22 resultados para Differential Inclusions with Constraints

em CentAUR: Central Archive University of Reading - UK


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Fish-oil supplementation can reduce circulating triacylglycerol (TG) levels and cardiovascular risk. This study aimed to assess independent associations between changes in platelet eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) and fasting and postprandial (PP) lipoprotein concentrations and LDL oxidation status, following fish-oil intervention. Fiftyfive mildly hypertriacylglycerolaemic (TG 1·5–4·0 mmol/l) men completed a double-blind placebo controlled cross over study, where individuals consumed 6 g fish oil (3 g EPA � DHA) or 6 g olive oil (placebo)/d for two 6-week intervention periods, with a 12-week wash-out period in between. Fish-oil intervention resulted in a significant increase in the platelet phospholipid EPA (+491 %, P,0·001) and DHA (+44 %, P,0·001) content and a significant decrease in the arachidonic acid (210 %, P,0·001) and g-linolenic acid (224 %, P,0·001) levels. A 30% increase in ex vivo LDL oxidation (P,0·001) was observed. In addition, fish oil resulted in a significant decrease in fasting and PP TG levels (P,0·001), PP non-esterified fatty acid (NEFA) levels, and in the percentage LDL as LDL-3 (P�0·040), and an increase in LDLcholesterol (P�0·027). In multivariate analysis, changes in platelet phospholipid DHA emerged as being independently associated with the rise in LDL-cholesterol, accounting for 16% of the variability in this outcome measure (P�0·030). In contrast, increases in platelet EPA were independently associated with the reductions in fasting (P�0·046) and PP TG (P�0·023), and PP NEFA (P�0·015), explaining 15–20% and 25% of the variability in response respectively. Increases in platelet EPA � DHA were independently and positively associated with the increase in LDL oxidation (P�0·011). EPA and DHA may have differential effects on plasma lipids in mildly hypertriacylglycerolaemic men.

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Adaptive methods which “equidistribute” a given positive weight function are now used fairly widely for selecting discrete meshes. The disadvantage of such schemes is that the resulting mesh may not be smoothly varying. In this paper a technique is developed for equidistributing a function subject to constraints on the ratios of adjacent steps in the mesh. Given a weight function $f \geqq 0$ on an interval $[a,b]$ and constants $c$ and $K$, the method produces a mesh with points $x_0 = a,x_{j + 1} = x_j + h_j ,j = 0,1, \cdots ,n - 1$ and $x_n = b$ such that\[ \int_{xj}^{x_{j + 1} } {f \leqq c\quad {\text{and}}\quad \frac{1} {K}} \leqq \frac{{h_{j + 1} }} {{h_j }} \leqq K\quad {\text{for}}\, j = 0,1, \cdots ,n - 1 . \] A theoretical analysis of the procedure is presented, and numerical algorithms for implementing the method are given. Examples show that the procedure is effective in practice. Other types of constraints on equidistributing meshes are also discussed. The principal application of the procedure is to the solution of boundary value problems, where the weight function is generally some error indicator, and accuracy and convergence properties may depend on the smoothness of the mesh. Other practical applications include the regrading of statistical data.

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Interaction of G-protein-coupled receptors with beta-arrestins is an important step in receptor desensitization and in triggering "alternative" signals. By means of confocal microscopy and fluorescence resonance energy transfer, we have investigated the internalization of the human P2Y receptors 1, 2, 4, 6, 11, and 12 and their interaction with beta-arrestin-1 and -2. Co-transfection of each individual P2Y receptor with beta-arrestin-1-GFP or beta-arrestin-2-YFP into HEK-293 cells and stimulation with the corresponding agonists resulted in a receptor-specific interaction pattern. The P2Y(1) receptor stimulated with ADP strongly translocated beta-arrestin-2-YFP, whereas only a slight translocation was observed for beta-arrestin-1-GFP. The P2Y(4) receptor exhibited equally strong translocation for beta-arrestin-1-GFP and beta-arrestin-2YFP when stimulated with UTP. The P2Y(6), P2Y(11), and P2Y(12) receptor internalized only when GRK2 was additionally cotransfected, but beta-arrestin translocation was only visible for the P2Y(6) and P2Y(11) receptor. The P2Y(2) receptor showed a beta-arrestin translocation pattern that was dependent on the agonist used for stimulation. UTP translocated beta-arrestin-1-GFP and beta-arrestin-2-YFP equally well, whereas ATP translocated beta-arrestin-1-GFP to a much lower extent than beta-arrestin2- YFP. The same agonist-dependent pattern was seen in fluorescence resonance energy transfer experiments between the fluorescently labeled P2Y(2) receptor and beta-arrestins. Thus, the P2Y(2) receptor would be classified as a class A receptor when stimulated with ATP or as a class B receptor when stimulated with UTP. The ligand-specific recruitment of beta-arrestins by ATP and UTP stimulation of P2Y(2) receptors was further found to result in differential stimulation of ERK phosphorylation. This suggests that the two different agonists induce distinct active states of this receptor that show differential interactions with beta-arrestins.

