32 resultados para Matrix of complex negotiation
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Pack aluminide coating is a useful method for conferring oxidation resistance on nickel-base superalloys. Nominally, these coatings have a matrix composed of a Ni-Al based B2-type phase (commonly denoted as Β). However, following high-temperature exposure in oxidative envi-ronments, aluminum is depleted from the coating. Aluminum depletion in turn, leads to de-stabilization of the Β phase, resulting in the formation of a characteristic lathlike Β-derivative microstructure. This article presents a transmission electron microscopy study of the formation of the lathlike Β-derivative microstructure using bulk nickel aluminides as model alloys. In the bulk nickel aluminides, the lathlike microstructure has been found to correspond to two distinct components: L10-type martensite and a new Β derivative. The new Β derivative is characterized and the conditions associated with the presence of this feature are identified and compared with those leading to the formation of the L10 martensitic phase. © 1995 The Minerals, Metals & Material Society.
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We measure complex amplitude of scattered wave in the far field, and justify theoretically and numerically solution of the inverse scattering problem. This allows single-shot reconstructing of dielectric function distribution during direct femtosecond laser micro-fabrication.
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We present experimental studies and numerical modeling based on a combination of the Bidirectional Beam Propagation Method and Finite Element Modeling that completely describes the wavelength spectra of point by point femtosecond laser inscribed fiber Bragg gratings, showing excellent agreement with experiment. We have investigated the dependence of different spectral parameters such as insertion loss, all dominant cladding and ghost modes and their shape relative to the position of the fiber Bragg grating in the core of the fiber. Our model is validated by comparing model predictions with experimental data and allows for predictive modeling of the gratings. We expand our analysis to more complicated structures, where we introduce symmetry breaking; this highlights the importance of centered gratings and how maintaining symmetry contributes to the overall spectral quality of the inscribed Bragg gratings. Finally, the numerical modeling is applied to superstructure gratings and a comparison with experimental results reveals a capability for dealing with complex grating structures that can be designed with particular wavelength characteristics.
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This paper considers the global synchronisation of a stochastic version of coupled map lattices networks through an innovative stochastic adaptive linear quadratic pinning control methodology. In a stochastic network, each state receives only noisy measurement of its neighbours' states. For such networks we derive a generalised Riccati solution that quantifies and incorporates uncertainty of the forward dynamics and inverse controller in the derivation of the stochastic optimal control law. The generalised Riccati solution is derived using the Lyapunov approach. A probabilistic approximation type algorithm is employed to estimate the conditional distributions of the state and inverse controller from historical data and quantifying model uncertainties. The theoretical derivation is complemented by its validation on a set of representative examples.
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Design verification in the digital domain, using model-based principles, is a key research objective to address the industrial requirement for reduced physical testing and prototyping. For complex assemblies, the verification of design and the associated production methods is currently fragmented, prolonged and sub-optimal, as it uses digital and physical verification stages that are deployed in a sequential manner using multiple systems. This paper describes a novel, hybrid design verification methodology that integrates model-based variability analysis with measurement data of assemblies, in order to reduce simulation uncertainty and allow early design verification from the perspective of satisfying key assembly criteria.
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Computational and communication complexities call for distributed, robust, and adaptive control. This paper proposes a promising way of bottom-up design of distributed control in which simple controllers are responsible for individual nodes. The overall behavior of the network can be achieved by interconnecting such controlled loops in cascade control for example and by enabling the individual nodes to share information about data with their neighbors without aiming at unattainable global solution. The problem is addressed by employing a fully probabilistic design, which can cope with inherent uncertainties, that can be implemented adaptively and which provide a systematic rich way to information sharing. This paper elaborates the overall solution, applies it to linear-Gaussian case, and provides simulation results.
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The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.
