19 resultados para Silicon Bridge


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The element silicon (Si) is not considered an essential nutrient for plant function. Nevertheless, Si is absorbed from soil in large amounts that are several fold higher than those of other essential macronutrients in certain plant species. Its beneficial effects have been reported in various situations, especially under biotic and abiotic stress conditions. The most significant effect of Si on plants, besides improving their fitness in nature and increasing agricultural productivity, is the restriction of parasitism. There has been a considerable amount of research showing the positive effect of Si in controlling diseases in important crops. Rice (Oryza sativa), in particular, is affected by the presence of Si, with diseases such as blast, brown spot and sheath blight becoming more severe on rice plants grown in Si-depleted soils. The hypothesis underlying the control of some diseases in both mono- and di-cots by Si has been confined to that of a mechanical barrier resulting from its polymerization in planta. However, some studies show that Si-mediated resistance against pathogens is associated with the accumulation of phenolics and phytoalexins as well as with the activation of some PR-genes. These findings strongly suggest that Si plays an active role in the resistance of some plants to diseases rather than forming a physical barrier that impedes penetration by fungal pathogens.

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A field experiment conducted with the irrigated rice cultivar BRS Formoso, to assess the efficiency of calcinated serpentinite as a silicon source on grain yield was utilized to study its effect on leaf blast severity and tissue sugar levels. The treatments consisted of five rates of calcinated serpentinite (0, 2, 4, 6, 8 Mg.ha-1) incorporated into the soil prior to planting. The leaf blast severity was reduced at the rate of 2.96% per ton of calcinated serpentinite. The total tissue sugar content decreased significantly as the rates of serpentinite applied increased (R² = 0.83). The relationship between the tissue sugar content and leaf blast severity was linear and positive (R² = 0.81). The decrease in leaf blast severity with increased rates of calcinated serpentinite was also linear (R²= 0.96) and can be ascribed to reduced sugar level.

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This paper discusses the effect of tool wear on surface finish in single-point diamond turning of single crystal silicon. The morphology and topography of the machined surface clearly show the type of cutting edge wear reproduced onto the cutting grooves. Scanning electron microscopy is used in order to correlate the cutting edge damage and microtopography features observed through atomic force microscopy. The possible wear mechanisms affecting tool performance and surface generation during cutting are also discussed. The zero degree rake angle single point diamond tool presented small nicks on the cutting edge. The negative rake angle tools presented more a type of crater wear on the rake face. No wear was detected on flank face of the diamond tools.

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Crack formation and growth in steel bridge structural elements may be due to loading oscillations. The welded elements are liable to internal discontinuities along welded joints and sensible to stress variations. The evaluation of the remaining life of a bridge is needed to make cost-effective decisions regarding inspection, repair, rehabilitation, and replacement. A steel beam model has been proposed to simulate crack openings due to cyclic loads. Two possible alternatives have been considered to model crack propagation, which the initial phase is based on the linear fracture mechanics. Then, the model is extended to take into account the elastoplastic fracture mechanic concepts. The natural frequency changes are directly related to moment of inertia variation and consequently to a reduction in the flexural stiffness of a steel beam. Thus, it is possible to adopt a nondestructive technique during steel bridge inspection to quantify the structure eigenvalue variation that will be used to localize the grown fracture. A damage detection algorithm is developed for the proposed model and the numerical results are compared with the solutions achieved by using another well know computer code.