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Hidden Markov Models (HMMs) have been successfully applied to different modelling and classification problems from different areas over the recent years. An important step in using HMMs is the initialisation of the parameters of the model as the subsequent learning of HMM’s parameters will be dependent on these values. This initialisation should take into account the knowledge about the addressed problem and also optimisation techniques to estimate the best initial parameters given a cost function, and consequently, to estimate the best log-likelihood. This paper proposes the initialisation of Hidden Markov Models parameters using the optimisation algorithm Differential Evolution with the aim to obtain the best log-likelihood.

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A direct method is presented for determining the uncertainty in reservoir pressure, flow, and net present value (NPV) using the time-dependent, one phase, two- or three-dimensional equations of flow through a porous medium. The uncertainty in the solution is modelled as a probability distribution function and is computed from given statistical data for input parameters such as permeability. The method generates an expansion for the mean of the pressure about a deterministic solution to the system equations using a perturbation to the mean of the input parameters. Hierarchical equations that define approximations to the mean solution at each point and to the field covariance of the pressure are developed and solved numerically. The procedure is then used to find the statistics of the flow and the risked value of the field, defined by the NPV, for a given development scenario. This method involves only one (albeit complicated) solution of the equations and contrasts with the more usual Monte-Carlo approach where many such solutions are required. The procedure is applied easily to other physical systems modelled by linear or nonlinear partial differential equations with uncertain data.

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We give a characterisation of the spectral properties of linear differential operators with constant coefficients, acting on functions defined on a bounded interval, and determined by general linear boundary conditions. The boundary conditions may be such that the resulting operator is not selfadjoint. We associate the spectral properties of such an operator $S$ with the properties of the solution of a corresponding boundary value problem for the partial differential equation $\partial_t q \pm iSq=0$. Namely, we are able to establish an explicit correspondence between the properties of the family of eigenfunctions of the operator, and in particular whether this family is a basis, and the existence and properties of the unique solution of the associated boundary value problem. When such a unique solution exists, we consider its representation as a complex contour integral that is obtained using a transform method recently proposed by Fokas and one of the authors. The analyticity properties of the integrand in this representation are crucial for studying the spectral theory of the associated operator.

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Accuracy and mesh generation are key issues for the high-resolution hydrodynamic modelling of the whole Great Barrier Reef. Our objective is to generate suitable unstructured grids that can resolve topological and dynamical features like tidal jets and recirculation eddies in the wake of islands. A new strategy is suggested to refine the mesh in areas of interest taking into account the bathymetric field and an approximated distance to islands and reefs. Such a distance is obtained by solving an elliptic differential operator, with specific boundary conditions. Meshes produced illustrate both the validity and the efficiency of the adaptive strategy. Selection of refinement and geometrical parameters is discussed. (c) 2006 Elsevier Ltd. All rights reserved.

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A key step in many numerical schemes for time-dependent partial differential equations with moving boundaries is to rescale the problem to a fixed numerical mesh. An alternative approach is to use a moving mesh that can be adapted to focus on specific features of the model. In this paper we present and discuss two different velocity-based moving mesh methods applied to a two-phase model of avascular tumour growth formulated by Breward et al. (2002) J. Math. Biol. 45(2), 125-152. Each method has one moving node which tracks the moving boundary. The first moving mesh method uses a mesh velocity proportional to the boundary velocity. The second moving mesh method uses local conservation of volume fraction of cells (masses). Our results demonstrate that these moving mesh methods produce accurate results, offering higher resolution where desired whilst preserving the balance of fluxes and sources in the governing equations.

