Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland

Surface roughness is an important geomorphological variable which has been used in the Earth and planetary sciences to infer material properties, current/past processes, and the time elapsed since formation. No single definition exists; however, within the context of geomorphometry, we use surface roughness as an expression of the variability of a topographic surface at a given scale, where the scale of analysis is determined by the size of the landforms or geomorphic features of interest. Six techniques for the calculation of surface roughness were selected for an assessment of the parameter`s behavior at different spatial scales and data-set resolutions. Area ratio operated independently of scale, providing consistent results across spatial resolutions. Vector dispersion produced results with increasing roughness and homogenization of terrain at coarser resolutions and larger window sizes. Standard deviation of residual topography highlighted local features and did not detect regional relief. Standard deviation of elevation correctly identified breaks of slope and was good at detecting regional relief. Standard deviation of slope (SD(slope)) also correctly identified smooth sloping areas and breaks of slope, providing the best results for geomorphological analysis. Standard deviation of profile curvature identified the breaks of slope, although not as strongly as SD(slope), and it is sensitive to noise and spurious data. In general, SD(slope) offered good performance at a variety of scales, while the simplicity of calculation is perhaps its single greatest benefit.

Fiedler trees for multiscale surface analysis

In this work we introduce a new hierarchical surface decomposition method for multiscale analysis of surface meshes. In contrast to other multiresolution methods, our approach relies on spectral properties of the surface to build a binary hierarchical decomposition. Namely, we utilize the first nontrivial eigenfunction of the Laplace-Beltrami operator to recursively decompose the surface. For this reason we coin our surface decomposition the Fiedler tree. Using the Fiedler tree ensures a number of attractive properties, including: mesh-independent decomposition, well-formed and nearly equi-areal surface patches, and noise robustness. We show how the evenly distributed patches can be exploited for generating multiresolution high quality uniform meshes. Additionally, our decomposition permits a natural means for carrying out wavelet methods, resulting in an intuitive method for producing feature-sensitive meshes at multiple scales. Published by Elsevier Ltd.

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.

Multiscale Curvature Analysis of Asphaltic Aggregate Particles

A new method for characterization and analysis of asphaltic mixtures aggregate particles is reported. By relying on multiscale representation of the particles, curvature estimation, and discriminant analysis for optimal separation of the categories of mixtures, a particularly effective and comprehensive methodology is obtained. The potential of the methodology is illustrated with respect to three important types of particles used in asphaltic mixtures, namely basalt, gabbro, and gravel. The obtained results show that gravel particles are markedly distinct from the other two types of particles, with the gabbro category resulting with intermediate geometrical properties. The importance of each considered measurement in the discrimination between the three categories of particles was also quantified in terms of the adopted discriminant analysis.

Learning processes and the neural analysis of conditioning

Classical and operant conditioning principles, such as the behavioral discrepancy-derived assumption that reinforcement always selects antecedent stimulus and response relations, have been studied at the neural level, mainly by observing the strengthening of neuronal responses or synaptic connections. A review of the literature on the neural basis of behavior provided extensive scientific data that indicate a synthesis between the two conditioning processes based mainly on stimulus control in learning tasks. The resulting analysis revealed the following aspects. Dopamine acts as a behavioral discrepancy signal in the midbrain pathway of positive reinforcement, leading toward the nucleus accumbens. Dopamine modulates both types of conditioning in the Aplysia mollusk and in mammals. In vivo and in vitro mollusk preparations show convergence of both types of conditioning in the same motor neuron. Frontal cortical neurons are involved in behavioral discrimination in reversal and extinction procedures, and these neurons preferentially deliver glutamate through conditioned stimulus or discriminative stimulus pathways. Discriminative neural responses can reliably precede operant movements and can also be common to stimuli that share complex symbolic relations. The present article discusses convergent and divergent points between conditioning paradigms at the neural level of analysis to advance our knowledge on reinforcement.

PARTITIONED ANALYSIS FOR DIMENSIONALLY-HETEROGENEOUS HYDRAULIC NETWORKS

In this work an iterative strategy is developed to tackle the problem of coupling dimensionally-heterogeneous models in the context of fluid mechanics. The procedure proposed here makes use of a reinterpretation of the original problem as a nonlinear interface problem for which classical nonlinear solvers can be applied. Strong coupling of the partitions is achieved while dealing with different codes for each partition, each code in black-box mode. The main application for which this procedure is envisaged arises when modeling hydraulic networks in which complex and simple subsystems are treated using detailed and simplified models, correspondingly. The potentialities and the performance of the strategy are assessed through several examples involving transient flows and complex network configurations.

