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.

Improved voice activity detection algorithm using wavelet and support vector machine

This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and support vector machine (SVM) for European Telecommunication Standards Institution (ETS1) adaptive multi-rate (AMR) narrow-band (NB) and wide-band (WB) speech codecs. First, based on the wavelet transform, the original IIR filter bank and pitch/tone detector are implemented, respectively, via the wavelet filter bank and the wavelet-based pitch/tone detection algorithm. The wavelet filter bank can divide input speech signal into several frequency bands so that the signal power level at each sub-band can be calculated. In addition, the background noise level can be estimated in each sub-band by using the wavelet de-noising method. The wavelet filter bank is also derived to detect correlated complex signals like music. Then the proposed algorithm can apply SVM to train an optimized non-linear VAD decision rule involving the sub-band power, noise level, pitch period, tone flag, and complex signals warning flag of input speech signals. By the use of the trained SVM, the proposed VAD algorithm can produce more accurate detection results. Various experimental results carried out from the Aurora speech database with different noise conditions show that the proposed algorithm gives considerable VAD performances superior to the AMR-NB VAD Options 1 and 2, and AMR-WB VAD. (C) 2009 Elsevier Ltd. All rights reserved.

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.

Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimization

Augmented Lagrangian methods for large-scale optimization usually require efficient algorithms for minimization with box constraints. On the other hand, active-set box-constraint methods employ unconstrained optimization algorithms for minimization inside the faces of the box. Several approaches may be employed for computing internal search directions in the large-scale case. In this paper a minimal-memory quasi-Newton approach with secant preconditioners is proposed, taking into account the structure of Augmented Lagrangians that come from the popular Powell-Hestenes-Rockafellar scheme. A combined algorithm, that uses the quasi-Newton formula or a truncated-Newton procedure, depending on the presence of active constraints in the penalty-Lagrangian function, is also suggested. Numerical experiments using the Cute collection are presented.

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.