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Dystrophin, the 427 x 10(3) Mr product of the Duchenne muscular dystrophy (DMD) gene, was studied in human foetal skeletal muscle from 9 to 26 weeks of gestation. Dystrophin could be detected from at least 9 weeks of gestation at the sarcolemmal membrane of most myotubes, though there was differential staining with antibodies raised to various regions of the protein. Dystrophin immunostaining increased and became more uniform with age and by 26 weeks of gestation there was intense sarcolemmal staining of all myotubes. On a Western blot, a doublet of smaller relative molecular mass than that seen in adult tissue was detected in all foetuses studied. There was a gradual increase in abundance of the upper band from 9 to 26 weeks, and the lower band, although present in low amounts in young foetuses, increased significantly between 20 and 26 weeks of gestation. These data indicate that there are several specific isoforms of dystrophin present in developing skeletal muscle, though the role of these is unknown.

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This paper investigates the impact of aerosol forcing uncertainty on the robustness of estimates of the twentieth-century warming attributable to anthropogenic greenhouse gas emissions. Attribution analyses on three coupled climate models with very different sensitivities and aerosol forcing are carried out. The Third Hadley Centre Coupled Ocean - Atmosphere GCM (HadCM3), Parallel Climate Model (PCM), and GFDL R30 models all provide good simulations of twentieth-century global mean temperature changes when they include both anthropogenic and natural forcings. Such good agreement could result from a fortuitous cancellation of errors, for example, by balancing too much ( or too little) greenhouse warming by too much ( or too little) aerosol cooling. Despite a very large uncertainty for estimates of the possible range of sulfate aerosol forcing obtained from measurement campaigns, results show that the spatial and temporal nature of observed twentieth-century temperature change constrains the component of past warming attributable to anthropogenic greenhouse gases to be significantly greater ( at the 5% level) than the observed warming over the twentieth century. The cooling effects of aerosols are detected in all three models. Both spatial and temporal aspects of observed temperature change are responsible for constraining the relative roles of greenhouse warming and sulfate cooling over the twentieth century. This is because there are distinctive temporal structures in differential warming rates between the hemispheres, between land and ocean, and between mid- and low latitudes. As a result, consistent estimates of warming attributable to greenhouse gas emissions are obtained from all three models, and predictions are relatively robust to the use of more or less sensitive models. The transient climate response following a 1% yr(-1) increase in CO2 is estimated to lie between 2.2 and 4 K century(-1) (5-95 percentiles).

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Feathers are composed of a structure that, whilst being very light, is able to withstand the large aerodynamic forces exerted upon them during flight. To explore the contribution of molecular orientation to feather keratin mechanical properties, we have examined the nanoscopic organisation of the keratin molecules by X-ray diffraction techniques and have confirmed a link between this and the Young's modulus of the feather rachis. Our results indicate that along the rachis length, from calamus to tip, the keratin molecules become more aligned than at the calamus before returning to a state of higher mis-orientation towards the tip of the rachis. We have also confirmed the general trend of increasing Young's modulus with distance along the rachis. Furthermore, we report a distinct difference in the patterns of orientation of beta-keratin in the feathers of flying and flightless birds. The trend for increased modulus along the feathers of volant birds is absent in the flightless ostrich.

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This paper illustrates how nonlinear programming and simulation tools, which are available in packages such as MATLAB and SIMULINK, can easily be used to solve optimal control problems with state- and/or input-dependent inequality constraints. The method presented is illustrated with a model of a single-link manipulator. The method is suitable to be taught to advanced undergraduate and Master's level students in control engineering.

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We present a novel topology of the radial basis function (RBF) neural network, referred to as the boundary value constraints (BVC)-RBF, which is able to automatically satisfy a set of BVC. Unlike most existing neural networks whereby the model is identified via learning from observational data only, the proposed BVC-RBF offers a generic framework by taking into account both the deterministic prior knowledge and the stochastic data in an intelligent manner. Like a conventional RBF, the proposed BVC-RBF has a linear-in-the-parameter structure, such that it is advantageous that many of the existing algorithms for linear-in-the-parameters models are directly applicable. The BVC satisfaction properties of the proposed BVC-RBF are discussed. Finally, numerical examples based on the combined D-optimality-based orthogonal least squares algorithm are utilized to illustrate the performance of the proposed BVC-RBF for completeness.