{C}^0$ penalty methods for the fully nonlinear Monge-Ampère equation

In this paper, we develop and analyze C(0) penalty methods for the fully nonlinear Monge-Ampere equation det(D(2)u) = f in two dimensions. The key idea in designing our methods is to build discretizations such that the resulting discrete linearizations are symmetric, stable, and consistent with the continuous linearization. We are then able to show the well-posedness of the penalty method as well as quasi-optimal error estimates using the Banach fixed-point theorem as our main tool. Numerical experiments are presented which support the theoretical results.

A Unified Approach to Encoding and Classification Using Bimodal Projection-Based Features

In general the objective of accurately encoding the input data and the objective of extracting good features to facilitate classification are not consistent with each other. As a result, good encoding methods may not be effective mechanisms for classification. In this paper, an earlier proposed unsupervised feature extraction mechanism for pattern classification has been extended to obtain an invertible map. The method of bimodal projection-based features was inspired by the general class of methods called projection pursuit. The principle of projection pursuit concentrates on projections that discriminate between clusters and not faithful representations. The basic feature map obtained by the method of bimodal projections has been extended to overcome this. The extended feature map is an embedding of the input space in the feature space. As a result, the inverse map exists and hence the representation of the input space in the feature space is exact. This map can be naturally expressed as a feedforward neural network.

A family of Runge-Kutta based explicit methods for rotational dynamics

The present paper develops a family of explicit algorithms for rotational dynamics and presents their comparison with several existing methods. For rotational motion the configuration space is a non-linear manifold, not a Euclidean vector space. As a consequence the rotation vector and its time derivatives correspond to different tangent spaces of rotation manifold at different time instants. This renders the usual integration algorithms for Euclidean space inapplicable for rotation. In the present algorithms this problem is circumvented by relating the equation of motion to a particular tangent space. It has been accomplished with the help of already existing relation between rotation increments which belongs to two different tangent spaces. The suggested method could in principle make any integration algorithm on Euclidean space, applicable to rotation. However, the present paper is restricted only within explicit Runge-Kutta enabled to handle rotation. The algorithms developed here are explicit and hence computationally cheaper than implicit methods. Moreover, they appear to have much higher local accuracy and hence accurate in predicting any constants of motion for reasonably longer time. The numerical results for solutions as well as constants of motion, indicate superior performance by most of our algorithms, when compared to some of the currently known algorithms, namely ALGO-C1, STW, LIEMID[EA], MCG, SUBCYC-M.

Multicomponent solids of lamotrigine with some selected coformers and their characterization by thermoanalytical, spectroscopic and X-ray diffraction methods

The present study investigates the structural and pharmaceutical properties of different multicomponent crystalline forms of lamotrigine (LTG) with some pharmaceutically acceptable coformers viz. nicotinamide (1), acetamide (2), acetic acid (3), 4-hydroxy-benzoic acid (4) and saccharin (5). The structurally homogeneous phases were characterized in the solid state by DSC/TGA, FT-IR and XRD (powder and single crystal structure analysis) as well as in the solution phase. Forms 1 and 2 were found to be cocrystal hydrate and cocrystal, respectively, while in forms 3, 4 and 5, proton transfer was observed from coformer to drug. The enthalpy of formation of multicomponent crystals from their components was determined from the enthalpy of solution of the cocrystals and the components separately. Higher exothermic values of the enthalpy of formation for molecular complexes 3, 4 and 5 suggest these to be more stable than 1 and 2. The solubility was measured in water as well as in phosphate buffers of varying pH. The salt solvate 3 exhibited the highest solubility of the drug in water as well as in buffers over the pH range 7-3 while the cocrystal hydrate 1 showed the maximum solubility in a buffer of pH 2. A significant lowering of the dosage profile of LTG was observed for 1, 3 and 5 in the animal activity studies on mice.

