Bribery in voting with CP-nets

We investigate the computational complexity of finding optimal bribery schemes in voting domains where the candidate set is the Cartesian product of a set of variables and voters use CP-nets, an expressive and compact way to represent preferences. To do this, we generalize the traditional bribery problem to take into account several issues over which agents vote, and their inter-dependencies. We consider five voting rules, three kinds of bribery actions, and five cost schemes. For most of the combinations of these parameters, we find that bribery in this setting is computationally easy.     

Active learning paradigms for CBIR systems based on optimum-path forest classification

This paper discusses methods for content-based image retrieval (CBIR) systems based on relevance feedback according to two active learning paradigms, named greedy and planned. In greedy methods, the system aims to return the most relevant images for a query at each iteration. In planned methods, the most informative images are returned during a few iterations and the most relevant ones are only presented afterward. In the past, we proposed a greedy approach based on optimum-path forest classification (OPF) and demonstrated its gain in effectiveness with respect to a planned method based on support-vector machines and another greedy approach based on multi-point query. In this work, we introduce a planned approach based on the OPF classifier and demonstrate its gain in effectiveness over all methods above using more image databases. In our tests, the most informative images are better obtained from images that are classified as relevant, which differs from the original definition. The results also indicate that both OPF-based methods require less user involvement (efficiency) to satisfy the user's expectation (effectiveness), and provide interactive response times.     

Synthesis, Molecular Characterization and Preliminary Antioxidant Activity Evaluation of Quercetin Fatty Esters

Quercetin shows interesting pharmacological effects, but its use in topical applications is limited by its low skin permeability and solubility. In this work, the synthesis of highly lipophilic quercetin esters with oleic, linoleic and linolenic acid useful as topical quercetin prodrugs is reported. Partial OH esterification is advisable to maintain the antioxidant activity of these compounds; tetraesters and triesters can be achieved by modulating the reaction conditions utilized for the total esterification of quercetin. The chemical structures of the esters were proven by spectroscopic techniques; quantum chemical NMR calculation were mandatory to unequivocally assign the free position in triesters. Finally, the antioxidant activity of all the synthesized compounds was determined by the 2,2-diphenyl-1-picryl-hydrazyl method and by 2,2-azinobis(3-ethyl-benzothiazoline-6-sulfonic acid) assay.     

Ultrasound image segmentation with shape priors: application to automatic cattle rib-eye area estimation.

Automatic ultrasound (US) image segmentation is a difficult task due to the quantity of noise present in the images and the lack of information in several zones produced by the acquisition conditions. In this paper, we propose a method that combines shape priors and image information to achieve this task. In particular, we introduce knowledge about the rib-eye shape using a set of images manually segmented by experts. A method is proposed for the automatic segmentation of new samples in which a closed curve is fitted taking into account both the US image information and the geodesic distance between the evolving curve and the estimated mean rib-eye shape in a shape space. This method can be used to solve similar problems that arise when dealing with US images in other fields. The method was successfully tested over a database composed of 610 US images, for which we have the manual segmentations of two experts.     

Design and In vitro Evaluation of Branched Peptide Conjugates: Turning Nonspecific Cytotoxic Drugs into Tumor‐Selective Agents

The use of peptide receptors as targets for tumor‐selective therapies was envisaged years ago with the findings that receptors for different endogenous regulatory peptides are overexpressed in several primary and metastatic human tumors, and can be used as tumor antigens. Branched peptides can retain or even increase, through multivalent binding, the biological activity of a peptide and are very resistant to proteolysis, thus having a markedly higher in vivo activity compared with the corresponding monomeric peptides. Oligo‐branched peptides, containing the human regulatory peptide neurotensin (NT) sequence, have been used as tumor‐specific targeting agents. These peptides are able to selectively and specifically deliver effector units, for cell imaging or killing, to tumor cells that overexpress NT receptors. Results obtained with branched NT conjugated to different functional units for tumor imaging and therapy indicate that branched peptides are promising novel multifunctional targeting molecules. This study is focused on the role of the releasing pattern of drug‐conjugated branched NT peptides. We present results obtained with oligo‐branched neurotensin peptides conjugated to 6‐mercaptopurin (6‐MP), combretastain A‐4 (CA4) and monastrol (MON). Drugs were conjugated to oligo‐branched neurotensin through different linkers, and the mode‐of‐release, together with cytotoxicity, was studied in different human cancer cell lines. The results show that branched peptides are very promising pharmacodelivery options. Among our drug‐armed branched peptides, NT4–CA4 was identified as a candidate for further development and evaluation in preclinical pharmacokinetic and pharmacodynamic studies. This peptide–drug exhibits significant activity against pancreas and prostate human cancer cells. Consequently, this derivative is of considerable interest due to the high mortality rates of pancreas neuroendocrine tumors and the high incidence of prostate cancer.     

Shifted FSAI preconditioners for the efficient parallel solution of non‐linear groundwater flow models

The present paper investigates the performance of a shifted factorized sparse approximate inverse as a parallel preconditioner for the iterative solution to the linear systems arising in the finite element discretization of non‐linear groundwater flow models. The shift strategy is based on an inexpensive preconditioner update exploiting the structure of the coefficient matrix. The proposed algorithm is experimented with in the parallel simulation of a large‐scale real multi‐aquifer system characterized by a stochastic distribution of the hydraulic conductivity. The numerical results show that the shifted factorized sparse approximate inverse algorithm may yield an overall computational gain up to 300% with respect to the non‐shifted scheme with an excellent parallel efficiency. Copyright © 2011 John Wiley & Sons, Ltd.     

Self-Consistent Approximation for Fluids and Lattice Gases

A self-consistent Ornstein–Zernike approximation (SCOZA) for the direct-correlation function, embodying consistency between the compressibility and the internal energy routes to the thermodynamics, has recently been quantitatively evaluated for a nearest-neighbor attractive lattice gas and for a fluid of Yukawa spheres, in which the pair potential has a hard core and an attractive Yukawa tail. For the lattice gas the SCOZA yields remarkably accurate predictions for the thermodynamics, the correlations, the critical point, and the coexistence curve. The critical temperature agrees to within 0.2% of the best estimates based on extrapolation of series expansions. Until the temperature is to within less than 1% of its critical value, the effective critical exponents do not differ appreciably from their estimated exact form, so that the thermodynamics deviates from the correct behavior only in a very narrow neighborhood of the critical point. For the Yukawa fluid accurate results are obtained as well, although a comparison as sharp as in the lattice-gas case has not been possible due to the greater uncertainty affecting the available simulation results, especially with regard to the position of the critical point and the coexistence curve.