822 research outputs found

    On fiber dispersion models: exclusion of compressed fibers and spurious model comparisons

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    Fiber dispersion in collagenous soft tissues has an important influence on the mechanical response, and the modeling of the collagen fiber architecture and its mechanics has developed significantly over the last few years. The purpose of this paper is twofold, first to develop a method for excluding compressed fibers within a dispersion for the generalized structure tensor (GST) model, which several times in the literature has been claimed not to be possible, and second to draw attention to several erroneous and misleading statements in the literature concerning the relative values of the GST and the angular integration (AI) models. For the GST model we develop a rather simple method involving a deformation dependent dispersion parameter that allows the mechanical influence of compressed fibers within a dispersion to be excluded. The theory is illustrated by application to simple extension and simple shear in order to highlight the effect of exclusion. By means of two examples we also show that the GST and the AI models have equivalent predictive power, contrary to some claims in the literature. We conclude that from the theoretical point of view neither of these two models is superior to the other. However, as is well known and as we now emphasize, the GST model has proved to be very successful in modeling the data from experiments on a wide range of tissues, and it is easier to analyze and simpler to implement than the AI approach, and the related computational effort is much lower

    Be-implanted (GaAl)As stripe geometry lasers

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    GaAl)As double-heterostructure stripe geometry lasers have been fabricated using Be ion implantation. Pulsed threshold currents as low as 21 mA have been found. The light-vs-current characteristics were kink-free up to 10 mW output power and the measured differential quantum efficiency was 45%

    Biaxial deformation of collagen and elastin fibers in coronary adventitia

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    The microstructural deformation-mechanical loading relation of the blood vessel wall is essential for understanding the overall mechanical behavior of vascular tissue in health and disease. We employed simultaneous mechanical loading-imaging to quantify in situ deformation of individual collagen and elastin fibers on unstained fresh porcine coronary adventitia under a combination of vessel inflation and axial extension loading. Specifically, the specimens were imaged under biaxial loads to study microscopic deformation-loading behavior of fibers in conjunction with morphometric measurements at the zero-stress state. Collagen fibers largely orientate in the longitudinal direction, while elastin fibers have major orientation parallel to collagen, but with additional orientation angles in each sublayer of the adventitia. With an increase of biaxial load, collagen fibers were uniformly stretched to the loading direction, while elastin fibers gradually formed a network in sublayers, which strongly depended on the initial arrangement. The waviness of collagen decreased more rapidly at a circumferential stretch ratio of λθ = 1.0 than at λθ = 1.5, while most collagen became straightened at λθ = 1.8. These microscopic deformations imply that the longitudinally stiffer adventitia is a direct result of initial fiber alignment, and the overall mechanical behavior of the tissue is highly dependent on the corresponding microscopic deformation of fibers. The microstructural deformation-loading relation will serve as a foundation for micromechanical models of the vessel wall

    Cooperating Attackers in Neural Cryptography

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    A new and successful attack strategy in neural cryptography is presented. The neural cryptosystem, based on synchronization of neural networks by mutual learning, has been recently shown to be secure under different attack strategies. The advanced attacker presented here, named the ``Majority-Flipping Attacker'', is the first whose success does not decay with the parameters of the model. This new attacker's outstanding success is due to its using a group of attackers which cooperate throughout the synchronization process, unlike any other attack strategy known. An analytical description of this attack is also presented, and fits the results of simulations
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