108 resultados para Stone Tool Function

em Indian Institute of Science - Bangalore - Índia


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Increased emphasis on rotorcraft performance and perational capabilities has resulted in accurate computation of aerodynamic stability and control parameters. System identification is one such tool in which the model structure and parameters such as aerodynamic stability and control derivatives are derived. In the present work, the rotorcraft aerodynamic parameters are computed using radial basis function neural networks (RBFN) in the presence of both state and measurement noise. The effect of presence of outliers in the data is also considered. RBFN is found to give superior results compared to finite difference derivatives for noisy data. (C) 2010 Elsevier Inc. All rights reserved.

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We present a method to perform in situ microrheological measurements on monolayers of soft materials undergoing viscoelastic transitions under compression. Using the combination of a Langmuir trough mounted on the inverted microscope stage of a laser scanning confocal microscope we track the motion of individual fluorescent quantum dots partly dispersed in monolayers spread at the air-water interface. From the calculated mean square displacement of the probe particles and extending a well established scheme of the generalized Stokes-Einstein relation in bulk to the interface we arrive at the viscoelastic modulus for the respective monolayers as a function of surface density. Measurements on monolayers of glassy as well as nonglassy polymers and a standard fatty acid clearly show sensitivity of our technique to subtle variations, in the viscoelastic properties of the highly confined materials under compression. Evidence for possible spatial variations of such viscoelastic properties at a given surface density for the fatty acid monolayer is also provided.

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We present a method to perform in situ microrheological measurements on monolayers of soft materials undergoing viscoelastic transitions under compression. Using the combination of a Langmuir trough mounted on the inverted microscope stage of a laser scanning confocal microscope we track the motion of individual fluorescent quantum dots partly dispersed in monolayers spread at the air-water interface. From the calculated mean square displacement of the probe particles and extending a well established scheme of the generalized Stokes-Einstein relation in bulk to the interface we arrive at the viscoelastic modulus for the respective monolayers as a function of surface density. Measurements on monolayers of glassy as well as nonglassy polymers and a standard fatty acid clearly show sensitivity of our technique to subtle variations, in the viscoelastic properties of the highly confined materials under compression. Evidence for possible spatial variations of such viscoelastic properties at a given surface density for the fatty acid monolayer is also provided.

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In engineering design, the end goal is the creation of an artifact, product, system, or process that fulfills some functional requirements at some desired level of performance. As such, knowledge of functionality is essential in a wide variety of tasks in engineering activities, including modeling, generation, modification, visualization, explanation, evaluation, diagnosis, and repair of these artifacts and processes. A formal representation of functionality is essential for supporting any of these activities on computers. The goal of Parts 1 and 2 of this Special Issue is to bring together the state of knowledge of representing functionality in engineering applications from both the engineering and the artificial intelligence (AI) research communities.

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A computational pipeline PocketAnnotate for functional annotation of proteins at the level of binding sites has been proposed in this study. The pipeline integrates three in-house algorithms for site-based function annotation: PocketDepth, for prediction of binding sites in protein structures; PocketMatch, for rapid comparison of binding sites and PocketAlign, to obtain detailed alignment between pair of binding sites. A novel scheme has been developed to rapidly generate a database of non-redundant binding sites. For a given input protein structure, putative ligand-binding sites are identified, matched in real time against the database and the query substructure aligned with the promising hits, to obtain a set of possible ligands that the given protein could bind to. The input can be either whole protein structures or merely the substructures corresponding to possible binding sites. Structure-based function annotation at the level of binding sites thus achieved could prove very useful for cases where no obvious functional inference can be obtained based purely on sequence or fold-level analyses. An attempt has also been made to analyse proteins of no known function from Protein Data Bank. PocketAnnotate would be a valuable tool for the scientific community and contribute towards structure-based functional inference. The web server can be freely accessed at http://proline.biochem.iisc.ernet.in/pocketannotate/.

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The Lovasz θ function of a graph, is a fundamental tool in combinatorial optimization and approximation algorithms. Computing θ involves solving a SDP and is extremely expensive even for moderately sized graphs. In this paper we establish that the Lovasz θ function is equivalent to a kernel learning problem related to one class SVM. This interesting connection opens up many opportunities bridging graph theoretic algorithms and machine learning. We show that there exist graphs, which we call SVM−θ graphs, on which the Lovasz θ function can be approximated well by a one-class SVM. This leads to a novel use of SVM techniques to solve algorithmic problems in large graphs e.g. identifying a planted clique of size Θ(n√) in a random graph G(n,12). A classic approach for this problem involves computing the θ function, however it is not scalable due to SDP computation. We show that the random graph with a planted clique is an example of SVM−θ graph, and as a consequence a SVM based approach easily identifies the clique in large graphs and is competitive with the state-of-the-art. Further, we introduce the notion of a ''common orthogonal labeling'' which extends the notion of a ''orthogonal labelling of a single graph (used in defining the θ function) to multiple graphs. The problem of finding the optimal common orthogonal labelling is cast as a Multiple Kernel Learning problem and is used to identify a large common dense region in multiple graphs. The proposed algorithm achieves an order of magnitude scalability compared to the state of the art.

