A New Class of Highly Accurate Solvers for Ordinary Differential Equations

We introduce a new class of predictor-corrector schemes for the numerical solution of the Cauchy problem for non-stiff ordinary differential equations (ODEs), obtained via the decomposition of the solutions into combinations of appropriately chosen exponentials; historically, such techniques have been known as exponentially fitted methods. The proposed algorithms differ from the classical ones both in the selection of exponentials and in the design of the quadrature formulae used by the predictor-corrector process. The resulting schemes have the advantage of significantly faster convergence, given fixed lengths of predictor and corrector vectors. The performance of the approach is illustrated via a number of numerical examples. This work was partially supported by the US Department of Defense under ONR Grant #N00014-07-1-0711 and AFOSR Grants #FA9550-06-1-0197 and #FA9550-06-1-0239.     

PHANTOM: A Monte Carlo event generator for six parton final states at high energy colliders

PHANTOM is a tree level Monte Carlo for six parton final states at proton-proton, proton-antiproton and electron-positron colliders at and including possible interferences between the two sets of diagrams. This comprehends all purely electroweak contributions as well as all contributions with one virtual or two external gluons. It can generate unweighted events for any set of processes and it is interfaced to parton shower and hadronization packages via the latest Les Houches Accord protocol. It can be used to analyze the physics of boson-boson scattering, Higgs boson production in boson-boson fusion, and three boson production.

Program summary

Program title:PHANTOM (V. 1.0)Catalogue identifier: AECE_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AECE_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 175 787No. of bytes in distributed program, including test data, etc.: 965 898Distribution format: tar.gzProgramming language: Fortran 77Computer: Any with a UNIX, LINUX compatible Fortran compilerOperating system: UNIX, LINUXRAM: 500 MBClassification: 11.1External routines: LHAPDF (Les Houches Accord PDF Interface, http://projects.hepforge.org/lhapdf/), CIRCE (beamstrahlung for e⁺e⁻ ILC collider).Nature of problem: Six fermion final state processes have become important with the increase of collider energies and are essential for the study of top, Higgs and electroweak symmetry breaking physics at high energy colliders. Since thousands of Feynman diagrams contribute in a single process and events corresponding to hundreds of different final states need to be generated, a fast and stable calculation is needed.Solution method:PHANTOM is a tree level Monte Carlo for six parton final states at proton-proton, proton-antiproton and electron-positron colliders. It computes all amplitudes at and including possible interferences between the two sets of diagrams. The matrix elements are computed with the helicity formalism implemented in the program PHACT [1]. The integration makes use of an iterative-adaptive multichannel method which, relying on adaptivity, allows the use of only a few channels per process. Unweighted event generation can be performed for any set of processes and it is interfaced to parton shower and hadronization packages via the latest Les Houches Accord protocol.Restrictions: All Feynman diagrams are computed al LO.Unusual features: Phantom is written in Fortran 77 but it makes use of structures. The g77 compiler cannot compile it as it does not recognize the structures. The Intel, Portland Group, True64 HP Fortran 77 or Fortran 90 compilers have been tested and can be used.Running time: A few hours for a cross section integration of one process at per mille accuracy. One hour for one thousand unweighted events.References:

[1]

A. Ballestrero, E. Maina, Phys. Lett. B 350 (1995) 225, hep-ph/9403244; A. Ballestrero, PHACT 1.0, Program for helicity amplitudes Calculations with Tau matrices, hep-ph/9911318, in: B.B. Levchenko, V.I. Savrin (Eds.), Proceedings of the 14th International Workshop on High Energy Physics and Quantum Field Theory (QFTHEP 99), SINP MSU, Moscow, p. 303.

     

Dynamic workload balancing of parallel applications with user-level scheduling on the Grid

This paper suggests a hybrid resource management approach for efficient parallel distributed computing on the Grid. It operates on both application and system levels, combining user-level job scheduling with dynamic workload balancing algorithm that automatically adapts a parallel application to the heterogeneous resources, based on the actual resource parameters and estimated requirements of the application. The hybrid environment and the algorithm for automated load balancing are described, the influence of resource heterogeneity level is measured, and the speedup achieved with this technique is demonstrated for different types of applications and resources.     

