Magnetic and magnetotransport properties of intermetallic SmMn2Si2

The magnetic properties of naturally layered intermetallic compound SmMn2Si2 with textured structure have been studied. There exist a ferromagnetic transition at 35 K and two antiferromagnetic transitions at 120 and 230 K. The antiferromagnetic state below 230 K exhibits different magnetoresistance, with a negative magnetoresistance of 3%-4% for current I applied perpendicular to the c axis and with a positive magnetoresistance effect of about 4%-6% for current I parallel to the c axis. The observed magnetoresistance is likely to be related to magnetovolume effects. In the ferromagnetic state, a positive magnetoresistance with a maximum increase of 22% under an applied field of 5 T is observed at 4 K, and both H perpendicular to I and H parallel to I configurations show positive magnetoresistance. (C) 1997 American Institute of Physics.

Effective properties of spherically anisotropic piezoelectric composites

Piezoelectric composites consisting of spherically anisotropic piezoelectric inclusions (i.e., piezoceramic material) in an infinite nonpiezoelectric matrix under a uniform electric field are theoretically investigated. Analytical solutions for the elastic displacements and the electric potentials are derived exactly. Taking account of the coupling effects of elasticity, permittivity, and piezoelectricity, formulas are derived for the effective dielectric and piezoelectric responses in the dilute limit. A piezoelectric response mechanism is revealed, in which the effective piezoelectric response vanishes irrespective of how much spherically anisotropic piezoelectric inclusions are inside. Moreover, the effective coupled responses of the piezoelectric composites show that the effective dielectric responses decrease (increase) as the inclusion elastic (piezoelectric) constants increase.

Electrochemical Synthesis of Barium Tungstate Crystallites with Different Morphologies: Effect of Electrolyte Components

Barium tungstate crystallites with different sizes and morphologies were successfully synthesized using a simple electro-chemical technique by varying the components of electrolyte solutions. XRD analysis evidenced that the as-prepared samples were a pure tetragonal-phase of BaWO4 with a scheelite structure. Scanning electron microscopy images and PL spectra of BaWO4 crystallites revealed that the presence of OH- ions and the incorporation of absolute ethanol into the electrolyte solution would have important effects on their particle sizes, morphologies, and optical properties.

Synthesis of NiWO4 nano-particles in low-temperature molten salt medium

Nickel tungstate (NiWO4) nano-particles were successfully synthesized at low temperatures by a molten salt method, and characterized by Xray diffraction (XRD), transmission electron microscopy (TEM) and ultraviolet visible spectra techniques (UV-vis), respectively. The effects of calcining temperature and salt quantity on the crystallization and development of NiWO4 crystallites were studied. Experimental results showed that the well-crystallized NiWO4 nano-particles with about 30 nm in diameter could be prepared at 270 degrees C with 6:1 mass ratio of the salt to NiWO4 precursor. XRD analysis confirmed that the product was a pure monoclinic phase of NiWO4 with wolframite structure. UV-vis spectrum revealed that NiWO4 nano-particles had good light absorption properties in both ultraviolet and visible light region. (C) 2009 Elsevier Ltd and Techna Group S.r.l. All rights reserved.

Automatically Recovering Geometry and Texture from Large Sets of Calibrated Images

Three-dimensional models which contain both geometry and texture have numerous applications such as urban planning, physical simulation, and virtual environments. A major focus of computer vision (and recently graphics) research is the automatic recovery of three-dimensional models from two-dimensional images. After many years of research this goal is yet to be achieved. Most practical modeling systems require substantial human input and unlike automatic systems are not scalable. This thesis presents a novel method for automatically recovering dense surface patches using large sets (1000's) of calibrated images taken from arbitrary positions within the scene. Physical instruments, such as Global Positioning System (GPS), inertial sensors, and inclinometers, are used to estimate the position and orientation of each image. Essentially, the problem is to find corresponding points in each of the images. Once a correspondence has been established, calculating its three-dimensional position is simply a matter of geometry. Long baseline images improve the accuracy. Short baseline images and the large number of images greatly simplifies the correspondence problem. The initial stage of the algorithm is completely local and scales linearly with the number of images. Subsequent stages are global in nature, exploit geometric constraints, and scale quadratically with the complexity of the underlying scene. We describe techniques for: 1) detecting and localizing surface patches; 2) refining camera calibration estimates and rejecting false positive surfels; and 3) grouping surface patches into surfaces and growing the surface along a two-dimensional manifold. We also discuss a method for producing high quality, textured three-dimensional models from these surfaces. Some of the most important characteristics of this approach are that it: 1) uses and refines noisy calibration estimates; 2) compensates for large variations in illumination; 3) tolerates significant soft occlusion (e.g. tree branches); and 4) associates, at a fundamental level, an estimated normal (i.e. no frontal-planar assumption) and texture with each surface patch.