A simple method for non-linear analysis of steel fiber reinforced concrete

This paper proposes a physical non-linear formulation to deal with steel fiber reinforced concrete by the finite element method. The proposed formulation allows the consideration of short or long fibers placed arbitrarily inside a continuum domain (matrix). The most important feature of the formulation is that no additional degree of freedom is introduced in the pre-existent finite element numerical system to consider any distribution or quantity of fiber inclusions. In other words, the size of the system of equations used to solve a non-reinforced medium is the same as the one used to solve the reinforced counterpart. Another important characteristic of the formulation is the reduced work required by the user to introduce reinforcements, avoiding ""rebar"" elements, node by node geometrical definitions or even complex mesh generation. Bounded connection between long fibers and continuum is considered, for short fibers a simplified approach is proposed to consider splitting. Non-associative plasticity is adopted for the continuum and one dimensional plasticity is adopted to model fibers. Examples are presented in order to show the capabilities of the formulation.

GENERALIZED FINITE ELEMENT METHOD FOR NONLINEAR THREE-DIMENSIONAL ANALYSIS OF SOLIDS

The Generalized Finite Element Method (GFEM) is employed in this paper for the numerical analysis of three-dimensional solids tinder nonlinear behavior. A brief summary of the GFEM as well as a description of the formulation of the hexahedral element based oil the proposed enrichment strategy are initially presented. Next, in order to introduce the nonlinear analysis of solids, two constitutive models are briefly reviewed: Lemaitre`s model, in which damage and plasticity are coupled, and Mazars`s damage model suitable for concrete tinder increased loading. Both models are employed in the framework of a nonlocal approach to ensure solution objectivity. In the numerical analyses carried out, a selective enrichment of approximation at regions of concern in the domain (mainly those with high strain and damage gradients) is exploited. Such a possibility makes the three-dimensional analysis less expensive and practicable since re-meshing resources, characteristic of h-adaptivity, can be minimized. Moreover, a combination of three-dimensional analysis and the selective enrichment presents a valuable good tool for a better description of both damage and plastic strain scatterings.

Long-Term Astroglial Reaction and Neuronal Plasticity in the Subcortical Visual Pathways After a Complete Ablation of Telencephalon in Pigeons (Columba livia)

This paper analyzes the astroglial and neuronal responses in subtelencephalic structures, following a bilateral ablation of the telencephalon in the Columba livia pigeons. Control birds received a sham operation. Four months later the birds were sacrificed and their brains processed for glial fribillary acid protein (GFAP) and neurofilament immunohistochemistry, markers for astrocytes and neurons, respectively. Computer-assisted image analysis was employed for quantification of the immunoreactive labeling in the nucleus rotundus (N.Rt) and the optic tectum (OT) of the birds. An increased number of GFAP immunoreactive astrocytes were found in several subregions of the N.Rt (p .001), as well as in layers 1, 2cd, 3, and 6 of the OT (p .001) of the lesioned animals. Neurofilament immunoreactivity decreased massively in the entire N.Rt of the lesioned birds; however, remaining neurons with healthy aspect showing large cytoplasm and ramified branches were detected mainly in the periphery of the nucleus. In view of the recently described paracrine neurotrophic properties of the activated astrocytes, the data of the present study may suggest a long-lasting neuroglial interaction in regions of the lesioned bird brain far from injury. Such events may trigger neuronal plasticity in remaining brain structures that may lead spontaneous behavior recovery as the one promoted here even after a massive injury.

