967 resultados para shearless curves


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© 2014 AIP Publishing LLC. Superparamagnetic nanoparticles are employed in a broad range of applications that demand detailed magnetic characterization for superior performance, e.g., in drug delivery or cancer treatment. Magnetic hysteresis measurements provide information on saturation magnetization and coercive force for bulk material but can be equivocal for particles having a broad size distribution. Here, first-order reversal curves (FORCs) are used to evaluate the effective magnetic particle size and interaction between equally sized magnetic iron oxide (Fe2O3) nanoparticles with three different morphologies: (i) pure Fe2O3, (ii) Janus-like, and (iii) core/shell Fe2O3/SiO2synthesized using flame technology. By characterizing the distribution in coercive force and interaction field from the FORC diagrams, we find that the presence of SiO2in the core/shell structures significantly reduces the average coercive force in comparison to the Janus-like Fe2O3/SiO2and pure Fe2O3particles. This is attributed to the reduction in the dipolar interaction between particles, which in turn reduces the effective magnetic particle size. Hence, FORC analysis allows for a finer distinction between equally sized Fe2O3particles with similar magnetic hysteresis curves that can significantly influence the final nanoparticle performance.

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In this paper, we propose the dynamic P-V curve for modulator and P-I curve for laser diode, and present a simple approach to deriving the curves from the small-signal frequency responses measured using a microwave network analyzer. The linear response range, modulation efficiency, optimal driving conditions at different frequency can, therefore, be determined. It is demonstrated that the large-signal performance of electro-absorption (EA) modulator and the directly modulated semiconductor lasers can be predicted from the dynamic curved surface. Experiments show a good agreement between the evaluated characteristics and the measured large-signal performance.

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Following the idea of Xing et al., we investigate a general method for constructing families of pseudorandom sequences with low correlation and large linear complexity from elliptic curves over finite fields in this correspondence. With the help of the tool of exponential sums on elliptic curves, we study their periods, linear complexities, linear complexity profiles, distributions of r-patterns, periodic correlation, partial period distributions, and aperiodic correlation in detail. The results show that they have nice randomness.

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The transport processes of components in capillary electrochromatographic column was investigated based on the basic model of relaxation theory. A principal transport equation of chromatographic relaxation theory was established and mathematical expressions for eluting curves were obtained under the situations of both capillary electrophoresis and chromatography. Characteristics of peak symmetry and its effecting factors are discussed. Tailing peaks, symmetrical peaks and fronting peaks would be observed simultaneously, which was further proved with reversed capillary electrochromatographic experiments.

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This paper studies the radiation properties of the immiscible blend of nylon1010 and HIPS. The gel fraction increased with increasing radiation dose. The network was found mostly in nylon1010, the networks were also found in both nylon1010 and HIPS when the dose reaches 0.85 MGy or more. We used the Charleby-Pinner equation and the modified Zhang-Sun-Qian equation to simulate the relationship with the dose and the sol fraction. The latter equation fits well with these polymer blends and the relationship used by it showed better linearity than the one by the Charleby-Pinner equation. We also studied the conditions of formation of the network by the mathematical expectation theorem for the binary system. Thermal properties of polymer blend were observed by DSC curves. The crystallization temperature decreases with increasing dose because the cross-linking reaction inhibited the crystallization procession and destroyed the crystals. The melting temperature also reduced with increasing radiation dose. The dual melting peak gradually shifted to single peak and the high melting peak disappeared at high radiation dose. However, the radiation-induced crystallization was observed by the heat of fusion increasing at low radiation dose. On the other hand, the crystal will be damaged by radiation. A similar conclusion may be drawn by the DSC traces when the polymer blends were crystallized. When the radiation dose increases, the heat of fusion reduces dramatically and so does the heat of crystallization. (C) 1999 Elsevier Science Ltd. All rights reserved.

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The Saliency Network proposed by Shashua and Ullman is a well-known approach to the problem of extracting salient curves from images while performing gap completion. This paper analyzes the Saliency Network. The Saliency Network is attractive for several reasons. First, the network generally prefers long and smooth curves over short or wiggly ones. While computing saliencies, the network also fills in gaps with smooth completions and tolerates noise. Finally, the network is locally connected, and its size is proportional to the size of the image. Nevertheless, our analysis reveals certain weaknesses with the method. In particular, we show cases in which the most salient element does not lie on the perceptually most salient curve. Furthermore, in some cases the saliency measure changes its preferences when curves are scaled uniformly. Also, we show that for certain fragmented curves the measure prefers large gaps over a few small gaps of the same total size. In addition, we analyze the time complexity required by the method. We show that the number of steps required for convergence in serial implementations is quadratic in the size of the network, and in parallel implementations is linear in the size of the network. We discuss problems due to coarse sampling of the range of possible orientations. We show that with proper sampling the complexity of the network becomes cubic in the size of the network. Finally, we consider the possibility of using the Saliency Network for grouping. We show that the Saliency Network recovers the most salient curve efficiently, but it has problems with identifying any salient curve other than the most salient one.

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In practice, piles are most often modelled as "Beams on Non-Linear Winkler Foundation" (also known as “p-y spring” approach) where the soil is idealised as p-y springs. These p-y springs are obtained through semi-empirical approach using element test results of the soil. For liquefied soil, a reduction factor (often termed as p-multiplier approach) is applied on a standard p-y curve for the non-liquefied condition to obtain the p-y curve liquefied soil condition. This paper presents a methodology to obtain p-y curves for liquefied soil based on element testing of liquefied soil considering physically plausible mechanisms. Validation of the proposed p-y curves is carried out through the back analysis of physical model tests.

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Given M(r; f) =maxjzj=r (jf(z)j) , curves belonging to the set of points M = fz : jf(z)j = M(jzj; f)g were de�ned by Hardy to be maximum curves. Clunie asked the question as to whether the set M could also contain isolated points. This paper shows that maximum curves consist of analytic arcs and determines a necessary condition for such curves to intersect. Given two entire functions f1(z) and f2(z), if the maximum curve of f1(z) is the real axis, conditions are found so that the real axis is also a maximum curve for the product function f1(z)f2(z). By means of these results an entire function of in�nite order is constructed for which the set M has an in�nite number of isolated points. A polynomial is also constructed with an isolated point.

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