X-ray spectrometry: a powerful tool for the measurement of complete fusion of weakly bound nuclei

We describe how the method of detection of delayed K x-rays produced by the electron capture decay of the residual nuclei can be a powerful tool in the investigation of the effect of the breakup process on the complete fusion (CF) cross-section of weakly bound nuclei at energies close to the Coulomb barrier. This is presently one of the most interesting subjects under investigation in the field of low-energy nuclear reactions, and the difficult experimental task of separating CF from the incomplete fusion (ICF) of one of the breakup fragments can be achieved by the x-ray spectrometry method. We present results for the fusion of the (9)Be + (144)Sm system. Copyright (c) 2008 John Wiley & Sons, Ltd.

Total reaction cross-sections for light weakly bound systems

We have measured the elastic scattering cross-section for (8)Li + (9)Be and (8)Li + (51)V systems at 19.6 MeV and 18.5 MeV, respectively. We have also extracted total reaction cross sections from the elastic scattering analysis for several light weakly bound systems using the optical model with Woods-Saxon and double-folding-type potentials. Different reduction methods for the total reaction cross-sections have been applied to analyze and compare simultaneously all the systems.

Two-dimensional electron states bound to an off-plane donor in a magnetic field

The states of an electron confined in a two-dimensional (2D) plane and bound to an off-plane donor impurity center, in the presence of a magnetic field, are investigated. The energy levels of the ground state and the first three excited states are calculated variationally. The binding energy and the mean orbital radius of these states are obtained as a function of the donor center position and the magnetic field strength. The limiting cases are discussed for an in-plane donor impurity (i.e. a 2D hydrogen atom) as well as for the donor center far away from the 2D plane in strong magnetic fields, which corresponds to a 2D harmonic oscillator.

On the lower bound on the exchange-correlation energy in two dimensions

We study the properties of the lower bound on the exchange-correlation energy in two dimensions. First we review the derivation of the bound and show how it can be written in a simple density-functional form. This form allows an explicit determination of the prefactor of the bound and testing its tightness. Next we focus on finite two-dimensional systems and examine how their distance from the bound depends on the system geometry. The results for the high-density limit suggest that a finite system that comes as close as possible to the ultimate bound on the exchange-correlation energy has circular geometry and a weak confining potential with a negative curvature. (c) 2009 Elsevier B.V. All rights reserved.

Tightened Lieb-Oxford Bound for Systems of Fixed Particle Number

The Lieb-Oxford bound is a constraint upon approximate exchange-correlation functionals. We explore a nonempirical tightening of that bound in both universal and electron number-dependent form. The test functional is PBE. Regarding both atomization energies (slightly worsened) and bond lengths (slightly improved), we find the PBE functional to be remarkably insensitive to the value of the Lieb-Oxford bound. This both rationalizes the use of the original Lieb-Oxford constant in PBE and suggests that enhancement factors more sensitive to sharpened constraints await discovery.

Empirical analysis of the Lieb-Oxford bound in ions and molecules

Universal properties of the Coulomb interaction energy apply to all many-electron systems. Bounds on the exchange-correlation energy, in particular, are important for the construction of improved density functionals. Here we investigate one such universal property-the Lieb-Oxford lower bound-for ionic and molecular systems. In recent work [J Chem Phys 127, 054106 (2007)], we observed that for atoms and electron liquids this bound may be substantially tightened. Calculations for a few ions and molecules suggested the same tendency, but were not conclusive due to the small number of systems considered. Here we extend that analysis to many different families of ions and molecules, and find that for these, too, the bound can be empirically tightened by a similar margin as for atoms and electron liquids. Tightening the Lieb-Oxford bound will have consequences for the performance of various approximate exchange-correlation functionals. (C) 2008 Wiley Periodicals Inc.

Crystal structure of a soluble decoy receptor IL-22BP bound to interleukin-22

Interleukin-22 (IL-22) plays an important role in the regulation of immune and inflammatory responses in mammals. The IL-22 binding protein (IL-22BP), a soluble receptor that specifically binds IL-22, prevents the IL-22/interleukin-22 receptor 1 (IL-22R1)/interleukin-10 receptor 2 (IL-10R2) complex assembly and blocks IL-22 biological activity. Here we present the crystal structure of the IL-22/IL-22BP complex at 2.75 angstrom resolution. The structure reveals IL-22BP residues critical for IL-22 binding, which were confirmed by site-directed mutagenesis and functional studies. Comparison of IL-22/IL-22BP and IL-22/IL-22R1 crystal structures shows that both receptors display an overlapping IL-22 binding surface, which is consistent with the inhibitory role played by IL-22 binding protein.