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Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6-7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and identification.

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We study the performance of a hybrid Graphene-Boron Nitride armchair nanoribbon (a-GNR-BN) n-MOSFET at its ballistic transport limit. We consider three geometric configurations 3p, 3p + 1, and 3p + 2 of a-GNR-BN with BN atoms embedded on either side (2, 4, and 6 BN) on the GNR. Material properties like band gap, effective mass, and density of states of these H-passivated structures are evaluated using the Density Functional Theory. Using these material parameters, self-consistent Poisson-Schrodinger simulations are carried out under the Non Equilibrium Green's Function formalism to calculate the ballistic n-MOSFET device characteristics. For a hybrid nanoribbon of width similar to 5 nm, the simulated ON current is found to be in the range of 265 mu A-280 mu A with an ON/OFF ratio 7.1 x 10(6)-7.4 x 10(6) for a V-DD = 0.68 V corresponding to 10 nm technology node. We further study the impact of randomly distributed Stone Wales (SW) defects in these hybrid structures and only 2.5% degradation of ON current is observed for SW defect density of 3.18%. (C) 2014 AIP Publishing LLC.

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We report the effect of topological as well as lattice vacancy defects on the electro-thermal transport properties of the metallic zigzag graphene nano ribbons at their ballistic limit. We employ the density function theory-Non equilibrium green's function combination to calculate the transmission details. We then present an elaborated study considering the variation in the electrical current and the heat current transport with the change in temperature as well as the voltage gradient across the nano ribbons. The comparative analysis shows, that in the case of topological defects, such as the Stone-Wales defect, the electrical current transport is minimum. Besides, for the voltage gradient of 0.5 Volt and the temperature gradient of 300 K, the heat current transport reduces by similar to 62 % and similar to 50% for the cases of Stones-Wales defect and lattice vacancy defect respectively, compared to that of the perfect one.

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Drosophila melanogaster has served as an excellent model system for understanding the neuronal circuits and molecular mechanisms regulating complex behaviors. The Drosophila female reproductive circuits, in particular, are well studied and can be used as a tool to understand the role of novel genes in neuronal function in general and female reproduction in particular. In the present study, the role of Beadex, a transcription co-activator, in Drosophila female reproduction was assessed by generation of mutant and knock down studies. Null allele of Beadex was generated by transposase induced excision of P-element present within an intron of Beadex gene. The mutant showed highly compromised reproductive abilities as evaluated by reduced fecundity and fertility, abnormal oviposition and more importantly, the failure of sperm release from storage organs. However, no defect was found in the overall ovariole development. Tissue specific, targeted knock down of Beadex indicated that its function in neurons is important for efficient female reproduction, since its neuronal knock down led to compromised female reproductive abilities, similar to Beadex null females. Further, different neuronal class specific knock down studies revealed that Beadex function is required in motor neurons for normal fecundity and fertility of females. Thus, the present study attributes a novel and essential role for Beadex in female reproduction through neurons.

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Background: Understanding channel structures that lead to active sites or traverse the molecule is important in the study of molecular functions such as ion, ligand, and small molecule transport. Efficient methods for extracting, storing, and analyzing protein channels are required to support such studies. Further, there is a need for an integrated framework that supports computation of the channels, interactive exploration of their structure, and detailed visual analysis of their properties. Results: We describe a method for molecular channel extraction based on the alpha complex representation. The method computes geometrically feasible channels, stores both the volume occupied by the channel and its centerline in a unified representation, and reports significant channels. The representation also supports efficient computation of channel profiles that help understand channel properties. We describe methods for effective visualization of the channels and their profiles. These methods and the visual analysis framework are implemented in a software tool, CHEXVIS. We apply the method on a number of known channel containing proteins to extract pore features. Results from these experiments on several proteins show that CHEXVIS performance is comparable to, and in some cases, better than existing channel extraction techniques. Using several case studies, we demonstrate how CHEXVIS can be used to study channels, extract their properties and gain insights into molecular function. Conclusion: CHEXVIS supports the visual exploration of multiple channels together with their geometric and physico-chemical properties thereby enabling the understanding of the basic biology of transport through protein channels. The CHEXVIS web-server is freely available at http://vgl.serc.iisc.ernet.in/chexvis/. The web-server is supported on all modern browsers with latest Java plug-in.

