Discriminating Different Classes of Biological Networks by Analyzing the Graphs Spectra Distribution

The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e. g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.

Analyzing the Complexity and Reliability of Switch-Frequency-Reconfigurable Antennas Using Graph Models

This paper addresses the functional reliability and the complexity of reconfigurable antennas using graph models. The correlation between complexity and reliability for any given reconfigurable antenna is defined. Two methods are proposed to reduce failures and improve the reliability of reconfigurable antennas. The failures are caused by the reconfiguration technique or by the surrounding environment. These failure reduction methods proposed are tested and examples are given which verify these methods.

Connections between the Sznajd model with general confidence rules and graph theory

The Sznajd model is a sociophysics model that is used to model opinion propagation and consensus formation in societies. Its main feature is that its rules favor bigger groups of agreeing people. In a previous work, we generalized the bounded confidence rule in order to model biases and prejudices in discrete opinion models. In that work, we applied this modification to the Sznajd model and presented some preliminary results. The present work extends what we did in that paper. We present results linking many of the properties of the mean-field fixed points, with only a few qualitative aspects of the confidence rule (the biases and prejudices modeled), finding an interesting connection with graph theory problems. More precisely, we link the existence of fixed points with the notion of strongly connected graphs and the stability of fixed points with the problem of finding the maximal independent sets of a graph. We state these results and present comparisons between the mean field and simulations in Barabasi-Albert networks, followed by the main mathematical ideas and appendices with the rigorous proofs of our claims and some graph theory concepts, together with examples. We also show that there is no qualitative difference in the mean-field results if we require that a group of size q > 2, instead of a pair, of agreeing agents be formed before they attempt to convince other sites (for the mean field, this would coincide with the q-voter model).

Temperature Effect on the Two-Photon Absorption Spectrum of All-trans-beta-carotene

In this report, we investigate the influence of temperature on the two-photon absorption (2PA) spectrum of all-trans-beta-carotene using the femtosecond white-light-continuum Z-scan technique. We observed that the 2PA cross-section decreases quadratically with the temperature. Such effect was modeled using a three-energy-level diagram within the sum-over-essential states approach, assuming temperature dependencies to the transition dipole moment and refractive index of the solvent. The results show that the transition dipole moments from ground to excited state and between the excited states, which governed the two-photon matrix element, have distinct behaviors with the temperature. The first one presents a quadratic dependence, while the second exhibits a linear dependence. Such effects were attributed mainly to the trans -> cis thermal interconversion process, which decreases the effective conjugation length, contributing to diminishing the transition dipole moments and, consequently, the 2PA cross-section.

Analytic perturbation theory for bound states in the transfer matrix spectrum of weakly correlated lattice ferromagnetic spin systems

We consider general d-dimensional lattice ferromagnetic spin systems with nearest neighbor interactions in the high temperature region ('beta' << 1). Each model is characterized by a single site apriori spin distribution taken to be even. We also take the parameter 'alfa' = ('S POT.4') - 3 '(S POT.2') POT.2' > 0, i.e. in the region which we call Gaussian subjugation, where ('S POT.K') denotes the kth moment of the apriori distribution. Associated with the model is a lattice quantum field theory known to contain a particle of asymptotic mass -ln 'beta' and a bound state below the two-particle threshold. We develop a 'beta' analytic perturbation theory for the binding energy of this bound state. As a key ingredient in obtaining our result we show that the Fourier transform of the two-point function is a meromorphic function, with a simple pole, in a suitable complex spectral parameter and the coefficients of its Laurent expansion are analytic in 'beta'.

Complete Sequence of Broad-Host-Range Plasmid pRIO-5 Harboring the Extended-Spectrum-beta-Lactamase Gene bla(BES-1)

Broad-host-range plasmid pRIO-5, harboring the extended-spectrum beta-lactamase bla(BES-1) gene in Serratia marcescens, was fully sequenced. Analysis of the 12,957-bp sequence of this IncP6-type plasmid revealed that the bla(BES-1) gene was associated with two copies of the insertion sequence IS26. The promoter responsible for the bla(BES-1) expression was hybrid, made of a - 35 box located inside the inverted repeat of IS26 and a - 10 box inside a remnant of an insertion sequence.

Fractal descriptors based on Fourier spectrum applied to texture analysis

This work proposes the development and study of a novel technique lot the generation of fractal descriptors used in texture analysis. The novel descriptors are obtained from a multiscale transform applied to the Fourier technique of fractal dimension calculus. The power spectrum of the Fourier transform of the image is plotted against the frequency in a log-log scale and a multiscale transform is applied to this curve. The obtained values are taken as the fractal descriptors of the image. The validation of the proposal is performed by the use of the descriptors for the classification of a dataset of texture images whose real classes are previously known. The classification precision is compared to other fractal descriptors known in the literature. The results confirm the efficiency of the proposed method. (C) 2012 Elsevier B.V. All rights reserved.

Riemannian Submersions with Discrete Spectrum

We prove some estimates on the spectrum of the Laplacian of the total space of a Riemannian submersion in terms of the spectrum of the Laplacian of the base and the geometry of the fibers. When the fibers of the submersions are compact and minimal, we prove that the spectrum of the Laplacian of the total space is discrete if and only if the spectrum of the Laplacian of the base is discrete. When the fibers are not minimal, we prove a discreteness criterion for the total space in terms of the relative growth of the mean curvature of the fibers and the mean curvature of the geodesic spheres in the base. We discuss in particular the case of warped products.

