959 resultados para surface texture


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Crystallographic texture is perceived to play an important role in controlling material properties. However, the influence of texture in modulating the properties of biomedical materials has not been well investigated. In this work, commercially pure titanium (cp-Ti) was processed through six different routes to generate a variety of textures. The effect of texture on mechanical properties, corrosion behavior, cell proliferation and osteogenesis was characterized for potential use in orthopedic applications. The presence of closely packed, low-energy crystallographic planes at the material surface was influenced by the volume fraction of the components in the overall texture, thereby influencing surface energy and corrosion behavior. Texture modulated osteoblast proliferation through variations in surface water wettability. It also affected mineralization by possibly influencing the coherency between the substrate and calcium phosphate deposits. This study demonstrates that crystallographic texture can be an important tool in improving the properties of biomaterials to achieve the enhanced performance of biomedical implants.

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Magnesium and its alloys are an emerging class of resorbable materials for orthopedic and cardiovascular applications. The typical strategy underlying the development of these materials involves the control of material processing routes and the addition of alloying elements. Crystallographic texture is known to control bulk mechanical as well as surface properties. However, its role in determining the properties of magnesium for implant materials has not been well studied. In this work, an extruded rod of pure magnesium was cut in multiple directions to generate samples with different textures. It was found that texture significantly affected the strength and ductility of magnesium. Corrosion rates in Hank's solution decreased with the increased presence of low energy basal planes at the surface. In vitro cell studies revealed that changes in texture did not induce cytotoxicity. Thus, the control of texture in magnesium based implants could be used to tailor the mechanical properties and the resorption rates without compromising cytocompatibility. This study elucidates the importance of texture in the use of magnesium as a resorbable biomaterial.

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In spite of intense research on ZnO over the past decade, the detailed investigation about the crystallographic texture of as obtained ZnO thin films/coatings, and its deviation with growth surface is scarce. We report a systematic study about the orientation distribution of nanostructured ZnO thin films fabricated by microwave irradiation with the variation of substrates and surfactants. The nanostructured films comprising of ZnO nanorods are grown on semiconductor substrates such as Si(100), Ge(100)], conducting substrates (ITO-coated glass, Cr coated Si), and polymer coated Si (PMMA/Si) to examine the respective development of crystallographic texture. The ZnO deposited on semiconductor substrates yieldsmixed texture, whereas c-axis oriented ZnO nanostructured films are obtained by conducting substrate, and PMMA coated Si substrates. Among all the surfactants, nanostructured film produced by using the lower molecular weight of polymeric surfactants (polyvinylpyrrolidone) shows a stronger (0002) texture, and that can be tuned to (10 - 10) by increasing the molecular weight of the surfactant. The strongest basal pole is achieved for the ZnO deposited on PMMA coated Si as substrate, and cetyl-trimethyl ammonium bromide as cationic surfactant. The texture analysis is carried out by X-ray pole figure analysis using the Schultz reflection method. (C) 2015 Elsevier B.V. All rights reserved.

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Through a combination of experimental techniques we show that the topmost layer of the topological insulator TlBiSe2 as prepared by cleavage is formed by irregularly shaped Tl islands at cryogenic temperatures and by mobile Tl atoms at room temperature. No trivial surface states are observed in photoemission at low temperatures, which suggests that these islands cannot be regarded as a clear surface termination. The topological surface state is, however, clearly resolved in photoemission experiments. This is interpreted as direct evidence of its topological self-protection and shows the robust nature of the Dirac cone-like surface state. Our results can also help explain the apparent mass acquisition in S-doped TlBiSe2.

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Surface texturing has a great potential to improve tribological performance. First, possible texturing methods were identified and classified according to their physical principles. In sequence, some alternative texturing methods are presented. Some of them are already currently used either in industry or in laboratory, and innovations or simplifications are described for them. Others are innovative techniques. Some were explored only tentatively, where basic ideas and simple experimental investigations were developed to check their validity. Others were explored in more detail, so that their practical applicability could be identified. The first texturing method was photochemical texturing using a simple and cheap apparatus. Masking with inkjet printing before chemical etching was also successful to texture metallic samples. A new method involving electrochemical texturing, without the need to previously mask the samples to be textured have been studied in terms of voltage, current, mechanical configuration of the apparatus and electrolyte flushing. Another method aims to generate randomly distributed circular pockets on steel surfaces and involves dispersion of small acid droplets in oil. The final method involves the selective formation of hard areas on a steel surface by locallised diffusion, which should then develop into a texture during wear.