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Inventory Management (IM) plays a decisive role in the enhancement of efficiency and competitiveness of manufacturing enterprises. Therefore, major manufacturing enterprises are following IM practices as a strategy to improve efficiency and achieve competitiveness. However, the spread of IM culture among Small and Medium Enterprises (SMEs) is limited due to lack of initiation, expertise and financial limitations in developed countries, leave alone developing countries. With this backdrop, this paper makes an attempt to ascertain the role and importance of IM practices and performance of SMEs in the machine tools industry of Bangalore, India. The relationship between inventory management practices and inventory cost are probed based on primary data gathered from 91 SMEs. The paper brings out that formal IM practices have a positive impact on the inventory performance of SMEs.

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We find in complementary experiments and event-driven simulations of sheared inelastic hard spheres that the velocity autocorrelation function psi(t) decays much faster than t(-3/2) obtained for a fluid of elastic spheres at equilibrium. Particle displacements are measured in experiments inside a gravity-driven flow sheared by a rough wall. The average packing fraction obtained in the experiments is 0.59, and the packing fraction in the simulations is varied between 0.5 and 0.59. The motion is observed to be diffusive over long times except in experiments where there is layering of particles parallel to boundaries, and diffusion is inhibited between layers. Regardless, a rapid decay of psi(t) is observed, indicating that this is a feature of the sheared dissipative fluid, and is independent of the details of the relative particle arrangements. An important implication of our study is that the non-analytic contribution to the shear stress may not be present in a sheared inelastic fluid, leading to a wider range of applicability of kinetic theory approaches to dense granular matter.

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Although LH is essential for survival and function of the corpus luteum (CL) in higher primates, luteolysis occurs during nonfertile cycles without a discernible decrease in circulating LH levels. Using genome-wide expression analysis, several experiments were performed to examine the processes of luteolysis and rescue of luteal function in monkeys. Induced luteolysis with GnRH receptor antagonist (Cetrorelix) resulted in differential regulation of 3949 genes, whereas replacement with exogenous LH (Cetrorelix plus LH) led to regulation of 4434 genes (1563 down-regulation and 2871 up-regulation). A model system for prostaglandin (PG) F-2 alpha-induced luteolysis in the monkey was standardized and demonstrated that PGF(2 alpha) regulated expression of 2290 genes in the CL. Analysis of the LH-regulated luteal transcriptome revealed that 120 genes were regulated in an antagonistic fashion by PGF(2 alpha). Based on the microarray data, 25 genes were selected for validation by real-time RT-PCR analysis, and expression of these genes was also examined in the CL throughout the luteal phase and from monkeys treated with human chorionic gonadotropin (hCG) to mimic early pregnancy. The results indicated changes in expression of genes favorable to PGF(2 alpha) action during the late to very late luteal phase, and expressions of many of these genes were regulated in an opposite manner by exogenous hCG treatment. Collectively, the findings suggest that curtailment of expression of downstream LH-target genes possibly through PGF(2 alpha) action on the CL is among the mechanisms underlying cross talk between the luteotropic and luteolytic signaling pathways that result in the cessation of luteal function, but hCG is likely to abrogate the PGF(2 alpha)-responsive gene expression changes resulting in luteal rescue crucial for the maintenance of early pregnancy. (Endocrinology 150: 1473-1484, 2009)

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Immunization of proven fertile adult male monkeys (n = 3) with a recombinant FSH receptor protein preparation (oFSHR-P) (representing amino acids 1-134 of the extracellular domain of the receptor Mr similar to 15KDa) resulted in production of receptor blocking antibodies. The ability of the antibody to bind a particulate FSH receptor preparation and receptors in intact granulosa cells was markedly (by 30-80%) inhibited by FSH. Serum T levels and LH receptor function following immunization remained unchanged. The immunized monkeys showed a 50% reduction (p<0.001) in transformation of spermatogonia(2C) to primary spermatocytes (4C) as determined by flow cytometry and the 4C:2C ratio showed a correlative change (R 0.81, p<0.0007) with reduction in fertility index (sperm counts X motility score). Breeding studies indicated that monkeys became infertile between 242-368 days of immunization when the fertility index was in the range of 123+/-76 to 354+/-42 (compared to a value of 1602+/-384 on day 0). As the effects observed ate near identical to that seen following immunization with FSH it is suggestive that oFSHR-P can substitute for FSH in the development of a contraceptive vaccine.