88 resultados para Engineering libraries


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In continuation of our studies on the influence of fluoro substitution on the solid state photobehaviour and packing pattern of styrylcoumarins, the results obtained for 4-(3-fluorostyryl)coumarin 1, 4-styryl-6-fluorocoumarin 2 and 4-styryl-7-fluorocoumarin 3 are presented. The configuration of the dimers was established on the basis of crystal packing of 1 and 2 (alpha-packed). A rationale for the significantly lower dimer yield in the crystal for 2 is proposed. In the observed centrosymmetric arrangement of the reactants the C=O ...pi (phenyl) contacts seem to provide additional attractive interactions. C-H ... O and C-H ... F hydrogen bonding seems to provide stability in these structures.

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In continuation of our studies on crystal engineering using fluorine as a steering group, the photobehaviour of di and tri fluoro 4-styrylcoumarins has been examined. It is found that out of the five derivatives, four crystallize into P-packing mode producing syn-HH photodimer upon irradiation whereas the parent hydrocarbon produces an anti K-T dimer. The packing features of the photolabile crystals of 4-(4-fluorostyryl)-6-fluorocoumarin (1), 4-(2,6-difluorostyryl) 6-fluorocoumarin (2) and the photodimer (3a) of 4-(2,6-fluorostyryl)-7-fluorocoumarin (3) have been determined by single crystal X-ray diffraction studies. The stereochemistry of the photodimer of 4-(2-fluorostyryl)-6-fluorocoumarin (4) is deduced based on preliminary X-ray crystallographic data. However, 4-(2,6-difluorostyryl) coumarin (5) is photoinert. The remarkable steering ability of fluorine is established with the molecular packing in the crystal lattice leading to the formation of syn H-H dimer in the above four examples. (C) 1999 Elsevier Science Ltd. All rights reserved.

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The objective of the present in vitro research was to investigate cardiac tissue cell functions (specifically cardiomyocytes and neurons) on poly(lactic-co-glycolic acid) (PLGA) (50:50 wt.%)-carbon nanofiber (CNF) composites to ascertain their potential for myocardial tissue engineering applications. CNF were added to biodegradable PLGA to increase the conductivity and cytocompatibility of pure PLGA. For this reason, different PLGA:CNF ratios (100:0, 75:25, 50:50,25:75, and 0:100 wt.%) were used and the conductivity as well as cytocompatibility of cardiomyocytes and neurons were assessed. Scanning electron microscopy, X-ray diffraction and Raman spectroscopy analysis characterized the microstructure, chemistry, and crystallinity of the materials of interest to this study. The results show that PLGA:CNF materials are conductive and that the conductivity increases as greater amounts of CNF are added to PLGA, from OS m(-1) for pure PLGA (100:0 wt.%) to 5.5 x 10(-3) S m(-1) for pure CNF (0:100 wt.%). The results also indicate that cardiomyocyte density increases with greater amounts of CNF in PLGA (up to 25:75 wt.% PLGA:CNF) for up to 5 days. For neurons a similar trend to cardiomyocytes was observed, indicating that these conductive materials promoted the adhesion and proliferation of two cell types important for myocardial tissue engineering applications. This study thus provides, for the first time, an alternative conductive scaffold using nanotechnology which should be further explored for cardiovascular applications. (C) 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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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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With extensive use of dynamic voltage scaling (DVS) there is increasing need for voltage scalable models. Similarly, leakage being very sensitive to temperature motivates the need for a temperature scalable model as well. We characterize standard cell libraries for statistical leakage analysis based on models for transistor stacks. Modeling stacks has the advantage of using a single model across many gates there by reducing the number of models that need to be characterized. Our experiments on 15 different gates show that we needed only 23 models to predict the leakage across 126 input vector combinations. We investigate the use of neural networks for the combined PVT model, for the stacks, which can capture the effect of inter die, intra gate variations, supply voltage(0.6-1.2 V) and temperature (0 - 100degC) on leakage. Results show that neural network based stack models can predict the PDF of leakage current across supply voltage and temperature accurately with the average error in mean being less than 2% and that in standard deviation being less than 5% across a range of voltage, temperature.

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We investigate the feasibility of developing a comprehensive gate delay and slew models which incorporates output load, input edge slew, supply voltage, temperature, global process variations and local process variations all in the same model. We find that the standard polynomial models cannot handle such a large heterogeneous set of input variables. We instead use neural networks, which are well known for their ability to approximate any arbitrary continuous function. Our initial experiments with a small subset of standard cell gates of an industrial 65 nm library show promising results with error in mean less than 1%, error in standard deviation less than 3% and maximum error less than 11% as compared to SPICE for models covering 0.9- 1.1 V of supply, -40degC to 125degC of temperature, load, slew and global and local process parameters. Enhancing the conventional libraries to be voltage and temperature scalable with similar accuracy requires on an average 4x more SPICE characterization runs.

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We investigate the feasibility of developing a comprehensive gate delay and slew models which incorporates output load, input edge slew, supply voltage, temperature, global process variations and local process variations all in the same model. We find that the standard polynomial models cannot handle such a large heterogeneous set of input variables. We instead use neural networks, which are well known for their ability to approximate any arbitrary continuous function. Our initial experiments with a small subset of standard cell gates of an industrial 65 nm library show promising results with error in mean less than 1%, error in standard deviation less than 3% and maximum error less than 11% as compared to SPICE for models covering 0.9- 1.1 V of supply, -40degC to 125degC of temperature, load, slew and global and local process parameters. Enhancing the conventional libraries to be voltage and temperature scalable with similar accuracy requires on an average 4x more SPICE characterization runs.

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The objective of this work is to develop a systematic methodology for describing hand postures and grasps which is independent of the kinematics and geometry of the hand model which in turn can be used for developing a universal referencing scheme. It is therefore necessary that the scheme be general enough to describe the continuum of hand poses. Indian traditional classical dance form, “Bharathanatyam”, uses 28 single handed gestures, called “mudras”. A Mudra can be perceived as a hand posture with a specific pattern of finger configurations. Using modifiers, complex mudras could be constructed from relatively simple mudras. An adjacency matrix is constructed to describe the relationship among mudras. Various mudra transitions can be obtained from the graph associated with this matrix. Using this matrix, a hierarchy of the mudras is formed. A set of base mudras and modifiers are used for describing how one simple posture of hand can be transformed into another relatively complex one. A canonical set of predefined hand postures and modifiers can be used in digital human modeling to develop standard hand posture libraries.

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Automated synthesis of mechanical designs is an important step towards the development of an intelligent CAD system. Research into methods for supporting conceptual design using automated synthesis has attracted much attention in the past decades. The research work presented here is based on an empirical study of the process of synthesis of multiple state mechanical devices. As a background to the work, the paper explores concepts of what mechanical device, state, single state and multiple state are, and in the context of the above observational studies, attempts to identify the outstanding issues for supporting multiple state synthesis of mechanical devices.