Anisotropy of spin relaxation of water protons in cartilage and tendon

Transverse spin relaxation rates of water protons in articular cartilage and tendon depend on the orientation of the tissue relative to the applied static magnetic field. This complicates the interpretation of magnetic resonance images of these tissues. At the same time, relaxation data can provide information about their organisation and microstructure. We present a theoretical analysis of the anisotropy of spin relaxation of water protons observed in fully hydrated cartilage. We demonstrate that the anisotropy of transverse relaxation is due almost entirely to intramolecular dipolar coupling modulated by a specific mode of slow molecular motion: the diffusion of water molecules in the hydration shell of a collagen fibre around the fibre, such that the molecular director remains perpendicular to the fibre. The theoretical anisotropy arising from this mechanism follows the “magic-angle” dependence observed in magnetic-resonance measurements of cartilage and tendon and is in good agreement with the available experimental results. We discuss the implications of the theoretical findings for MRI of ordered collagenous tissues.

Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors

Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.

Eco-structure data forms : classification of data analysis using perceived design affordances for musical outcomes

This paper explores a method of comparative analysis and classification of data through perceived design affordances. Included is discussion about the musical potential of data forms that are derived through eco-structural analysis of musical features inherent in audio recordings of natural sounds. A system of classification of these forms is proposed based on their structural contours. The classifications include four primitive types; steady, iterative, unstable and impulse. The classification extends previous taxonomies used to describe the gestural morphology of sound. The methods presented are used to provide compositional support for eco-structuralism.