Relative performance of mutual information estimation methods for quantifying the dependence among short and noisy data.

Commonly used dependence measures, such as linear correlation, cross-correlogram, or Kendall's tau , cannot capture the complete dependence structure in data unless the structure is restricted to linear, periodic, or monotonic. Mutual information (MI) has been frequently utilized for capturing the complete dependence structure including nonlinear dependence. Recently, several methods have been proposed for the MI estimation, such as kernel density estimators (KDEs), k -nearest neighbors (KNNs), Edgeworth approximation of differential entropy, and adaptive partitioning of the XY plane.

Stress Reduction in Adjacent Level Discs via Dynamic Instrumentation: A Finite Element Analysis.

Background: Conventional (rigid) fusion instrumentation is believed to accelerate the degeneration of adjacent discs by increasing stresses caused by motion discontinuity. Fusion instrumentation that employs reduced rod stiffness and increased axial motion, or dynamic instrumentation, may partially alleviate this problem, but the effects of this instrumentation on the stresses in the adjacent disc are unknown. We used a finiteelement model to calculate and compare the stresses in the adjacent-level disc that are induced by rigid and dynamic posterior lumbar fusion instrumentation.