Compton scattering spectrum as a source of information of normal and neoplastic breast tissues' composition

In this work we measured X-ray scatter spectra from normal and neoplastic breast tissues using photon energy of 17.44 key and a scattering angle of 90 degrees, in order to study the shape (FWHM) of the Compton peaks. The obtained results for FWHM were discussed in terms of composition and histological characteristics of each tissue type. The statistical analysis shows that the distribution of FWHM of normal adipose breast tissue clearly differs from all other investigated tissues. Comparison between experimental values of FWHM and effective atomic number revealed a strong correlation between them, showing that the FWHM values can be used to provide information about elemental composition of the tissues. (C) 2012 Elsevier Ltd. All rights reserved.

IDENTIFICATION OF ETHANOLIC WOOD EXTRACTS USING ELECTRONIC ABSORPTION SPECTRUM AND MULTIVARIATE ANALYSIS

IDENTIFICATION OF ETHANOLIC WOOD EXTRACTS USING ELECTRONIC ABSORPTION SPECTRUM AND MULTIVARIATE ANALYSIS. The application of multivariate analysis to spectrophotometric (UV) data was explored for distinguishing extracts of cachaca woods commonly used in the manufacture of casks for aging cachacas (oak, cabretiva-parda, jatoba, amendoim and canela-sassafras). Absorbances close to 280 nm were more strongly correlated with oak and jatoba woods, whereas absorbances near 230 nm were more correlated with canela-sassafras and cabretiva-parda. A comparison between the spectrophotometric model and the model based on chromatographic (HPLC-DAD) data was carried out. The spectrophotometric model better explained the variance data (PC1 + PC2 = 91%) exhibiting potential as a routine method for checking aged spirits.

Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.

Effect of Solvent-Induced Coil to Helix Conformational Change on the Two-Photon Absorption Spectrum of Poly(3,6-phenanthrene)

This paper investigates the effect of solvent-induced conformational changes of poly(3,6-phenanthrene) on their two-photon absorption (2PA). Such effect was studied employing the wavelength-tunable femtosecond Z-scan technique and modeled using the sum-over-essential states approach. We observed a strong reduction of the 2PA cross-section when the sample was prepared in hexane (poor solvent) in comparison to chloroform (good solvent), which is related to the conformation adopted by the polymer in each case. In chloroform it adopts a random coil conformation, as opposed to the one-handed helix conformation in hexane. Our results pointed out that the coil to helix conformation change decreases the degree of molecular planarity of the polymer pi-conjugated backbone, which is primarily responsible for their optical nonlinearity, contributing to diminishing the effective transition dipole moments and, consequently, the 2PA cross-section. Moreover, by studying the nonlinear response with different light polarization, we showed that, although the solvent-induced conformational change does not alter the molecular symmetry of the polymer, it modifies considerably the direction of the transition dipole moments between the excited states.

Analog of the susceptibility spectrum for levitation forces between a superconductor and a permanent magnet

We report on the measurements of both vertical and lateral levitation forces between a permanent magnet NdFeB and a polycrystalline YBa4Cu6O7-delta superconductor. The analysis of the obtained results revealed an interesting correlation between the behavior of the forces in the field-cooled and zero-field-cooled regimes, resembling the structure of the so-called susceptibility spectrum chi ''(chi'). Such force-force diagrams can be useful for identifying flux distribution structure inside a superconducting material. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4743006]

Algebraic-graph method for identification of islanding in power system grids

In this paper, a new algebraic-graph method for identification of islanding in power system grids is proposed. The proposed method identifies all the possible cases of islanding, due to the loss of a equipment, by means of a factorization of the bus-branch incidence matrix. The main features of this new method include: (i) simple implementation, (ii) high speed, (iii) real-time adaptability, (iv) identification of all islanding cases and (v) identification of the buses that compose each island in case of island formation. The method was successfully tested on large-scale systems such as the reduced south Brazilian system (45 buses/72 branches) and the south-southeast Brazilian system (810 buses/1340 branches). (C) 2011 Elsevier Ltd. All rights reserved.

Spectrum of cognitive impairment in neurocysticercosis Differences according to disease phase

Objectives: Cognitive decline related to neurocysticercosis (NC) remains poorly characterized and underdiagnosed. In a cross-sectional study with a prospective phase, we evaluated cognitive decline in patients with strictly calcified form (C-NC), the epidemiologically largest subgroup of NC, and investigated whether there is a spectrum of cognitive abnormalities in the disease. Methods: Forty treatment-naive patients with C-NC aged 37.6 +/- 11.3 years and fulfilling criteria for definitive C-NC were submitted to a comprehensive cognitive and functional evaluation and were compared with 40 patients with active NC (A-NC) and 40 healthy controls (HC) matched for age and education. Patients with dementia were reassessed after 24 months. Results: Patients with C-NC presented 9.4 +/- 3.1 altered test scores out of the 30 from the cognitive battery when compared to HC. No patient with C-NC had dementia and 10 patients (25%) presented cognitive impairment-no dementia (CIND). The A-NC group had 5 patients (12.5%) with dementia and 11 patients (27.5%) with CIND. On follow-up, 3 out of 5 patients with A-NC with dementia previously still presented cystic lesions with scolex on MRI and still had dementia. One patient died and the remaining patient no longer fulfilled criteria for either dementia or CIND, presenting exclusively calcified lesions on neuroimaging. Conclusions: Independently of its phase, NC leads to a spectrum of cognitive abnormalities, ranging from impairment in a single domain, to CIND and, occasionally, to dementia. These findings are more conspicuous during active vesicular phase and less prominent in calcified stages. Neurology (R) 2012; 78: 861-866