Core stability exercise in chronic low back pain

Exercise is commonly used in the management of chronic musculoskeletal conditions, including chronic low back pain (CLBP). The focus of exercise is varied and may include parameters ranging from strength and endurance training, to specific training of muscle coordination and control. The assumption underpinning these approaches is that improved neuromuscular function will restore or augment the control and support of the spine and pelvis. In a biomechanical model of CLBP, which assumes that pain recurrence is caused by repeated mechanical irritation of pain sensitive structures [1], it is proposed that this improved control and stability would reduce mechanical irritation and lead to pain relief [1]. Although this model provides explanation for the chronicity of LBP, perpetuation of pain is more complex, and contemporary neuroscience holds the view that chronic pain is mediated by a range of changes including both peripheral (eg, peripheral sensitization) and central neuroplastic changes [2]. Although this does not exclude the role of improved control of the lumbar spine and pelvis in management of CLBP, particularly when there is peripheral sensitization, it highlights the need to look beyond outdated simplistic models. One factor that this information highlights is that the refinement of control and coordination may be more important than simple strength and endurance training for the trunk muscles. The objective of this article is to discuss the rationale for core stability exercise in the management of CLBP, to consider critical factors for its implementation, and to review evidence for efficacy of the approach.

Stability criteria for unsupervised temporal association networks

A biologically realizable, unsupervised learning rule is described for the online extraction of object features, suitable for solving a range of object recognition tasks. Alterations to the basic learning rule are proposed which allow the rule to better suit the parameters of a given input space. One negative consequence of such modifications is the potential for learning instability. The criteria for such instability are modeled using digital filtering techniques and predicted regions of stability and instability tested. The result is a family of learning rules which can be tailored to the specific environment, improving both convergence times and accuracy over the standard learning rule, while simultaneously insuring learning stability.

Structure and thermal stability of Langmuir-Blodgett films of barium arachidate

The structures of multilayer Langmuir-Blodgett films of barium arachidate before and after heat treatment have been investigated using both atomic force microscopy (AFM) and grazing incidence synchrotron X-ray diffraction (GIXD). AFM gave information on surface morphology at molecular resolution while GIXD provided quantitative details of the lattice structures of the films with their crystal symmetries and lattice constants. As-prepared films contained three coexisting structures: two triclinic structures with the molecularchains tilted by about 20degrees from the film normal and with 3 x 1 or 2 x 2 super-lattice features arising from height modulation of the molecules in the films; a rectangular structure with molecules perpendicular to the film surface. Of these, the 3 x 1 structure is dominant with a loose correlation between the bilayers. In the film plane both superstructures are commensurate with the local structures, having different oblique symmetries. The lattice constants for the 3 x 1 structure are a(s) = 3a = 13.86 Angstrom, b(s) = b = 4.31 Angstrom and gamma(s) = gamma = 82.7degrees; for the 2 x 2 structure a(s) = 2a = 16.54 Angstrom, b(s) = 2b = 9.67 Angstrom, gamma(s) = gamma = 88degrees. For the rectangular structure the lattice constants are a = 7.39 Angstrom, b = 4.96 Angstrom and gamma = 90degrees. After annealing, the 2 x 2 and rectangular structures were not observed, while the 3 x 1 structure had developed over the entire film. For the annealed films the correlation length in the film plane is about twice that in the unheated films, and in the out-of-plane direction covers two bilayers. The above lattice parameters, determined by GIXD, differed significantly from the values obtained by AFM, due possibly to distortion of the films by the scanning action of the AFM tip. (C) 2004 Published by Elsevier B.V.

Power system sensitivity analysis for probabilistic small signal stability assessment in a deregulated environment

Deregulations and market practices in power industry have brought great challenges to the system planning area. In particular, they introduce a variety of uncertainties to system planning. New techniques are required to cope with such uncertainties. As a promising approach, probabilistic methods are attracting more and more attentions by system planners. In small signal stability analysis, generation control parameters play an important role in determining the stability margin. The objective of this paper is to investigate power system state matrix sensitivity characteristics with respect to system parameter uncertainties with analytical and numerical approaches and to identify those parameters have great impact on system eigenvalues, therefore, the system stability properties. Those identified parameter variations need to be investigated with priority. The results can be used to help Regional Transmission Organizations (RTOs) and Independent System Operators (ISOs) perform planning studies under the open access environment.

Stability for parametric implicit vector equilibrium problems

In this paper, we consider a class of parametric implicit vector equilibrium problems in Hausdorff topological vector spaces where a mapping f and a set K are perturbed by parameters is an element of and lambda respectively. We establish sufficient conditions for the upper semicontinuity and lower semicontinuity of the solution set mapping S : Lambda(1) x A(2) -> 2(X) for such parametric implicit vector equilibrium problems. (c) 2005 Elsevier Ltd. All rights reserved.

Eigenvalue sensitivity analysis for probabilistic small signal stability assessment

This paper presents a method to analyze the first order eigenvalue sensitivity with respect to the operating parameters of a power system. The method is based on explicitly expressing the system state matrix into sub-matrices. The eigenvalue sensitivity is calculated based on the explicitly formed system state matrix. The 4th order generator model and 4th order exciter system model are used to form the system state matrix. A case study using New England 10-machine 39-bus system is provided to demonstrate the effectiveness of the proposed method. This method can be applied into large scale power system eigenvalue sensitivity with respect to operating parameters.