Exact Search Directions for Optimization of Linear and Nonlinear Models Based on Generalized Orthonormal Functions

A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

All-optical switching device for infrared based on PbTe quantum dots

Multilayers of PbTe quantum dots embedded in SiO2 were fabricated by alternate use of Pulsed Laser Deposition (PLD) and Plasma Enhanced Chemical Vapor Deposition (PECVD) techniques. The morphological properties of the nanostructured material were studied by means of High Resolution Transmission Electron Microscopy (HRTEM), Grazing-Incidence Small-Angle X-ray scattering (GISAXS) and X-ray Reflectometry (XRR) techniques. A preliminary analysis of the GISAXS spectra provided information about the multilayer periodicity and its relationship to the size of the deposited PbTe nanoparticles. Finally multilayers were fabricated inside a Fabry-Perot cavity. The device was characterized by means of Scanning Electron Microscopy (SEM). Transmittance measurements show the device functionality in the infrared region. (C) 2007 Elsevier Ltd. All rights reserved.

Semiconductor nanoparticle modeling via density functional theory

In this work, a 2.0 nm nanoparticle (low limit synthesized system) is compared to possible simplified models: passivated clusters, small (1.3 nm) nanoparticles and sets of plane surfaces. Our density functional theory results suggest that even when geometric aspects are properly described by the simplifications considered, electronic properties might be very different, especially when edge atoms are not properly taken into account in the nanoparticle`s modeling. In addition, we propose a protocol that might help future theoretical descriptions of nanoparticles.

Realistic calculations of carbon-based disordered systems

Carbon nanotubes rank amongst potential candidates for a new family of nanoscopic devices, in particular for sensing applications. At the same time that defects in carbon nanotubes act as binding sites for foreign species, our current level of control over the fabrication process does not allow one to specifically choose where these binding sites will actually be positioned. In this work we present a theoretical framework for accurately calculating the electronic and transport properties of long disordered carbon nanotubes containing a large number of binding sites randomly distributed along a sample. This method combines the accuracy and functionality of ab initio density functional theory to determine the electronic structure with a recursive Green`s functions method. We apply this methodology on the problem of nitrogen-rich carbon nanotubes, first considering different types of defects and then demonstrating how our simulations can help in the field of sensor design by allowing one to compute the transport properties of realistic nanotube devices containing a large number of randomly distributed binding sites.

Disorder-based graphene spintronics

The use of the spin of the electron as the ultimate logic bit-in what has been dubbed spintronics-can lead to a novel way of thinking about information flow. At the same time single-layer graphene has been the subject of intense research due to its potential application in nanoscale electronics. While defects can significantly alter the electronic properties of nanoscopic systems, the lack of control can lead to seemingly deleterious effects arising from the random arrangement of such impurities. Here we demonstrate, using ab initio density functional theory and non-equilibrium Green`s functions calculations, that it is possible to obtain perfect spin selectivity in doped graphene nanoribbons to produce a perfect spin filter. We show that initially unpolarized electrons entering the system give rise to 100% polarization of the current due to random disorder. This effect is explained in terms of different localization lengths for each spin channel which leads to a new mechanism for the spin filtering effect that is disorder-driven.

First-order-reversal-curve analysis of Pr-Fe-B-based nanocomposites

Ribbons of nominal composition (Pr(9.5)Fe(84.5)B(6))(0.96)Cr(0.01)(TiC)(0.03) were produced by arc-melting and melt-spinning the alloys on a Cu wheel. X-ray diffraction reveals two main phases, one based upon alpha-Fe and the other upon Pr(2)Fe(14)B. The ribbons show exchange spring behavior with H(c)=12.5 kOe and (BH)(max)= 13.6 MGOe when these two phases are well coupled. Transmission electron microscopy revealed that the coupled behavior is observed when the microstructure consists predominantly of alpha-Fe grains(diameter similar to 100 nm.) surrounded by hard material containing Pr(2)Fe(14)B. A first-order-reversal-curve (FORC) analysis was performed for both a well-coupled sample and a partially-coupled sample. The FORC diagrams show two strong peaks for both the partially-coupled sample and for the well coupled material. In both cases, the localization of the FORC probability suggests demagnetizing interactions between particles. Switching field distributions were calculated and are consistent with the sample microstructure. (C) 2009 Elsevier B.V. All rights reserved.

Low-energy nuclear reactions with double-solenoid based radioactive nuclear beam

The University of Notre Dame, USA (Becchetti et al, Nucl. Instrum. Metho ds Res. A505, 377 (2003)) and later the University of Sao Paulo, Brazil (Lichtenthaler et al, Eur. Phys. J. A25, S-01, 733 (2005)) adopted a system based on superconducting solenoids to produce low-energy radioactive nuclear beams. In these systems the solenoids act as thick lenses to collect, select, and focus the secondary beam into a scattering chamb er. Many experiments with radioactive light particle beams (RNB) such as (6)He, (7)Be, (8)Li, (8)B have been performed at these two facilities. These low-energy RNB have been used to investigate low-energy reactions such as elastic scattering, transfer and breakup, providing useful information on the structure of light nuclei near the drip line and on astrophysics. Total reaction cross-sections, derived from elastic scattering analysis, have also been investigated for light system as a function of energy and the role of breakup of weakly bound or exotic nuclei is discussed.

Comments on regularization of identity based solutions in string field theory

We analyze the consistency of the recently proposed regularization of an identity based solution in open bosonic string field theory. We show that the equation of motion is satisfied when it is contracted with the regularized solution itself. Additionally, we propose a similar regularization of an identity based solution in the modified cubic superstring field theory.

