A complex network approach to text summarization

Automatic summarization of texts is now crucial for several information retrieval tasks owing to the huge amount of information available in digital media, which has increased the demand for simple, language-independent extractive summarization strategies. In this paper, we employ concepts and metrics of complex networks to select sentences for an extractive summary. The graph or network representing one piece of text consists of nodes corresponding to sentences, while edges connect sentences that share common meaningful nouns. Because various metrics could be used, we developed a set of 14 summarizers, generically referred to as CN-Summ, employing network concepts such as node degree, length of shortest paths, d-rings and k-cores. An additional summarizer was created which selects the highest ranked sentences in the 14 systems, as in a voting system. When applied to a corpus of Brazilian Portuguese texts, some CN-Summ versions performed better than summarizers that do not employ deep linguistic knowledge, with results comparable to state-of-the-art summarizers based on expensive linguistic resources. The use of complex networks to represent texts appears therefore as suitable for automatic summarization, consistent with the belief that the metrics of such networks may capture important text features. (c) 2008 Elsevier Inc. All rights reserved.

An entropy-based approach to automatic image segmentation of satellite images

An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.

A pattern recognition approach to complex networks

Complex networks exist in many areas of science such as biology, neuroscience, engineering, and sociology. The growing development of this area has led to the introduction of several topological and dynamical measurements, which describe and quantify the structure of networks. Such characterization is essential not only for the modeling of real systems but also for the study of dynamic processes that may take place in them. However, it is not easy to use several measurements for the analysis of complex networks, due to the correlation between them and the difficulty of their visualization. To overcome these limitations, we propose an effective and comprehensive approach for the analysis of complex networks, which allows the visualization of several measurements in a few projections that contain the largest data variance and the classification of networks into three levels of detail, vertices, communities, and the global topology. We also demonstrate the efficiency and the universality of the proposed methods in a series of real-world networks in the three levels.

Estimating losses in an entanglement concentration scheme using the phenomenological operator approach to dissipation in cavity quantum electrodynamics

In a previous paper, we developed a phenomenological-operator technique aiming to simplify the estimate of losses due to dissipation in cavity quantum electrodynamics. In this paper, we apply that technique to estimate losses during an entanglement concentration process in the context of dissipative cavities. In addition, some results, previously used without proof to justify our phenomenological-operator approach, are now formally derived, including an equivalent way to formulate the Wigner-Weisskopf approximation.

A game theoretical approach to the evolution of structured communication codes

Structured meaning-signal mappings, i.e., mappings that preserve neighborhood relationships by associating similar signals with similar meanings, are advantageous in an environment where signals are corrupted by noise and sub-optimal meaning inferences are rewarded as well. The evolution of these mappings, however, cannot be explained within a traditional language evolutionary game scenario in which individuals meet randomly because the evolutionary dynamics is trapped in local maxima that do not reflect the structure of the meaning and signal spaces. Here we use a simple game theoretical model to show analytically that when individuals adopting the same communication code meet more frequently than individuals using different codes-a result of the spatial organization of the population-then advantageous linguistic innovations can spread and take over the population. In addition, we report results of simulations in which an individual can communicate only with its K nearest neighbors and show that the probability that the lineage of a mutant that uses a more efficient communication code becomes fixed decreases exponentially with increasing K. These findings support the mother tongue hypothesis that human language evolved as a communication system used among kin, especially between mothers and offspring.

A quasispecies approach to the evolution of sexual replication in unicellular organisms

This study develops a simplified model describing the evolutionary dynamics of a population composed of obligate sexually and asexually reproducing, unicellular organisms. The model assumes that the organisms have diploid genomes consisting of two chromosomes, and that the sexual organisms replicate by first dividing into haploid intermediates, which then combine with other haploids, followed by the normal mitotic division of the resulting diploid into two new daughter cells. We assume that the fitness landscape of the diploids is analogous to the single-fitness-peak approach often used in single-chromosome studies. That is, we assume a master chromosome that becomes defective with just one point mutation. The diploid fitness then depends on whether the genome has zero, one, or two copies of the master chromosome. We also assume that only pairs of haploids with a master chromosome are capable of combining so as to produce sexual diploid cells, and that this process is described by second-order kinetics. We find that, in a range of intermediate values of the replication fidelity, sexually reproducing cells can outcompete asexual ones, provided the initial abundance of sexual cells is above some threshold value. The range of values where sexual reproduction outcompetes asexual reproduction increases with decreasing replication rate and increasing population density. We critically evaluate a common approach, based on a group selection perspective, used to study the competition between populations and show its flaws in addressing the evolution of sex problem.

