Joint mobility was assessed in each member of an epidemiological sample of 96 girls and 97 boys, 17 years old, and graded by means of the hypermobility score of Beighton et al. Twenty two per cent of the girls and 3% of the boys could perform five or more of the nine manoeuvres. The prevalence of symptoms and signs of internal derangement in the temporomandibular joint was higher in adolescents...

Articular cartilage covers the end of bones in joints and determines the load-bearing characteristics and mobility of joints. It has a thin, smooth, low friction surface with a remarkable resiliency to compressive forces. In general, chondrocytes occupy lacunae in the matrix, and produce cartilaginous ECM (extracellular matrix), which consists of type II collagen (13%), proteoglycans (7%), and ...

This paper describes an advanced simulation environment that has been used to examine, validate, and predict the performance of Protocols for IP Mobility Support. It overcomes many limitations found in existing network simulators, and it provides more support on mobile-related issues. It contains several components that are common to all evaluations of IP mobility, which can model arbitrary net...

In this paper, we investigate the growth of solutions of the differential equation f (k) +Ak−1 (z) f (k−1) + · · ·+A1 (z) f ′ +A0 (z) f = F, where A0 (z) , . . . , Ak−1 (z) , F (z) / ≡ 0 are entire functions, and we obtain general estimates of the hyper-exponent of convergence of distinct zeros and the hyper-order of solutions for the above equation.

In this paper we introduce a two phase hyper-heuristic search method for solving the Eternity II puzzle. Eternity II is a challenging money prized edge matching puzzle. Solving the puzzle has been shown to be NP-complete [2]. Hyper-heuristics [1] are a recent trend in heuristic algorithms. They tend to be more general methods than meta-heuristics for solving optimization problems. Hyper-heurist...

Hyper-parameter tuning is one of the crucial steps in the successful application of machine learning algorithms to real data. In general, the tuning process is modeled as an optimization problem for which several methods have been proposed. For complex algorithms, the evaluation of a hyper-parameter configuration is expensive and their runtime is speed up through data sampling. In this paper, t...