Women Potters: Transforming Traditions

Vincentelli, Moira, Women Potters: Transforming Traditions (London: A and C Black, 2003) RAE2008

Facetas de Porcelana VS Facetas de Resina Composta

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Medicina Dentária

Qual a eficácia clínica do sistema CEREC com os seus diferentes materiais para reabilitação em prótese fixa e sobre implantes?

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Medicina Dentária

A Neural Model of 3D Shape-From-Texture: Multiple-Scale Filtering, Boundary Grouping, and Surface Filling-In

A neural model is presented of how cortical areas V1, V2, and V4 interact to convert a textured 2D image into a representation of curved 3D shape. Two basic problems are solved to achieve this: (1) Patterns of spatially discrete 2D texture elements are transformed into a spatially smooth surface representation of 3D shape. (2) Changes in the statistical properties of texture elements across space induce the perceived 3D shape of this surface representation. This is achieved in the model through multiple-scale filtering of a 2D image, followed by a cooperative-competitive grouping network that coherently binds texture elements into boundary webs at the appropriate depths using a scale-to-depth map and a subsequent depth competition stage. These boundary webs then gate filling-in of surface lightness signals in order to form a smooth 3D surface percept. The model quantitatively simulates challenging psychophysical data about perception of prolate ellipsoids (Todd and Akerstrom, 1987, J. Exp. Psych., 13, 242). In particular, the model represents a high degree of 3D curvature for a certain class of images, all of whose texture elements have the same degree of optical compression, in accordance with percepts of human observers. Simulations of 3D percepts of an elliptical cylinder, a slanted plane, and a photo of a golf ball are also presented.

Texture Segregation By Visual Cortex: Perceptual Grouping, Attention, and Learning

A neural model is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model brings together five interacting processes: region-based texture classification, contour-based boundary grouping, surface filling-in, spatial attention, and object attention. The model shows how form boundaries can determine regions in which surface filling-in occurs; how surface filling-in interacts with spatial attention to generate a form-fitting distribution of spatial attention, or attentional shroud; how the strongest shroud can inhibit weaker shrouds; and how the winning shroud regulates learning of texture categories, and thus the allocation of object attention. The model can discriminate abutted textures with blurred boundaries and is sensitive to texture boundary attributes like discontinuities in orientation and texture flow curvature as well as to relative orientations of texture elements. The model quantitatively fits a large set of human psychophysical data on orientation-based textures. Object boundar output of the model is compared to computer vision algorithms using a set of human segmented photographic images. The model classifies textures and suppresses noise using a multiple scale oriented filterbank and a distributed Adaptive Resonance Theory (dART) classifier. The matched signal between the bottom-up texture inputs and top-down learned texture categories is utilized by oriented competitive and cooperative grouping processes to generate texture boundaries that control surface filling-in and spatial attention. Topdown modulatory attentional feedback from boundary and surface representations to early filtering stages results in enhanced texture boundaries and more efficient learning of texture within attended surface regions. Surface-based attention also provides a self-supervising training signal for learning new textures. Importance of the surface-based attentional feedback in texture learning and classification is tested using a set of textured images from the Brodatz micro-texture album. Benchmark studies vary from 95.1% to 98.6% with attention, and from 90.6% to 93.2% without attention.