A comparison of three methods for downscaling daily precipitation in the Punjab region

Many downscaling techniques have been developed in the past few years for projection of station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs) to assess the hydrological impacts of climate change. This article compares the performances of three downscaling methods, viz. conditional random field (CRF), K-nearest neighbour (KNN) and support vector machine (SVM) methods in downscaling precipitation in the Punjab region of India, belonging to the monsoon regime. The CRF model is a recently developed method for downscaling hydrological variables in a probabilistic framework, while the SVM model is a popular machine learning tool useful in terms of its ability to generalize and capture nonlinear relationships between predictors and predictand. The KNN model is an analogue-type method that queries days similar to a given feature vector from the training data and classifies future days by random sampling from a weighted set of K closest training examples. The models are applied for downscaling monsoon (June to September) daily precipitation at six locations in Punjab. Model performances with respect to reproduction of various statistics such as dry and wet spell length distributions, daily rainfall distribution, and intersite correlations are examined. It is found that the CRF and KNN models perform slightly better than the SVM model in reproducing most daily rainfall statistics. These models are then used to project future precipitation at the six locations. Output from the Canadian global climate model (CGCM3) GCM for three scenarios, viz. A1B, A2, and B1 is used for projection of future precipitation. The projections show a change in probability density functions of daily rainfall amount and changes in the wet and dry spell distributions of daily precipitation. Copyright (C) 2011 John Wiley & Sons, Ltd.

Methods for Automatic Evaluation of Sentence Extract Summaries

This paper describes three novel techniques to automatically evaluate sentence extract summaries. Two of these techniques called FuSE and DeFuSE evaluate the quality of the generated extract summary based on the degree of similarity to the model summary. They use a fuzzy set theoretic basis to generate a match score. DeFuSE is an enhancement to FuSE and uses WordNet based hypernymy structures to detect similarity between sentences at abstracted levels. The third technique focuses on quantifying the quality of an extract summary based on the difficulty in generating such a summary. Advantages of these techniques are described with examples.

Multigrid algorithms for symmetric discontinuous Galerkin methods on graded meshes

We study a class of symmetric discontinuous Galerkin methods on graded meshes. Optimal order error estimates are derived in both the energy norm and the L 2 norm, and we establish the uniform convergence of V-cycle, F-cycle and W-cycle multigrid algorithms for the resulting discrete problems. Numerical results that confirm the theoretical results are also presented.

Inverse models to analyze the spatiotemporal variations of chemical weathering fluxes in a granito-gneissic watershed: Mule Hole, South India

Water-rock reactions are driven by the influx of water, which are out of equilibrium with the mineral assemblage in the rock. Here a mass balance approach is adopted to quantify these reactions. Based on field experiments carried out in a granito-gneissic small experimental watershed (SEW), Mule Hole SEW (similar to 4.5 km(2)), quartz, oligoclase, sericite, epidote and chlorite are identified as the basic primary minerals while kaolinite, goethite and smectite are identified as the secondary minerals. Observed groundwater chemistry is used to determine the weathering rates, in terms of `Mass Transfer Coefficients' (MTCs), of both primary and secondary minerals. Weathering rates for primary and secondary minerals are quantified in two steps. In the first step, top red soil is analyzed considering precipitation chemistry as initial phase and water chemistry of seepage flow as final phase. In the second step, minerals present in the saprolite layer are analyzed considering groundwater chemistry as the output phase. Weathering rates thus obtained are converted into weathering fluxes (Q(weathering)) using the recharge quantity. Spatial variability in the mineralogy observed among the thirteen wells of Mule Hole SEW is observed to be reflected in the MTC results and thus in the weathering fluxes. Weathering rates of the minerals in this silicate system varied from few 10 mu mol/L (in case of biotite) to 1000 s of micromoles per liter (calcite). Similarly, fluxes of biotite are observed to be least (7 +/- 5 mol/ha/yr) while those of calcite are highest (1265 791 mol/ha/yr). Further, the fluxes determined annually for all the minerals are observed to be within the bandwidth of the standard deviation of these fluxes. Variations in these annual fluxes are indicating the variations in the precipitation. Hence, the standard deviation indicated the temporal variations in the fluxes, which might be due to the variations in the annual rainfall. Thus, the methodology adopted defines an inverse way of determining weathering fluxes, which mainly contribute to the groundwater concentration. (C) 2011 Elsevier B.V. All rights reserved.