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).

Theoretical luminescence spectra in p-type superlattices based on InGaAsN

In this work, we present a theoretical photoluminescence (PL) for p-doped GaAs/InGaAsN nanostructures arrays. We apply a self-consistent method in the framework of the effective mass theory. Solving a full 8 x 8 Kane's Hamiltonian, generalized to treat different materials in conjunction with the Poisson equation, we calculate the optical properties of these systems. The trends in the calculated PL spectra, due to many-body effects within the quasi-two-dimensional hole gas, are analyzed as a function of the acceptor doping concentration and the well width. Effects of temperature in the PL spectra are also investigated. This is the first attempt to show theoretical luminescence spectra for GaAs/InGaAsN nanostructures and can be used as a guide for the design of nanostructured devices such as optoelectronic devices, solar cells, and others.

Deconvolution of the EPR spectra of vanadium oxide nanotubes

In this work we report results of continuous wave (CW) electron paramagnetic resonance (EPR) spectroscopy of vanadium oxide nanotubes. The observed EPR spectra are composed of a weak well-resolved spectrum of isolated V4+ ions on top of an intense and broad structure-less line shape, attributed to spin-spin exchanged V4+ clusters. With the purpose to deconvolute the structured weak spectrum from the composed broad line, a new approach based on the Krylov basis diagonalization method (KBDM) is introduced. It is based on the discrimination between broad and sharp components with respect to a selectable threshold and can be executed with few adjustable parameters, without the need of a priori information on the shape and structure of the lines. This makes the method advantageous with respect to other procedures and suitable for fast and routine spectral analysis, which, in conjunction with simulation techniques based on the spin Hamiltonian parameters, can provide a full characterization of the EPR spectrum. Results demonstrate and characterize the coexistence of two V4+ species in the nanotubes and show good progress toward the goal of obtaining high fidelity deconvoluted spectra from complex signals with overlapping broader line shapes. (C) 2012 Elsevier Inc. All rights reserved.

Optimization of x-ray spectra in digital mammography through Monte Carlo simulations

In this work, a Monte Carlo code was used to investigate the performance of different x-ray spectra in digital mammography, through a figure of merit (FOM), defined as FOM = CNR2/(D) over bar (g), with CNR being the contrast-to-noise ratio in image and (D) over bar (g) being the average glandular dose. The FOM was studied for breasts with different thicknesses t (2 cm <= t <= 8 cm) and glandular contents (25%, 50% and 75% glandularity). The anode/filter combinations evaluated were those traditionally employed in mammography (Mo/Mo, Mo/Rh, Rh/Rh), and a W anode combined with Al or K-edge filters (Zr, Mo, Rh, Pd, Ag, Cd, Sn), for tube potentials between 22 and 34 kVp. Results show that the W anode combined with K-edge filters provides higher values of FOM for all breast thicknesses investigated. Nevertheless, the most suitable filter and tube potential depend on the breast thickness, and for t >= 6 cm, they also depend on breast glandularity. Particularly for thick and dense breasts, a W anode combined with K-edge filters can greatly improve the digital technique, with the values of FOM up to 200% greater than that obtained with the anode/filter combinations and tube potentials traditionally employed in mammography. For breasts with t < 4 cm, a general good performance was obtained with the W anode combined with 60 mu m of the Mo filter at 24-25 kVp, while 60 mu m of the Pd filter provided a general good performance at 24-26 kVp for t = 4 cm, and at 28-30 and 29-31 kVp for t = 6 and 8 cm, respectively.

Comparative study on the far-field spectra and near-field amplitudes for silver and gold nanocubes irradiated at 514, 633 and 785 nm as a function of the edge length

We describe a systematic investigation by the discrete dipole approximation on the optical properties of silver (Ag) and gold (Au) nanocubes as a function of the edge length in the 20-100 nm range. Our results showed that, as the nanocube size increased, the plasmon resonance modes shifted to higher wavelengths, the contribution from scattering to the extinction increased, and the quadrupole modes became more intense in the spectra. The electric field amplitudes at the surface of the nanocubes were calculated considering 514, 633 and 785 nm as the excitation wavelengths. While Ag nanocubes displayed the highest electric field amplitudes (vertical bar E vertical bar(max)) when excited at 514 nm, the Au nanocubes displayed higher vertical bar E vertical bar(max) values than Ag, for all sizes investigated, when the excitation wavelength was either 633 or 785 nm. The variations in vertical bar E vertical bar(max) as a function of size for both Ag and Au nanocubes could be explained based on the relative position of the surface plasmon resonance peak relative to the wavelength of the incoming electromagnetic wave. Our results show that not only size and composition, but also the excitation wavelength, can play an important role over the maximum near-field amplitudes values generated at the surface of the nanocubes.