Non‐iterative Second‐order Approximation of Signed Distance Functions for Any Isosurface Representation

Signed distance functions (SDF) to explicit or implicit surface representations are intensively used in various computer graphics and visualization algorithms. Among others, they are applied to optimize collision detection, are used to reconstruct data fields or surfaces, and, in particular, are an obligatory ingredient for most level set methods. Level set methods are common in scientific visualization to extract surfaces from scalar or vector fields. Usual approaches for the construction of an SDF to a surface are either based on iterative solutions of a special partial differential equation or on marching algorithms involving a polygonization of the surface. We propose a novel method for a non‐iterative approximation of an SDF and its derivatives in a vicinity of a manifold. We use a second‐order algebraic fitting scheme to ensure high accuracy of the approximation. The manifold is defined (explicitly or implicitly) as an isosurface of a given volumetric scalar field. The field may be given at a set of irregular and unstructured samples. Stability and reliability of the SDF generation is achieved by a proper scaling of weights for the Moving Least Squares approximation, accurate choice of neighbors, and appropriate handling of degenerate cases. We obtain the solution in an explicit form, such that no iterative solving is necessary, which makes our approach fast.     

EXPLORATION OF MASSIVE CRIME DATA SETS THROUGH DATA MINING TECHNIQUES

We incorporate two data mining techniques, clustering and association-rule mining, into a fruitful exploratory tool for the discovery of spatio-temporal patterns in data-rich environments. This tool is an autonomous pattern detector that efficiently and effectively reveals plausible cause–effect associations among many geographical layers. We present two methods for exploratory analysis and detail algorithms to explore massive databases. We illustrate the algorithms with real crime data sets.     

O films with adjustable tilt of optical axis for LCD compensation

Abstract— A method of preparation of positive O films with the tilt angle of the optic axis continuously controlled in the range 0–90° is proposed. It is based on the use of reactive mesogens and alignment materials that provide a wide range of pretilt angles. The method developed allows for further improvement in the viewing‐angle characteristics of LCDs with O compensation films.     

Design of peptidomimetic inhibitors of aspartic protease of HIV-1 containing -Phe Psi Pro- core and displaying favourable ADME-related properties

Aspartic protease (PR) of HIV-1 virus represents a valid therapeutic target for the design of antiviral agents suitable for treatment of AIDS. We have designed peptidomimetic PR inhibitors containing a novel dihydroxyethylenediamine -Phe-Psi[CHOH-CHOH]-Pro- core using molecular modelling approach that predicts the inhibitory potencies (IC(50)(pre)) in terms of computed relative enzyme-inhibitor complexation Gibbs free energies (Delta Delta G(comp)). The modelling approach considers not only the enzyme-inhibitor interactions, but includes also the solvent and entropic effects affecting the enzyme inhibition. The objectives of this study were to optimize the number and type of flanking residues that occupy the S(3), S(2) and S(2'), S(3') positions in the PR binding pocket and to select potent lead candidates, which display also favourable ADME-related properties. The structure-based design was combined with a synthetic strategy used to prepare a training set of 10 analogues sharing the -Phe Psi Pro- core. This strategy couples stereochemical control with full flexibility in the choice of the flanking residues and in vitro activity assays. A QSAR model correlating calculated Delta Delta G(comp) with the measured IC(50)(exp) values for the training set was prepared and confirmed that our computational approach can serve for reliable prediction of PR inhibitory potencies of peptidomimetics. The appropriate choice of the flanking residues allowed us to design virtual lead compounds, such as FP14, FP23 and FP76, with reduced molecular weight, predicted inhibitory potencies in the picomolar range, promising ADME profiles and a potential to escape drug resistance due to favourable interactions with the PR backbone.     

Robot-assisted shopping for the blind: issues in spatial cognition and product selection

Research on spatial cognition and blind navigation suggests that a device aimed at helping blind people to shop independently should provide the shopper with effective interfaces to the locomotor and haptic spaces of the supermarket. In this article, we argue that robots can act as effective interfaces to haptic and locomotor spaces in modern supermarkets. We also present the design and evaluation of three product selection modalities—browsing, typing and speech, which allow the blind shopper to select the desired product from a repository of thousands of products.     

Minimizing nonsubmodular functions with graph cuts - a review

Optimization techniques based on graph cuts have become a standard tool for many vision applications. These techniques allow to minimize efficiently certain energy functions corresponding to pairwise Markov random fields (MRFs). Currently, there is an accepted view within the computer vision community that graph cuts can only be used for optimizing a limited class of MRF energies (e.g., submodular functions). In this survey, we review some results that show that graph cuts can be applied to a much larger class of energy functions (in particular, nonsubmodular functions). While these results are well-known in the optimization community, to our knowledge they were not used in the context of computer vision and MRF optimization. We demonstrate the relevance of these results to vision on the problem of binary texture restoration.