Qualitative analysis of hippocampal plastic changes in rats with epilepsy supplemented with oral omega-3 fatty acids

Studies have provided evidence of the important effects of omega-3 fatty acid on the brain in neurological conditions, including epilepsy. Previous data have indicated that omega-3 fatty acids lead to prevention of status epilepticus-associated neuropathological changes in the hippocampal formation of rats with epilepsy. Omega-3 fatty acid supplementation has resulted in extensive preservation of GABAergic cells in animals with epilepsy. This study investigated the interplay of these effects with neurogenesis and brain-derived neurotrophic factor (BDNF). The results clearly showed a positive effect of long-term omega-3 fatty acid supplementation on brain plasticity in animals with epilepsy. Enhanced hippocampal neurogenesis and BDNF levels and preservation of interneurons expressing parvalbumin were observed. Parvalbumin-positive cells were identified as surviving instead of newly formed cells. Additional investigations are needed to determine the electrophysiological properties of the newly formed cells and to clarify whether the effects of omega-3 fatty acids on brain plasticity are accompanied by functional gain in animals with epilepsy. (C) 2009 Elsevier Inc. All rights reserved.

Plasticity of Opioid Receptors in the Female Periaqueductal Gray: Multiparity-Induced Increase in the Activity of Genes Encoding for Mu and Kappa Receptors and a Post-Translational Decrease in Delta Receptor Expression

The periaqueductal gray (PAG) has been reported as a potential site for opioid regulation of behavioral selection. Opioid-mediated behavioral and physiological responses differ between nulliparous and multiparous females. This study addresses the effects of multiple reproductive experiences on mu-, kappa- and delta-opioid receptor (Oprm1, Oprk1, and Oprd1 respectively) gene activity and mu, kappa and delta protein expression (MOR, KOR and DOR respectively) in the PAG of the female rats. This was done by evaluating the opioid gene expression using real-time (RT-PCR) and quantification of each protein receptor by Western blot analysis. The RT-PCR results show that multiple reproductive experiences increase Oprm1 and Oprk1 gene expression. Western blot analysis revealed increased MOR and KOR while DOR protein was decreased in multiparous animals. Taken together, these data suggest that multiple reproductive experiences influence both gene activity and opioid receptor expression in the PAG. Post-translational mechanisms seem particularly relevant for DOR expression. Thus, opioid transmission in the PAG might be modulated by different mechanisms of multiparity-induced plasticity according to the opioid receptor type.

Medical image retrieval based on complexity analysis

Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.

A complex network-based approach for boundary shape analysis

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

Digital subtraction radiographic analysis of the combination of bioabsorbable membrane and bovine morphogenetic protein pool in human periodontal infrabony defects

OBJECTIVES: This study assessed the bone density gain and its relationship with the periodontal clinical parameters in a case series of a regenerative therapy procedure. MATERIAL AND METHODS: Using a split-mouth study design, 10 pairs of infrabony defects from 15 patients were treated with a pool of bovine bone morphogenetic proteins associated with collagen membrane (test sites) or collagen membrane only (control sites). The periodontal healing was clinically and radiographically monitored for six months. Standardized pre-surgical and 6-month postoperative radiographs were digitized for digital subtraction analysis, which showed relative bone density gain in both groups of 0.034 ± 0.423 and 0.105 ± 0.423 in the test and control group, respectively (p>0.05). RESULTS: As regards the area size of bone density change, the influence of the therapy was detected in 2.5 mm² in the test group and 2 mm² in the control group (p>0.05). Additionally, no correlation was observed between the favorable clinical results and the bone density gain measured by digital subtraction radiography (p>0.05). CONCLUSIONS: The findings of this study suggest that the clinical benefit of the regenerative therapy observed did not come with significant bone density gains. Long-term evaluation may lead to a different conclusions.

Isolation of Pseudomonas aeruginosa strains from dental office environments and units in Barretos, state of São Paulo, Brazil, and analysis of their susceptibility to antimicrobial drugs

A wide variety of opportunistic pathogens has been detected in the tubing supplying water to odontological equipment, in special in the biofilm lining of these tubes. Among these pathogens, Pseudomonas aeruginosa, one of the leading causes of nosocomial infections, is frequently found in water lines supplying dental units. In the present work, 160 samples of water, and 200 fomite samples from forty dental units were collected in the city of Barretos, State of São Paulo, Brazil and evaluated between January and July, 2005. Seventy-six P. aeruginosa strains, isolated from the dental environment (5 strains) and water system (71 strains), were tested for susceptibility to six antimicrobial drugs most frequently used against P. aeruginosa infections. Susceptibility to ciprofloxacin, followed by meropenem was the predominant profile. The need for effective means of reducing the microbial burden within dental unit water lines is emphasized, and the risk of exposure and cross-infection in dental practice, in special when caused by opportunistic pathogens like P. aeruginosa, are highlighted.