraints and clamping effects on the piezoelectric response is discussed. The study of the dielectric permittivity and the loss as a function of the amplitude of the alternating electric field reveals that extrinsic contributions to the dielectric permittivity become active at large fields. The DC electric field has the effect of freezing out the extrinsic contributions. The influence of the dielectric loss on the piezoelectric properties is discussed

Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)

We describe AlphaFold, the protein structure prediction system that was entered by the group A7D in CASP13 Submissions were made by three free-modelling methods which combine the predictions of three neural networks. All three systems were guided by predictions of distances between pairs of residues produced by a neural network. Two systems assembled fragments produced by a generative neural network, one using scores from a network trained to regress GDT_TS. The third system shows that simple gradient descent on a properly constructed potential is able to perform on-par with more expensive traditional search techniques and without requiring domain segmentation. In the CASP13 free-modelling assessors' ranking by summed z-scores, this system scored highest with 68.3 vs 48.2 for the next closest group. (An average GDT_TS of 61.4.) The system produced high-accuracy structures (with GDT_TS scores of 70 or higher) for 11 out of 43 free-modelling domains. Despite not explicitly using template information, the results in the template category were comparable to the best performing template-based methods

Improved design for SOI based evanescently coupled multilayer spot-size converter

We report an improved version of a spot-size converter (SSC) consisting of a silicon nanowire evanescently coupled to a phase-matched Poly-Si multilayer structure. With wider transversal dimensions the multilayer structure expands the mode significantly thus increasing the coupling efficiency with the conventional single-mode fiber. Detailed optimization process of a 17-layer based SSC is discussed and its coupling efficiency with a high-NA fiber of radius 2 μm is obtained as 98% providing only 0.087 dB loss. Vertical alignment tolerance between the optimized SSC and a high-NA fiber of radius 2 μm is also shown. This novel design does not consist of a taper and can be fabricated by using CMOS compatible process. It has a short device length and more relaxed alignment tolerances with the fiber. Full-vectorial and computationally efficient finite element method and the least squares boundary residual method have been used for the analysis and optimization of the proposed structure

Improved protein structure prediction using potentials from deep learning

Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence1. This problem is of fundamental importance as the structure of a protein largely determines its function2; however, protein structures can be difficult to determine experimentally. Considerable progress has recently been made by leveraging genetic information. It is possible to infer which amino acid residues are in contact by analysing covariation in homologous sequences, which aids in the prediction of protein structures3. Here we show that we can train a neural network to make accurate predictions of the distances between pairs of residues, which convey more information about the structure than contact predictions. Using this information, we construct a potential of mean force4 that can accurately describe the shape of a protein. We find that the resulting potential can be optimized by a simple gradient descent algorithm to generate structures without complex sampling procedures. The resulting system, named AlphaFold, achieves high accuracy, even for sequences with fewer homologous sequences. In the recent Critical Assessment of Protein Structure Prediction5 (CASP13)—a blind assessment of the state of the field—AlphaFold created high-accuracy structures (with template modelling (TM) scores6 of 0.7 or higher) for 24 out of 43 free modelling domains, whereas the next best method, which used sampling and contact information, achieved such accuracy for only 14 out of 43 domains. AlphaFold represents a considerable advance in protein-structure prediction. We expect this increased accuracy to enable insights into the function and malfunction of proteins, especially in cases for which no structures for homologous proteins have been experimentally determined7

Scintillation Counters for the D0 Muon Upgrade

We present the results of an upgrade to the D0 muon system. Scintillating counters have been added to the existing central D0 muon system to provide rejection for cosmic ray muons and out-of-time background, and to provide additional fast timing information for muons in an upgraded Tevatron. Performance and results from the 1994-1996 Tevatron run are presented.Comment: 30 pages, 25 postscript figure