ENHANCING MULTISCALE FRACTAL DESCRIPTORS USING FUNCTIONAL DATA ANALYSIS

This work presents a novel approach in order to increase the recognition power of Multiscale Fractal Dimension (MFD) techniques, when applied to image classification. The proposal uses Functional Data Analysis (FDA) with the aim of enhancing the MFD technique precision achieving a more representative descriptors vector, capable of recognizing and characterizing more precisely objects in an image. FDA is applied to signatures extracted by using the Bouligand-Minkowsky MFD technique in the generation of a descriptors vector from them. For the evaluation of the obtained improvement, an experiment using two datasets of objects was carried out. A dataset was used of characters shapes (26 characters of the Latin alphabet) carrying different levels of controlled noise and a dataset of fish images contours. A comparison with the use of the well-known methods of Fourier and wavelets descriptors was performed with the aim of verifying the performance of FDA method. The descriptor vectors were submitted to Linear Discriminant Analysis (LDA) classification method and we compared the correctness rate in the classification process among the descriptors methods. The results demonstrate that FDA overcomes the literature methods (Fourier and wavelets) in the processing of information extracted from the MFD signature. In this way, the proposed method can be considered as an interesting choice for pattern recognition and image classification using fractal analysis.

Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data

We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88-99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0 degrees vs. 20 degrees, 0 degrees vs. 60 degrees, and 0 degrees vs. 100 degrees), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (08 vs. 1008), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100 degrees condition in relation to the 0 degrees condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100 degrees condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100 degrees condition.

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.

Iodine(III)-promoted ring expansion of 1-vinylcycloalkanol derivatives: A metal-free approach toward seven-membered rings

A versatile and metal-free approach for the synthesis of molecules bearing seven- and eight-membered rings is described. The strategy is based on the ring expansion of 1-vinylcycloalkanols (or the corresponding silyl or methyl ether) mediated by the hypervalent iodine reagent HTIB (Phl(OH)OTs). The reaction condition can be easily adjusted to give seven-membered rings bearing different functional groups. A route to medium-ring lactones was also developed.

Supramolecular Approach to Gold Nanoparticle/Triruthenium Cluster Hybrid Materials and Interfaces

A systematic and comprehensive study of the interaction of citrate-stabilized gold nanoparticles with triruthenium cluster complexes of general formula [Ru(3)(CH(3)COO)(6)(L)](+) [L = 4-cyanopyridine (4-CNpy), 4,4`-bipyridine (4,4`-bpy) or 4,4`-bis(pyridyl)ethylene (bpe)] has been carried out. The cluster-nanoparticle interaction in solution and the construction of thin films of the hybrid materials were investigated in detail by electronic and surface plasmon resonance (SPR) spectroscopy, Raman scattering spectroscopy and scanning electron microscopy (SEM). Citrate-stabilized gold nanoparticles readily interacted with [Ru(3)O(CH(3)COO)(6)(L)(3)](+) complexes to generate functionalized nanoparticles that tend to aggregate according to rates and extents that depend on the bond strength defined by the characteristics of the cluster L ligands following the sequence bpe > 4,4`-bpy >> 4-CNpy. The formation of compact thin films of hybrid AuNP/[Ru(3)O(CH(3)COO)(6)(L)(3)](+) derivatives with L = bpe and 4,4`-bpy indicated that the stability/lability of AuNP-cluster bonds as well as their solubility are important parameters that influence the film contruction process. Fluorine-doped tin oxide electrodes modified with thin films of these nanomaterials exhibited similar electrocatalytic activity but much higher sensitivity than a conventional gold electrode in the oxidation of nitrite ion to nitrate depending on the bridging cluster complex, demonstrating the high potential for the development of amperometric sensors.

Solvent assisted decomposition of the tetrahedral intermediate of the transesterification reaction to biodiesel production. A density functional study

B3LYP/6-31 + G(d) calculations were employed to investigate the mechanism of the transesterification reaction between a model monoglyceride and the methoxide and ethoxide anions. The gas-phase results reveal that both reactions have essentially the same activation energy (5.9 kcal mol(-1)) for decomposition of the key tetrahedral intermediate. Solvent effects were included by means of both microsolvation and the polarizable continuum solvation model CPCM. Both solvent approaches reduce the activation energy, however, only the microsolvation model is able to introduce some differentiation between methanol and ethanol, yielding a lower activation energy for decomposition of the tetrahedral intermediate in the reaction with methanol (1.1 kcal mol(-1)) than for the corresponding reaction with ethanol (2.8 kcal mol(-1)), in line with experimental evidences. Analysis of the individual energy components within the CPCM approach reveals that electrostatic interactions are the main contribution to stabilization of the transition state. (C) 2009 Elsevier Ltd. All rights reserved.