Femtosecond third-order nonlinear spectra of lead-germanium oxide glasses containing silver nanoparticles

This work reports on the spectral dependence of both nonlinear refraction and absorption in lead-germanium oxide glasses (PbO-GeO2) containing silver nanoparticles. We have found that this material is suitable for all-optical switching at telecom wavelengths but at the visible range it behaves either as a saturable absorber or as an optical limiter. (C) 2012 Optical Society of America

Result on speech perception after conversion from Spectra (R) to Freedom (R)

New technology in the Freedom (R) speech processor for cochlear implants was developed to improve how incoming acoustic sound is processed; this applies not only for new users, but also for previous generations of cochlear implants. Aim: To identify the contribution of this technology - the Nucleus 22 (R) - on speech perception tests in silence and in noise, and on audiometric thresholds. Methods: A cross-sectional cohort study was undertaken. Seventeen patients were selected. The last map based on the Spectra (R) was revised and optimized before starting the tests. Troubleshooting was used to identify malfunction. To identify the contribution of the Freedom (R) technology for the Nucleus22 (R), auditory thresholds and speech perception tests were performed in free field in soundproof booths. Recorded monosyllables and sentences in silence and in noise (SNR = 0dB) were presented at 60 dBSPL. The nonparametric Wilcoxon test for paired data was used to compare groups. Results: Freedom (R) applied for the Nucleus22 (R) showed a statistically significant difference in all speech perception tests and audiometric thresholds. Conclusion: The reedom (R) technology improved the performance of speech perception and audiometric thresholds of patients with Nucleus 22 (R).

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.

Metallicities for six nearby open clusters from high-resolution spectra of giant stars [Fe/H] values for a planet search sample

We present a study of the stellar parameters and iron abundances of 18 giant stars in six open clusters. The analysis was based on high-resolution and high-S/N spectra obtained with the UVES spectrograph (VLT-UT2). The results complement our previous study where 13 clusters were already analyzed. The total sample of 18 clusters is part of a program to search for planets around giant stars. The results show that the 18 clusters cover a metallicity range between -0.23 and +0.23 dex. Together with the derivation of the stellar masses, these metallicities will allow the metallicity and mass effects to be disentangled when analyzing the frequency of planets as a function of these stellar parameters.

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.

Thermal Analysis and Raman Spectra of Different Phases of the Ionic Liquid Butyltrimethylammonium Bis(trifluoromethylsulfonyl)imide

The ionic liquid butyltrimethylammonium bis(trifluoromethylsulfonyl)imide, [C4C1C1C1N][Tf2N], is a glass-forming liquid that exhibits partial crystallization depending on the cooling rate. Differential scanning calorimetry (DSC) indicates crystallization at T-c = 227 K, melting at T-m = 258 K, glass transition at T-g similar to 191 K, and also cold crystallization at T-cc similar to 219 K. Raman spectroscopy shows that the crystalline structure obtained by slow cooling is formed with [Tf2N](-) in cisoid conformation, whereas [Tf2N](-) in transoid conformation results from fast cooling. No preferred conformation of the butyl chain of the [C4C1C1C1N](+) cation is favored by slow or fast cooling of [C4C1C1C1N][Tf2N]. Low-frequency Raman spectroscopy shows that crystalline domains developing in the supercooled liquid result in a glacial state made of a mixture of crystallites and amorphous phase. However, these crystalline structures obtained by slow cooling or cold crystallization are not the same because anion-cation interactions promote local structures with distinct conformations of the [Tf2N](-) anion.

Shape resonance spectra of lignin subunits

We report integral cross sections for elastic electron scattering by the lignin subunits phenol, guaiacol, and p-coumaryl alcohol. Our calculations employed the Schwinger multichannel method with pseudopotentials and indicate three to four pi* shape resonances for each of these systems, suggesting that low-energy electrons could efficiently transfer energy into the lignin matrix. We also discuss dissociation mechanisms based on the calculated cross sections, available experimental data, virtual orbital analysis, and the knowledge on electron interactions with biomolecules. Our results point out a physical-chemical basis for electron-driven biomass delignification. The latter would be an essential step for efficient biofuel production from lignocellulosic materials.

Processing of high resolution magic angle spinning spectra of breast cancer cells by the filter diagonalization method

Proton nuclear magnetic resonance (H-1 NMR) spectroscopy for detection of biochemical changes in biological samples is a successful technique. However, the achieved NMR resolution is not sufficiently high when the analysis is performed with intact cells. To improve spectral resolution, high resolution magic angle spinning (HR-MAS) is used and the broad signals are separated by a T-2 filter based on the CPMG pulse sequence. Additionally, HR-MAS experiments with a T-2 filter are preceded by a water suppression procedure. The goal of this work is to demonstrate that the experimental procedures of water suppression and T-2 or diffusing filters are unnecessary steps when the filter diagonalization method (FDM) is used to process the time domain HR-MAS signals. Manipulation of the FDM results, represented as a tabular list of peak positions, widths, amplitudes and phases, allows the removal of water signals without the disturbing overlapping or nearby signals. Additionally, the FDM can also be used for phase correction and noise suppression, and to discriminate between sharp and broad lines. Results demonstrate the applicability of the FDM post-acquisition processing to obtain high quality HR-MAS spectra of heterogeneous biological materials.