The spectrum of an open vertex model based on the U(q)[SU(2)] algebra at roots of unity

We study the exact solution of an N-state vertex model based on the representation of the U(q)[SU(2)] algebra at roots of unity with diagonal open boundaries. We find that the respective reflection equation provides us one general class of diagonal K-matrices having one free-parameter. We determine the eigenvalues of the double-row transfer matrix and the respective Bethe ansatz equation within the algebraic Bethe ansatz framework. The structure of the Bethe ansatz equation combine a pseudomomenta function depending on a free-parameter with scattering phase-shifts that are fixed by the roots of unity and boundary variables. (C) 2010 Elsevier B.V. All rights reserved.

A further exploration of a nucleophilicity index based on the gas-phase ionization potentials

An empirical nucleophilicity index based on the gas-phase ionization potentials has been recently shown to be useful categorizing and settling the nucleophilicity power of a series of captodative ethylenes reacting in cycloaddition reactions (L.R. Domingo, E. Chamorro, P. Perez, Journal of Organic Chemistry 73 (2008) 4615-4624). In the present work, the applicability of such model is tested within a broader series of substituted alkenes, substituted aromatic compounds and simple nucleophilic molecules. This index obtained within a Koopman`s theorem framework has been evaluated here in both gas and solution phases for several well-known nucleophiles. These results are found to be linearly correlated. Finally, the feasibility of the predictive character of this index has been discussed in comparison to the available experimental nucleophilicities of some amines in water. These results further support and validate the usefulness of such approximation in the modeling of the global nucleophilicity. (C) 2008 Elsevier B.V. All rights reserved.

Hematoporphyrin-based photodynamic therapy for cutaneous squamous cell carcinoma in cats

Photodynamic therapy (PDT) using a haematoporphyrin derivative (Photogem (R), General Physics Institute and clustes Ltda) as photosensitizer and light emitting diodes (LEDs) as the light source was evaluated in 12 cats with cutaneous squamous cell carcinoma. Lesions were illuminated with LEDs, (300 J/cm for 30 min) 24 h after the administration of the photosensitizer. Clinical responses were classified as complete disappearance of the tumour with total re-epithelialization; partial response (a reduction greater than 50%); and no response (less than 50% reduction). Tumours localized to the pinna treated with one (n = 3) or two (n = 4) applications of PDT yielded no response. Highly invasive tumours of the nose and nasal planum also showed no response, after two treatments (n = 2). A combination of PDT and surgery was performed in three cases. Two cats showed partial response and one complete response with one application of therapy 30 days after nasal surgery. Small and noninfiltrative lesions (n = 3) of the nasal planum showed a PR with one application (n = 2) and a CR with two applications (n = 1). This study shows that PDT using Photogem (R) and LEDs can provide local control of low-grade feline squamous cell carcinoma. The addition of PDT to surgery in more invasive cases may help prevent recurrence.

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.

Role of Halogen Bonds in Thyroid Hormone Receptor Selectivity: Pharmacophore-Based 3D-QSSR Studies

Most physiological effects of thyroid hormones are mediated by the two thyroid hormone receptor subtypes, TR alpha and TR beta. Several pharmacological effects mediated by TR beta might be beneficial in important medical conditions such as obesity, hypercholesterolemia and diabetes, and selective TR beta activation may elicit these effects while maintaining an acceptable safety profile, To understand the molecular determinants of affinity and subtype selectivity of TR ligands, we have successfully employed a ligand- and structure-guided pharmacophore-based approach to obtain the molecular alignment of a large series of thyromimetics. Statistically reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) and three-dimensional quantitative structure-selectivity relationship (3D-QSSR) models were obtained using the comparative molecular field analysis (CoMFA) method, and the visual analyses of the contour maps drew attention to a number of possible opportunities for the development of analogs with improved affinity and selectivity. Furthermore, the 3D-QSSR analysis allowed the identification of a novel and previously unmentioned halogen bond, bringing new insights to the mechanism of activity and selectivity of thyromimetics.

Cross-situational learning of object-word mapping using Neural Modeling Fields

The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or Virtual agents have brought that issue to a central place in more applied research fields, such as computational linguistics and neural networks, as well. An attractive approach to learning an object-word mapping is the so-called cross-situational learning. This learning scenario is based on the intuitive notion that a learner can determine the meaning of a word by finding something in common across all observed uses of that word. Here we show how the deterministic Neural Modeling Fields (NMF) categorization mechanism can be used by the learner as an efficient algorithm to infer the correct object-word mapping. To achieve that we first reduce the original on-line learning problem to a batch learning problem where the inputs to the NMF mechanism are all possible object-word associations that Could be inferred from the cross-situational learning scenario. Since many of those associations are incorrect, they are considered as clutter or noise and discarded automatically by a clutter detector model included in our NMF implementation. With these two key ingredients - batch learning and clutter detection - the NMF mechanism was capable to infer perfectly the correct object-word mapping. (C) 2009 Elsevier Ltd. All rights reserved.

Structure-Based Approach for the Study of Estrogen Receptor Binding Affinity and Subtype Selectivity

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpa (hER alpha) and beta (hER beta). Because the levels and relative proportion of hER alpha and hER beta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hER alpha and hER beta. Significant statistical coefficients were obtained (hER alpha, q(2) = 0.76; hER beta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hER alpha and hER beta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design or novel hER modulators with improved selectivity.