901 resultados para global nonhydrostatic model


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Objective: The purpose of this study was to examine the effect of maternal type 1 diabetes on the structure and function of the embryonic and neonatal mouse heart.

Methods: Type 1 diabetes was induced in female C57BL6/J mice using streptozotocin. Embryonic (n = 105) and neonatal hearts (n = 46) were examined using high-frequency ultrasound (US) and a cohort of E18.5 (n = 34) and 1-day-old pup hearts (n = 27) underwent histological examination.

Results: Global cardiac hypertrophy in late gestation (E18.5) was evident on US in the diabetic group compared to controls with increased interventricular septal (IVS) thickness (0.44 ± 0.08 mm vs 0.36 ± 0.08 mm, P < .05) and increased left ventricular wall thickness (0.38 ± 0.04 mm vs 0.29 mm ± 0.05, P < .01). Isovolumetric relaxation time was initially prolonged in the diabetic group but resolved by E18.5 to control values. Histological examination at E18.5 demonstrated increased transverse measurements (2.42 ± 0.72 mm/g vs 1.86 ± 0.55 mm/g, P < .05) and increased IVS thickness (0.64 ± 0.20 mm/g vs 0.43 ± 0.15 mm/g, P < .05) in diabetic embryos compared to control embryos.

Conclusion: Maternal hyperglycemia has severe effects on offspring with evidence of cardiac impairment and cardiac hypertrophy in the embryo. These effects persisted in the 1-day old but attenuated in the 1-week old suggesting cardiac remodeling after the hyperglycemic milieu of pregnancy is removed

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We perform an extensive study of the properties of global quantum correlations in finite-size one-dimensional quantum spin models at finite temperature. By adopting a recently proposed measure for global quantum correlations (Rulli and Sarandy 2011 Phys. Rev. A 84 042109), called global discord, we show that critical points can be neatly detected even for many-body systems that are not in their ground state. We consider the transverse Ising model, the cluster-Ising model where three-body couplings compete with an Ising-like interaction, and the nearest-neighbor XX Hamiltonian in transverse magnetic field. These models embody our canonical examples showing the sensitivity of global quantum discord close to criticality. For the Ising model, we find a universal scaling of global discord with the critical exponents pertaining to the Ising universality class.

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In this paper, neutral and charged particle dynamics in both the capacitive and inductive modes of an inductively coupled oxygen discharge are presented. Langmuir probes, laser-assisted photodetachment and two-photon laser-induced fluorescence are employed to measure plasma parameters in the 13.56MHz system for a range of plasma powers and gas pressures. It is found that the capacitive mode is more electronegative with lower molecular dissociation compared with the inductive mode. However, the negative ion density in each mode is comparable. A maximum is observed in the negative ion density and fraction with pressure for both modes. The experimental measurements are supplemented by a global model, which includes capacitive and inductive coupling effects. The model and experiments demonstrate that negative ion loss is dominated by ion-ion recombination and electron detachment at low pressures (

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The International Nusantara Stratification and Transport (INSTANT) program measured currents through multiple Indonesian Seas passages simultaneously over a three-year period (from January 2004 to December 2006). The Indonesian Seas region has presented numerous challenges for numerical modelers - the Indonesian Throughflow (ITF) must pass over shallow sills, into deep basins, and through narrow constrictions on its way from the Pacific to the Indian Ocean. As an important region in the global climate puzzle, a number of models have been used to try and best simulate this throughflow. In an attempt to validate our model, we present a comparison between the transports calculated from our model and those calculated from the INSTANT in situ measurements at five passages within the Indonesian Seas (Labani Channel, Lifamatola Passage, Lombok Strait, Ornbai Strait, and Timor Passage). Our Princeton Ocean Model (POM) based regional Indonesian Seas model was originally developed to analyze the influence of bottom topography on the temperature and salinity distributions in the Indonesian seas region, to disclose the path of the South Pacific Water from the continuation of the New Guinea Coastal Current entering the region of interest up to the Lifamatola Passage, and to assess the role of the pressure head in driving the ITF and in determining its total transport. Previous studies found that this model reasonably represents the general long-term flow (seasons) through this region. The INSTANT transports were compared to the results of this regional model over multiple timescales. Overall trends are somewhat represented but changes on timescales shorter than seasonal (three months) and longer than annual were not considered in our model. Normal velocities through each passage during every season are plotted. Daily volume transports and transport-weighted temperature and salinity are plotted and seasonal averages are tabulated.