Fragment-guided approach to incorporating structural information into a CoMFA study: BACE-1 as an example

Alzheimer`s disease is an ultimately fatal neurodegenerative disease, and BACE-1 has become an attractive validated target for its therapy, with more than a hundred crystal structures deposited in the PDB. In the present study, we present a new methodology that integrates ligand-based methods with structural information derived from the receptor. 128 BACE-1 inhibitors recently disclosed by GlaxoSmithKline R&D were selected specifically because the crystal structures of 9 of these compounds complexed to BACE-1, as well as five closely related analogs, have been made available. A new fragment-guided approach was designed to incorporate this wealth of structural information into a CoMFA study, and the methodology was systematically compared to other popular approaches, such as docking, for generating a molecular alignment. The influence of the partial charges calculation method was also analyzed. Several consistent and predictive models are reported, including one with r (2) = 0.88, q (2) = 0.69 and r (pred) (2) = 0.72. The models obtained with the new methodology performed consistently better than those obtained by other methodologies, particularly in terms of external predictive power. The visual analyses of the contour maps in the context of the enzyme drew attention to a number of possible opportunities for the development of analogs with improved potency. These results suggest that 3D-QSAR studies may benefit from the additional structural information added by the presented methodology.

An information-theoretic approach to statistical dependence: Copula information

We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter quantified by the mutual information. We define the information excess as a measure of deviation from a maximum-entropy distribution. The idea of marginal invariant dependence measures is also discussed and used to show that empirical linear correlation underestimates the amplitude of the actual correlation in the case of non-Gaussian marginals. The mutual information is shown to provide an upper bound for the asymptotic empirical log-likelihood of a copula. An analytical expression for the information excess of T-copulas is provided, allowing for simple model identification within this family. We illustrate the framework in a financial data set. Copyright (C) EPLA, 2009

A robust Bayesian approach to null intercept measurement error model with application to dental data

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved.

A New Approach to the Prediction of Partition Coefficients in Water/Organic Interfaces

In the present work, a new approach for the determination of the partition coefficient in different interfaces based on the density function theory is proposed. Our results for log P(ow) considering a n-octanol/water interface for a large super cell for acetone -0.30 (-0.24) and methane 0.95 (0.78) are comparable with the experimental data given in parenthesis. We believe that these differences are mainly related to the absence of van der Walls interactions and the limited number of molecules considered in the super cell. The numerical deviations are smaller than that observed for interpolation based tools. As the proposed model is parameter free, it is not limited to the n-octanol/water interface.

A proposed EPR approach to evaluating agonist binding site of a peptide receptor

Angiotensin II (Ang II) and its transmembrane AT(1) receptor were selected in order to test an innovative strategy that might allow the assessment of the agonist binding site in the receptor molecule. With the use of the 2,2,6,6-tetramethylpiperidine-1-oxyl-4-amino-4-carboxylic acid (TOAC) paramagnetic probe, a biologically active agonist (TOAC(1)-Ang II), as well as an inactive control (TOAC(4)-Ang II) analogs were mixed in solution with various synthesized AT(1) fragments. Comparative intermolecular interactions, as estimated by analyzing the EPR spectra of solutions, suggested the existence of an agonist binding site containing a sequence composed of portions of the N-terminal (13-17) and the third extracellular loop (266-278) fragments of the AT(1) molecule. Therefore, this combined EPR-TOAC approach shows promise as an alternative for use also in other applications related to specific intermolecular association processes.

A new approach to organomanganese compounds: the tellurium/manganese exchange reaction

Diorganomanganese compounds react with aryl, vinyl, and alkynyl tellurides in a tellurium/manganese exchange reaction. The new mixed organomanganese reagents react selectively with electrophiles. (C) 2010 Published by Elsevier Ltd.

Stereoselective Nucleophilic Addition of Potassium Alkyltrifluoroborates to Cyclic N-Acyliminium Ions: a Simple and Mild Approach to Chiral 5-Alkyl-pyrrolidin-2-ones

The stereoselective nucleophilic addition of potassium alkyltrifluoroborates to cyclic N-acyliminium ions derived from N-benzyl-3,4,5-triacetoxy-pyrrolidin-2-one, which affords 5-substituted-pyrrolidin-2-ones, is described. The products are obtained in moderate to good yields and are produced predominantly as the anti diastereomer.

Arylbutyltellurides as precursors of dilithium arylthienylcyanocuprates in a straightforward approach to phenethylamine derivatives

The ring opening reaction of N-tosyl aziridines with dilithium arylthienylcyanocuprates generated from arylbutyltellurides produced phenethylamine derivatives in good to excellent yields. (C) 2007 Elsevier Ltd. All rights reserved.

Computer-Assisted Approach to Structural Elucidation of Lignans

This paper reports an expert system (SISTEMAT) developed for structural determination of diverse chemical classes of natural products, including lignans, based mainly on 13C NMR and 1H NMR data of these compounds. The system is composed of five programs that analyze specific data of a lignan and shows a skeleton probability for the compound. At the end of analyses, the results are grouped, the global probability is computed, and the most probable skeleton is exhibited to the user. SISTEMAT was able to properly predict the skeletons of 80% of the 30 lignans tested, demonstrating its advantage during the structural elucidation course in a short period of time.