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BACKGROUND: Recombinant protein production is universally employed as a solution to obtain the milligram to gram quantities of a given protein required for applications as diverse as structural genomics and biopharmaceutical manufacture. Yeast is a well-established recombinant host cell for these purposes. In this study we wanted to investigate whether our respiratory Saccharomyces cerevisiae strain, TM6*, could be used to enhance the productivity of recombinant proteins over that obtained from corresponding wild type, respiro-fermentative strains when cultured under the same laboratory conditions. RESULTS: Here we demonstrate at least a doubling in productivity over wild-type strains for three recombinant membrane proteins and one recombinant soluble protein produced in TM6* cells. In all cases, this was attributed to the improved biomass properties of the strain. The yield profile across the growth curve was also more stable than in a wild-type strain, and was not further improved by lowering culture temperatures. This has the added benefit that improved yields can be attained rapidly at the yeast's optimal growth conditions. Importantly, improved productivity could not be reproduced in wild-type strains by culturing them under glucose fed-batch conditions: despite having achieved very similar biomass yields to those achieved by TM6* cultures, the total volumetric yields were not concomitantly increased. Furthermore, the productivity of TM6* was unaffected by growing cultures in the presence of ethanol. These findings support the unique properties of TM6* as a microbial cell factory. CONCLUSIONS: The accumulation of biomass in yeast cell factories is not necessarily correlated with a proportional increase in the functional yield of the recombinant protein being produced. The respiratory S. cerevisiae strain reported here is therefore a useful addition to the matrix of production hosts currently available as its improved biomass properties do lead to increased volumetric yields without the need to resort to complex control or cultivation schemes. This is anticipated to be of particular value in the production of challenging targets such as membrane proteins.
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The development of increasingly powerful computers, which has enabled the use of windowing software, has also opened the way for the computer study, via simulation, of very complex physical systems. In this study, the main issues related to the implementation of interactive simulations of complex systems are identified and discussed. Most existing simulators are closed in the sense that there is no access to the source code and, even if it were available, adaptation to interaction with other systems would require extensive code re-writing. This work aims to increase the flexibility of such software by developing a set of object-oriented simulation classes, which can be extended, by subclassing, at any level, i.e., at the problem domain, presentation or interaction levels. A strategy, which involves the use of an object-oriented framework, concurrent execution of several simulation modules, use of a networked windowing system and the re-use of existing software written in procedural languages, is proposed. A prototype tool which combines these techniques has been implemented and is presented. It allows the on-line definition of the configuration of the physical system and generates the appropriate graphical user interface. Simulation routines have been developed for the chemical recovery cycle of a paper pulp mill. The application, by creation of new classes, of the prototype to the interactive simulation of this physical system is described. Besides providing visual feedback, the resulting graphical user interface greatly simplifies the interaction with this set of simulation modules. This study shows that considerable benefits can be obtained by application of computer science concepts to the engineering domain, by helping domain experts to tailor interactive tools to suit their needs.
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Methods of dynamic modelling and analysis of structures, for example the finite element method, are well developed. However, it is generally agreed that accurate modelling of complex structures is difficult and for critical applications it is necessary to validate or update the theoretical models using data measured from actual structures. The techniques of identifying the parameters of linear dynamic models using Vibration test data have attracted considerable interest recently. However, no method has received a general acceptance due to a number of difficulties. These difficulties are mainly due to (i) Incomplete number of Vibration modes that can be excited and measured, (ii) Incomplete number of coordinates that can be measured, (iii) Inaccuracy in the experimental data (iv) Inaccuracy in the model structure. This thesis reports on a new approach to update the parameters of a finite element model as well as a lumped parameter model with a diagonal mass matrix. The structure and its theoretical model are equally perturbed by adding mass or stiffness and the incomplete number of eigen-data is measured. The parameters are then identified by an iterative updating of the initial estimates, by sensitivity analysis, using eigenvalues or both eigenvalues and eigenvectors of the structure before and after perturbation. It is shown that with a suitable choice of the perturbing coordinates exact parameters can be identified if the data and the model structure are exact. The theoretical basis of the technique is presented. To cope with measurement errors and possible inaccuracies in the model structure, a well known Bayesian approach is used to minimize the least squares difference between the updated and the initial parameters. The eigen-data of the structure with added mass or stiffness is also determined using the frequency response data of the unmodified structure by a structural modification technique. Thus, mass or stiffness do not have to be added physically. The mass-stiffness addition technique is demonstrated by simulation examples and Laboratory experiments on beams and an H-frame.