Continuous GRASP with a local active-set method for bound-constrained global optimization

Global optimization seeks a minimum or maximum of a multimodal function over a discrete or continuous domain. In this paper, we propose a hybrid heuristic-based on the CGRASP and GENCAN methods-for finding approximate solutions for continuous global optimization problems subject to box constraints. Experimental results illustrate the relative effectiveness of CGRASP-GENCAN on a set of benchmark multimodal test functions.

U-curve: A branch-and-bound optimization algorithm for U-shaped cost functions on Boolean lattices applied to the feature selection problem

This paper presents the formulation of a combinatorial optimization problem with the following characteristics: (i) the search space is the power set of a finite set structured as a Boolean lattice; (ii) the cost function forms a U-shaped curve when applied to any lattice chain. This formulation applies for feature selection in the context of pattern recognition. The known approaches for this problem are branch-and-bound algorithms and heuristics that explore partially the search space. Branch-and-bound algorithms are equivalent to the full search, while heuristics are not. This paper presents a branch-and-bound algorithm that differs from the others known by exploring the lattice structure and the U-shaped chain curves of the search space. The main contribution of this paper is the architecture of this algorithm that is based on the representation and exploration of the search space by new lattice properties proven here. Several experiments, with well known public data, indicate the superiority of the proposed method to the sequential floating forward selection (SFFS), which is a popular heuristic that gives good results in very short computational time. In all experiments, the proposed method got better or equal results in similar or even smaller computational time. (C) 2009 Elsevier Ltd. All rights reserved.

The bound quiver of a split extension

In this paper, we give a sufficient (which is also necessary under a compatibility hypothesis) condition on a set of arrows in the quiver of an algebra A so that A is a split extension of A/M, where M is the ideal of A generated by the classes of these arrows. We also compare the notion of split extension with that of semiconvex extension of algebras.

Purification and partial characterization of a midgut membrane-bound alpha-glucosidase from Quesada gigas (Hemiptera: Cicadidae)

Adults of Quesada gigas (Hemiptera: Cicadidae) have a major alpha-glucosidase bound to the perimicrovillar membranes, which are lipoprotein membranes that surround the midgut cell microvilli in Hemiptera and Thysanoptera. Determination of the spatial distribution of alpha-glucosidases in Q. gigas midgut showed that this activity is not equally distributed between soluble and membrane-bound isoforms. The major membrane-bound enzyme was solubilized in the detergent Triton X-100 and purified to homogeneity by means of gel filtration on Sephacryl S-100, and ion-exchange on High Q and Mono Q columns. The purified alpha-glucosidase is a protein with a pH optimum of 6.0 against the synthetic substrate p-nitrophenyl alpha-D-glucoside and M(r) of 61,000 (SDS-PAGE). Taking into account V(Max)/K(M) ratios, the enzyme is more active on maltose than sucrose and prefers oligomaltodextrins up to maltopentaose, with lower efficiency for longer chain maltodextrins. The Q gigas alpha-glucosidase was immunolocalized in perimicrovillar membranes by using a monospecific polyclonal antibody raised against the purified enzyme from Dysdercus peruvianus. The role of this enzyme in xylem fluid digestion and its possible involvement in osmoregulation is discussed. (C) 2009 Elsevier Inc. All rights reserved.

Branch and Bound Algorithm for Multiprocessor Scheduling

The multiprocessor task graph scheduling problem has been extensively studied asacademic optimization problem which occurs in optimizing the execution time of parallelalgorithm with parallel computer. The problem is already being known as one of the NPhardproblems. There are many good approaches made with many optimizing algorithmto find out the optimum solution for this problem with less computational time. One ofthem is branch and bound algorithm.In this paper, we propose a branch and bound algorithm for the multiprocessor schedulingproblem. We investigate the algorithm by comparing two different lower bounds withtheir computational costs and the size of the pruned tree.Several experiments are made with small set of problems and results are compared indifferent sections.

Statistical bound of genetic solutions to quadratic assignment problems

Quadratic assignment problems (QAPs) are commonly solved by heuristic methods, where the optimum is sought iteratively. Heuristics are known to provide good solutions but the quality of the solutions, i.e., the confidence interval of the solution is unknown. This paper uses statistical optimum estimation techniques (SOETs) to assess the quality of Genetic algorithm solutions for QAPs. We examine the functioning of different SOETs regarding biasness, coverage rate and length of interval, and then we compare the SOET lower bound with deterministic ones. The commonly used deterministic bounds are confined to only a few algorithms. We show that, the Jackknife estimators have better performance than Weibull estimators, and when the number of heuristic solutions is as large as 100, higher order JK-estimators perform better than lower order ones. Compared with the deterministic bounds, the SOET lower bound performs significantly better than most deterministic lower bounds and is comparable with the best deterministic ones.