Bone mineral density and singh index predict bone mechanical properties of human femur.

The aim of our study was to assess the predictive value of the Singh index (SI), which estimates bone architecture, and bone density (BMD) when dealing with the mechanical competence of bone and to analze possible differences in bone properties between gender in humans. The relationship between SI, BMD, and mechanical competence was analyzed in 106 bone cylinders from 37 human femoral heads obtained during hip-joint replacement surgery for low energy fracture or for osteoarthritis. Bones from osteoporotic patients are less dense and more brittle compared with bones from osteoarthritic patients, as expected. Among osteoporotic patients female bones were more brittle than those from males, although BMD was similar. In osteoarthritic patients there were no significant differences among sexes. Bone mechanical competence varies according to BMD and to SI categories. Thus, our study suggests that bone strength is predicted by both BMD and bone architecture.

Self-organized-criticality model consistent with statistical properties of edge turbulence in a fusion plasma.

The statistical properties of the intermittent signal generated by a recent model for self-organized criticality are examined. A successful comparison is made with previously published results of the equivalent quantities measured in the electrostatic turbulence at the edge of a fusion plasma. This result reestablishes self-organized criticality as a potential paradigm for transport in magnetic fusion devices, overriding shortcomings pointed out in earlier works [E. Spada, Phys. Rev. Lett. 86, 3032 (2001)10.1103/PhysRevLett.86.3032; V. Antoni, Phys. Rev. Lett. 87, 045001 (2001)10.1103/PhysRevLett.87.045001].

Non-Gaussian probability distribution functions from maximum-entropy-principle considerations.

In this work we develop the recently suggested concept of superstatistics [C. Beck and E.G.D. Cohen, Physica A 322, 267 (2003)], face the problem of devising a viable way for estimating the correct statistics for a system in the absence of sufficient knowledge of its microscopical dynamics, and suggest to solve it through the maximum-entropy principle. As an example, we deduce the probability distribution function for velocity fluctuations in turbulent fluids, which is slightly different from the form suggested by C. Beck [Phys. Rev. Lett. 87, 180601 (2001)].

Multiparameter generalization of nonextensive statistical mechanics.

We show that the stochastic interpretation of Tsallis's thermostatistics given recently by Beck [Phys. Rev. Lett 87, 180601 (2001)] leads naturally to a multiparameter generalization. The resulting class of distributions is able to fit experimental results, which cannot be reproduced within Boltzmann's or Tsallis's formalism.