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As a comparative newly-invented PKM with over-constraints in kinematic chains, the Exechon has attracted extensive attention from the research society. Different from the well-recognized kinematics analysis, the research on the stiffness characteristics of the Exechon still remains as a challenge due to the structural complexity. In order to achieve a thorough understanding of the stiffness characteristics of the Exechon PKM, this paper proposed an analytical kinetostatic model by using the substructure synthesis technique. The whole PKM system is decomposed into a moving platform subsystem, three limb subsystems and a fixed base subsystem, which are connected to each other sequentially through corresponding joints. Each limb body is modeled as a spatial beam with a uniform cross-section constrained by two sets of lumped springs. The equilibrium equation of each individual limb assemblage is derived through finite element formulation and combined with that of the moving platform derived with Newtonian method to construct the governing kinetostatic equations of the system after introducing the deformation compatibility conditions between the moving platform and the limbs. By extracting the 6 x 6 block matrix from the inversion of the governing compliance matrix, the stiffness of the moving platform is formulated. The computation for the stiffness of the Exechon PKM at a typical configuration as well as throughout the workspace is carried out in a quick manner with a piece-by-piece partition algorithm. The numerical simulations reveal a strong position-dependency of the PKM's stiffness in that it is symmetric relative to a work plane due to structural features. At the last stage, the effects of some design variables such as structural, dimensional and stiffness parameters on system rigidity are investigated with the purpose of providing useful information for the structural optimization and performance enhancement of the Exechon PKM. It is worthy mentioning that the proposed methodology of stiffness modeling in this paper can also be applied to other overconstrained PKMs and can evaluate the global rigidity over workplace efficiently with minor revisions.

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Many kinetic models have appeared in literature in past decades using two main approaches: the traditional global kinetics approach, or the more complex micro-kinetics approach. Whether global or micro-kinetics, kinetic models have been based on experimental data obtained at the end of the monolith. The experimental procedure using end pipe analysis may give an accurate overview of the reaction mechanisms that occur; however, the lack of information from within the catalyst can ultimately lead to inaccuracies in the kinetic model and parameters used.

Using SpaciMS, a spatially resolved experimental technique developed at the Queen's University Belfast, information from within the catalyst can be obtained. This minimally invasive technique provides detailed information of the gas concentration and temperature profile from inside the catalytic monolith. This paper presents a kinetic model and simulations validated against experimental data obtained from three positions inside the catalyst monolith at 2, 14, and 26 mm in, using data from the SpaciMS. Also, simulations of end pipe analysis, using a commercial reactor, for the CO oxidation are presented and analyzed. The simulations presented are for varying concentrations of both CO and O2 (0.5 % and 1 % CO, 0.5 % and 2 % O2) for both the global and micro-kinetic approach.

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We study the sensitivity of a MAP configuration of a discrete probabilistic graphical model with respect to perturbations of its parameters. These perturbations are global, in the sense that simultaneous perturbations of all the parameters (or any chosen subset of them) are allowed. Our main contribution is an exact algorithm that can check whether the MAP configuration is robust with respect to given perturbations. Its complexity is essentially the same as that of obtaining the MAP configuration itself, so it can be promptly used with minimal effort. We use our algorithm to identify the largest global perturbation that does not induce a change in the MAP configuration, and we successfully apply this robustness measure in two practical scenarios: the prediction of facial action units with posed images and the classification of multiple real public data sets. A strong correlation between the proposed robustness measure and accuracy is verified in both scenarios.

