1,591 research outputs found

    Efficient Localization of Discontinuities in Complex Computational Simulations

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    Surrogate models for computational simulations are input-output approximations that allow computationally intensive analyses, such as uncertainty propagation and inference, to be performed efficiently. When a simulation output does not depend smoothly on its inputs, the error and convergence rate of many approximation methods deteriorate substantially. This paper details a method for efficiently localizing discontinuities in the input parameter domain, so that the model output can be approximated as a piecewise smooth function. The approach comprises an initialization phase, which uses polynomial annihilation to assign function values to different regions and thus seed an automated labeling procedure, followed by a refinement phase that adaptively updates a kernel support vector machine representation of the separating surface via active learning. The overall approach avoids structured grids and exploits any available simplicity in the geometry of the separating surface, thus reducing the number of model evaluations required to localize the discontinuity. The method is illustrated on examples of up to eleven dimensions, including algebraic models and ODE/PDE systems, and demonstrates improved scaling and efficiency over other discontinuity localization approaches

    A continuous analogue of the tensor-train decomposition

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    We develop new approximation algorithms and data structures for representing and computing with multivariate functions using the functional tensor-train (FT), a continuous extension of the tensor-train (TT) decomposition. The FT represents functions using a tensor-train ansatz by replacing the three-dimensional TT cores with univariate matrix-valued functions. The main contribution of this paper is a framework to compute the FT that employs adaptive approximations of univariate fibers, and that is not tied to any tensorized discretization. The algorithm can be coupled with any univariate linear or nonlinear approximation procedure. We demonstrate that this approach can generate multivariate function approximations that are several orders of magnitude more accurate, for the same cost, than those based on the conventional approach of compressing the coefficient tensor of a tensor-product basis. Our approach is in the spirit of other continuous computation packages such as Chebfun, and yields an algorithm which requires the computation of "continuous" matrix factorizations such as the LU and QR decompositions of vector-valued functions. To support these developments, we describe continuous versions of an approximate maximum-volume cross approximation algorithm and of a rounding algorithm that re-approximates an FT by one of lower ranks. We demonstrate that our technique improves accuracy and robustness, compared to TT and quantics-TT approaches with fixed parameterizations, of high-dimensional integration, differentiation, and approximation of functions with local features such as discontinuities and other nonlinearities

    Inhibitory Activity of Leaves Extracts of Citrullus colocynthis Schrad. on HT29 Human Colon Cancer Cells

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    Aims: Citrullus colocynthis is a plant endemic in Asia, Africa and in the Mediterranean basin. It is used in folk medicine against infections, inflammations and cardiovascular and immune-related diseases. There are further evidences of the use of Citrullus colocynthis Schrad in the treatment of cancer in traditional practices. The present study aimed to determine the potential antiproliferative effects of different Citrullus colocynthis leaf extracts on human cancer cells. Methodology: Antiproliferative and antioxidant effects on HT-29 human colon cancer cells were detected by MTS assay and a modified protocol of the alkaline Comet assay. In vitro antioxidant activities of different leaf extracts were evaluated through DPPH, \u3b2-carotene/linoleic acid and reducing power assays. Results: The leaf chloroform extract exhibited the higher cell growth inhibitory activity without induction of DNA damage; it showed to be able to significantly decrease DNA damage induced by H2O2 (100 M). This antioxidant activity seems to be comparable to that of vitamin C (1 mM). Ethyl acetate, acetone and methanol leaf extracts showed to be the most effective in reducing the stable free DPPH radical (IC50 =113 g/ml), in transforming the Fe3+ to Fe2+ (IC50 = 134 \ub5g/ml) and in inducing linoleic acid oxidation with an inhibition of 31.9 %. Conclusion: Our results confirm the antiproliferative potential of Citrullus colocynthis Schrad. on human cancer cells