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Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics.
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Background - Lung cancer is the commonest cause of cancer in Scotland and is usually advanced at diagnosis. Median time between symptom onset and consultation is 14 weeks, so an intervention to prompt earlier presentation could support earlier diagnosis and enable curative treatment in more cases. Aim - To develop and optimise an intervention to reduce the time between onset and first consultation with symptoms that might indicate lung cancer. Design and setting - Iterative development of complex healthcare intervention according to the MRC Framework conducted in Northeast Scotland. Method - The study produced a complex intervention to promote early presentation of lung cancer symptoms. An expert multidisciplinary group developed the first draft of the intervention based on theory and existing evidence. This was refined following focus groups with health professionals and high-risk patients. Results - First draft intervention components included: information communicated persuasively, demonstrations of early consultation and its benefits, behaviour change techniques, and involvement of spouses/partners. Focus groups identified patient engagement, achieving behavioural change, and conflict at the patient–general practice interface as challenges and measures were incorporated to tackle these. Final intervention delivery included a detailed self-help manual and extended consultation with a trained research nurse at which specific action plans were devised. Conclusion -The study has developed an intervention that appeals to patients and health professionals and has theoretical potential for benefit. Now it requires evaluation.
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The microstructural stability of aluminide diffusion coatings, prepared by means of a two-stage pack-aluminization treatment on single-crystal nickel-base superalloy substrates, is considered in this article. Edge-on specimens of coated superalloy are studied using transmission electron microscopy (TEM). The effects of coating thickness and post-coating heat treatment (duration, temperature, and atmosphere) on coating microstructure are examined. The article discusses the partial transformation of the matrix of the coating, from a B2-type phase (nominally NiAl) to a L12 phase (nominally Ni3(Al, Ti)), during exposure at temperatures of 850 °C and 950 °C in air and in vacuum for up to 138 hours. Three possible processes that can account for decom- position of the coating matrix are investigated, namely, interdiffusion between the coating and the substrate, oxidation of the coating surface, and aging of the coating. Of these processes, aging of the coating is shown to be the predominant factor in the coating transformation under the conditions considered. © 1992 The Minerals, Metals and Materials Society, and ASM International.
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The purpose of this study was to investigate the effects of elastic anisotropy on nanoindentation measurements in human tibial cortical bone. Nanoindentation was conducted in 12 different directions in three principal planes for both osteonic and interstitial lamellae. The experimental indentation modulus was found to vary with indentation direction and showed obvious anisotropy (oneway analysis of variance test, P < 0.0001). Because experimental indentation modulus in a specific direction is determined by all of the elastic constants of cortical bone, a complex theoretical model is required to analyze the experimental results. A recently developed analysis of indentation for the properties of anisotropic materials was used to quantitatively predict indentation modulus by using the stiffness matrix of human tibial cortical bone, which was obtained from previous ultrasound studies. After allowing for the effects of specimen preparation (dehydrated specimens in nanoindentation tests vs. moist specimens in ultrasound tests) and the structural properties of bone (different microcomponents with different mechanical properties), there were no statistically significant differences between the corrected experimental indentation modulus (Mexp) values and corresponding predicted indentation modulus (Mpre) values (two-tailed unpaired t-test, P < 0.5). The variation of Mpre values was found to exhibit the same trends as the corrected Mexp data. These results show that the effects of anisotropy on nanoindentation measurements can be quantitatively evaluated. © 2002 Orthopaedic Research Society. Published by Elsevier Science Ltd. All rights reserved.