Aggregational behavior in water,of some polyamphiphiles derived from reactive polymers

Selected polyamphiphiles were prepared by the method of reactive polymers, i.e., interaction of polymaleic anhydride and polyacryloyl chloride with certain long chain alcohols. The aggregational behavior of these polyamphiphiles in water was studied by video-enhanced differential interference contrast microscopy, as well as by absorption and fluorescence spectroscopy. The formation of large aggregates was observed by video technique, while inter- and intramolecular micelles were detected by spectroscopic © 1993 John Wiley & Sons, Inc.     

Pomerons and BCFW recursion relations for strings on D-branes

We derive pomeron vertex operators for bosonic strings and superstrings in the presence of D-branes. We demonstrate how they can be used in order to compute the Regge behavior of string amplitudes on D-branes and the amplitude of ultrarelativistic D-brane scattering. After a lightning review of the BCFW method, we proceed in a classification of the various BCFW shifts possible in a field/string theory in the presence of defects/D-branes. The BCFW shifts present several novel features, such as the possibility of performing single particle momentum shifts, due to the breaking of momentum conservation in the directions normal to the defect. Using the pomeron vertices we show that superstring amplitudes on the disc involving both open and closed strings should obey BCFW recursion relations. As a particular example, we analyze explicitly the case of 1→1$1\to 1$ scattering of level one closed string states off a D-brane. Finally, we investigate whether the eikonal Regge regime conjecture holds in the presence of D-branes.     

Primal and dual linear decision rules in stochastic and robust optimization

Linear stochastic programming provides a flexible toolbox for analyzing real-life decision situations, but it can become computationally cumbersome when recourse decisions are involved. The latter are usually modeled as decision rules, i.e., functions of the uncertain problem data. It has recently been argued that stochastic programs can quite generally be made tractable by restricting the space of decision rules to those that exhibit a linear data dependence. In this paper, we propose an efficient method to estimate the approximation error introduced by this rather drastic means of complexity reduction: we apply the linear decision rule restriction not only to the primal but also to a dual version of the stochastic program. By employing techniques that are commonly used in modern robust optimization, we show that both arising approximate problems are equivalent to tractable linear or semidefinite programs of moderate sizes. The gap between their optimal values estimates the loss of optimality incurred by the linear decision rule approximation. Our method remains applicable if the stochastic program has random recourse and multiple decision stages. It also extends to cases involving ambiguous probability distributions.     

Geometry + Simulation Modules: Implementing Isogeometric Analysis

Isogeometric analysis (IGA) is a recently developed simulation method that allows integration of finite element analysis (FEA) with conventional computer-aided design (CAD) software [1,3]. This goal requires new software design strategies, in order to enable the use of CAD data in the analysis pipeline. To this end, we have initiated G + SMO (Geometry+Simulation Modules), an open-source, C++ library for IGA. G + SMO is an object-oriented, template library, that implements a generic concept for IGA, based on abstract classes for discretization basis, geometry map, assembler, solver and so on. It makes use of object polymorphism and inheritance techniques to provide a common framework for IGA, for a variety of different basis-types which are available. A highlight of our design is the dimension independent code, realized by means of template meta-programming. Some of the features already available include computing with B-spline, Bernstein, NURBS bases, as well as hierarchical and truncated hierarchical bases of arbitrary polynomial order. These basis functions are used in continuous and discontinuous Galerkin approximation of PDEs over (non-)conforming multi-patch computational (physical) domains. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A smoothing algorithm for finite min–max–min problems

We generalize a smoothing algorithm for finite min–max to finite min–max–min problems. We apply a smoothing technique twice, once to eliminate the inner min operator and once to eliminate the max operator. In mini–max problems, where only the max operator is eliminated, the approximation function is decreasing with respect to the smoothing parameter. Such a property is convenient to establish algorithm convergence, but it does not hold when both operators are eliminated. To maintain the desired property, an additional term is added to the approximation. We establish convergence of a steepest descent algorithm and provide a numerical example.     

Mössbauer study of hyperfine structure of (bis-diethyldithiocarbamato)FeIIIBr

The parameters of nuclear hyperfine splittings for the paramagnet Fe(dtc)₂Br have been determined by Mössbauer measurements on a mixed system of this compound with the homologous ferromagnetic chloro derivative acting as host. The crystal field z axis is found to be perpendicular to the exchange field for Fe(dtc)₂Br, in contrast to the host.