    Bayesian inference with optimal maps

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    We present a new approach to Bayesian inference that entirely avoids Markov chain simulation, by constructing a map that pushes forward the prior measure to the posterior measure. Existence and uniqueness of a suitable measure-preserving map is established by formulating the problem in the context of optimal transport theory. We discuss various means of explicitly parameterizing the map and computing it efficiently through solution of an optimization problem, exploiting gradient information from the forward model when possible. The resulting algorithm overcomes many of the computational bottlenecks associated with Markov chain Monte Carlo. Advantages of a map-based representation of the posterior include analytical expressions for posterior moments and the ability to generate arbitrary numbers of independent posterior samples without additional likelihood evaluations or forward solves. The optimization approach also provides clear convergence criteria for posterior approximation and facilitates model selection through automatic evaluation of the marginal likelihood. We demonstrate the accuracy and efficiency of the approach on nonlinear inverse problems of varying dimension, involving the inference of parameters appearing in ordinary and partial differential equations.United States. Dept. of Energy. Office of Advanced Scientific Computing Research (Grant DE-SC0002517)United States. Dept. of Energy. Office of Advanced Scientific Computing Research (Grant DE-SC0003908

    Bayesian reconstruction of binary media with unresolved fine-scale spatial structures

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    We present a Bayesian technique to estimate the fine-scale properties of a binary medium from multiscale observations. The binary medium of interest consists of spatially varying proportions of low and high permeability material with an isotropic structure. Inclusions of one material within the other are far smaller than the domain sizes of interest, and thus are never explicitly resolved. We consider the problem of estimating the spatial distribution of the inclusion proportion, F(x), and a characteristic length-scale of the inclusions, δ, from sparse multiscale measurements. The observations consist of coarse-scale (of the order of the domain size) measurements of the effective permeability of the medium (i.e., static data) and tracer breakthrough times (i.e., dynamic data), which interrogate the fine scale, at a sparsely distributed set of locations. This ill-posed problem is regularized by specifying a Gaussian process model for the unknown field F(x) and expressing it as a superposition of Karhunen–Loève modes. The effect of the fine-scale structures on the coarse-scale effective permeability i.e., upscaling, is performed using a subgrid-model which includes δ as one of its parameters. A statistical inverse problem is posed to infer the weights of the Karhunen–Loève modes and δ, which is then solved using an adaptive Markov Chain Monte Carlo method. The solution yields non-parametric distributions for the objects of interest, thus providing most probable estimates and uncertainty bounds on latent structures at coarse and fine scales. The technique is tested using synthetic data. The individual contributions of the static and dynamic data to the inference are also analyzed.United States. Dept. of Energy. National Nuclear Security Administration (Contract DE-AC04_94AL85000

    14-Bromo-12-chloro-2,16-dioxapentacyclohenicosa-3(8),10,12,14-tetraene-7,20-dione

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    In the title compound, C19H16BrClO4, both the fused xanthene rings and one of the cyclohexane rings adopt envelope conformations, while the other cyclohexane ring is in a chair conformation. In the crystal, molecules are linked by C-H...O hydrogen bonds, forming infinite chains running along [10-1] incorporating R22(16) ring motifs. In addition, C-H...[pi] interactions and weak [pi]-[pi] stacking interactions [centroid-centroid distance = 3.768 (3) Å] help to consolidate the packing

    Discovery of 6.035GHz Hydroxyl Maser Flares in IRAS18566+0408

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    We report the discovery of 6.035GHz hydroxyl (OH) maser flares toward the massive star forming region IRAS18566+0408 (G37.55+0.20), which is the only region known to show periodic formaldehyde (4.8 GHz H2CO) and methanol (6.7 GHz CH3OH) maser flares. The observations were conducted between October 2008 and January 2010 with the 305m Arecibo Telescope in Puerto Rico. We detected two flare events, one in March 2009, and one in September to November 2009. The OH maser flares are not simultaneous with the H2CO flares, but may be correlated with CH3OH flares from a component at corresponding velocities. A possible correlated variability of OH and CH3OH masers in IRAS18566+0408 is consistent with a common excitation mechanism (IR pumping) as predicted by theory.Comment: Accepted for publication in the Astrophysical Journa
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