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We present TANC, a TAN classifier (tree-augmented naive) based on imprecise probabilities. TANC models prior near-ignorance via the Extreme Imprecise Dirichlet Model (EDM). A first contribution of this paper is the experimental comparison between EDM and the global Imprecise Dirichlet Model using the naive credal classifier (NCC), with the aim of showing that EDM is a sensible approximation of the global IDM. TANC is able to deal with missing data in a conservative manner by considering all possible completions (without assuming them to be missing-at-random), but avoiding an exponential increase of the computational time. By experiments on real data sets, we show that TANC is more reliable than the Bayesian TAN and that it provides better performance compared to previous TANs based on imprecise probabilities. Yet, TANC is sometimes outperformed by NCC because the learned TAN structures are too complex; this calls for novel algorithms for learning the TAN structures, better suited for an imprecise probability classifier.

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In this paper we present TANC, i.e., a tree-augmented naive credal classifier based on imprecise probabilities; it models prior near-ignorance via the Extreme Imprecise Dirichlet Model (EDM) (Cano et al., 2007) and deals conservatively with missing data in the training set, without assuming them to be missing-at-random. The EDM is an approximation of the global Imprecise Dirichlet Model (IDM), which considerably simplifies the computation of upper and lower probabilities; yet, having been only recently introduced, the quality of the provided approximation needs still to be verified. As first contribution, we extensively compare the output of the naive credal classifier (one of the few cases in which the global IDM can be exactly implemented) when learned with the EDM and the global IDM; the output of the classifier appears to be identical in the vast majority of cases, thus supporting the adoption of the EDM in real classification problems. Then, by experiments we show that TANC is more reliable than the precise TAN (learned with uniform prior), and also that it provides better performance compared to a previous (Zaffalon, 2003) TAN model based on imprecise probabilities. TANC treats missing data by considering all possible completions of the training set, but avoiding an exponential increase of the computational times; eventually, we present some preliminary results with missing data.

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The Yarkovsky (orbital drift) and YORP (altering spin state) effects are important mechanisms governing the evolution of asteroids. We have included global-selfheating into a new model and demonstrate that it significantly affects YORP predictions.

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Despite its wide implications for many ecological issues, the global pattern of spatial turnover in the occurrence of species has been little studied, unlike the global pattern of species richness. Here, using a database on the breeding distributions of birds, we present the first global maps of variation in spatial turnover for an entire taxonomic class, a pattern that has to date remained largely a matter of conjecture, based on theoretical expectations and extrapolation of inconsistent patterns from different biogeographic realms. We use these maps to test four predictions from niche theory as to the form that this variation should take, namely that turnover should increase with species richness, towards lower latitudes, and with the steepness of environmental gradients and that variation in turnover is determined principally by rare (restricted) species. Contrary to prediction, we show that turnover is high both in areas of extremely low and high species richness, does not increase strongly towards the tropics, and is related both to average environmental conditions and spatial variation in those conditions. These results are closely associated with a further important and novel finding, namely that global patterns of spatial turnover are driven principally by widespread species rather than the restricted ones. This complements recent demonstrations that spatial patterns of species richness are also driven principally by widespread species, and thus provides an important contribution towards a unified model of how terrestrial biodiversity varies both within and between the Earth's major land masses.

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Mathematical models are useful tools for simulation, evaluation, optimal operation and control of solar cells and proton exchange membrane fuel cells (PEMFCs). To identify the model parameters of these two type of cells efficiently, a biogeography-based optimization algorithm with mutation strategies (BBO-M) is proposed. The BBO-M uses the structure of biogeography-based optimization algorithm (BBO), and both the mutation motivated from the differential evolution (DE) algorithm and the chaos theory are incorporated into the BBO structure for improving the global searching capability of the algorithm. Numerical experiments have been conducted on ten benchmark functions with 50 dimensions, and the results show that BBO-M can produce solutions of high quality and has fast convergence rate. Then, the proposed BBO-M is applied to the model parameter estimation of the two type of cells. The experimental results clearly demonstrate the power of the proposed BBO-M in estimating model parameters of both solar and fuel cells.