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Nanocrystalline ZnO films with strong (0002) texture and fine grains were deposited onto ultra-nanocrystalline diamond (UNCD) layers on silicon using high target utilization sputtering technology. The unique characteristic of this sputtering technique allows room temperature growth of smooth ZnO films with a low roughness and low stress at high growth rates. Surface acoustic wave (SAW) devices were fabricated on ZnO/UNCD structure and exhibited good transmission signals with a low insertion loss and a strong side-lobe suppression for the Rayleigh mode SAW. Based on the optimization of the layered structure of the SAW device, a good performance with a coupling coefficient of 5.2% has been realized, promising for improving the microfluidic efficiency in droplet transportation comparing with that of the ZnO/Si SAW device. An optimized temperature coefficient of frequency of -23.4 ppm°C-1 was obtained for the SAW devices with the 2.72 μm-thick ZnO and 1.1 μm-thick UNCD film. Significant thermal effect due to the acoustic heating has been redcued which is related to the temperature stability of the ZnO/UNCD SAW device. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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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.

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This thesis explores how to represent image texture in order to obtain information about the geometry and structure of surfaces, with particular emphasis on locating surface discontinuities. Theoretical and psychophysical results lead to the following conclusions for the representation of image texture: (1) A texture edge primitive is needed to identify texture change contours, which are formed by an abrupt change in the 2-D organization of similar items in an image. The texture edge can be used for locating discontinuities in surface structure and surface geometry and for establishing motion correspondence. (2) Abrupt changes in attributes that vary with changing surface geometry ??ientation, density, length, and width ??ould be used to identify discontinuities in surface geometry and surface structure. (3) Texture tokens are needed to separate the effects of different physical processes operating on a surface. They represent the local structure of the image texture. Their spatial variation can be used in the detection of texture discontinuities and texture gradients, and their temporal variation may be used for establishing motion correspondence. What precisely constitutes the texture tokens is unknown; it appears, however, that the intensity changes alone will not suffice, but local groupings of them may. (4) The above primitives need to be assigned rapidly over a large range in an image.

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Uniformly carbon-covered alumina (CCA) was prepared via the carbonization of sucrose highly dispersed on the alumina surface. The CCA samples were characterized by XRD, XPS, DTA-TG, UV Raman, nitrogen adsorption experiments at 77 K, and rhodamine B (RB) adsorption in aqueous media. UV Raman spectra indicated that the carbon species formed were probably conjugated olefinic or polycyclic aromatic hydrocarbons, which can be considered molecular subunits of a graphitic plane. The N(2) adsorption isotherms, pore size distributions, and XPS results indicated that carbon was uniformly dispersed on the alumina surface in the as-prepared CCA. The carbon coverage and number of carbon layers in CCA could be controlled by the tuning of the sucrose content in the precursor and impregnation times. RB adsorption isotherms suggested that the monolayer adsorption capacity of RB on alumina increased drastically for the sample with uniformly dispersed carbon. The as-prepared CCA possessed the texture of alumina and the surface properties of carbon or both carbon and alumina depending on the carbon coverage.

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A novel method for 3D head tracking in the presence of large head rotations and facial expression changes is described. Tracking is formulated in terms of color image registration in the texture map of a 3D surface model. Model appearance is recursively updated via image mosaicking in the texture map as the head orientation varies. The resulting dynamic texture map provides a stabilized view of the face that can be used as input to many existing 2D techniques for face recognition, facial expressions analysis, lip reading, and eye tracking. Parameters are estimated via a robust minimization procedure; this provides robustness to occlusions, wrinkles, shadows, and specular highlights. The system was tested on a variety of sequences taken with low quality, uncalibrated video cameras. Experimental results are reported.

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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.

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When we look at a scene, how do we consciously see surfaces infused with lightness and color at the correct depths? Random Dot Stereograms (RDS) probe how binocular disparity between the two eyes can generate such conscious surface percepts. Dense RDS do so despite the fact that they include multiple false binocular matches. Sparse stereograms do so even across large contrast-free regions with no binocular matches. Stereograms that define occluding and occluded surfaces lead to surface percepts wherein partially occluded textured surfaces are completed behind occluding textured surfaces at a spatial scale much larger than that of the texture elements themselves. Earlier models suggest how the brain detects binocular disparity, but not how RDS generate conscious percepts of 3D surfaces. A neural model predicts how the layered circuits of visual cortex generate these 3D surface percepts using interactions between visual boundary and surface representations that obey complementary computational rules.

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One of the first attempts to develop a formal model of depth cue integration is to be found in Maloney and Landy's (1989) "human depth combination rule". They advocate that the combination of depth cues by the visual sysetem is best described by a weighted linear model. The present experiments tested whether the linear combination rule applies to the integration of texture and shading. As would be predicted by a linear combination rule, the weight assigned to the shading cue did vary as a function of its curvature value. However, the weight assigned to the texture cue varied systematically as a function of the curvature value of both cues. Here we descrive a non-linear model which provides a better fit to the data. Redescribing the stimuli in terms of depth rather than curvature reduced the goodness of fit for all models tested. These results support the hypothesis that the locus of cue integration is a curvature map, rather than a depth map. We conclude that the linear comination rule does not generalize to the integration of shading and texture, and that for these cues it is likely that integration occurs after the recovery of surface curvature.