Methods of studying the planar distribution of objects in histological sections of brain tissue

This article reviews the statistical methods that have been used to study the planar distribution, and especially clustering, of objects in histological sections of brain tissue. The objective of these studies is usually quantitative description, comparison between patients or correlation between histological features. Objects of interest such as neurones, glial cells, blood vessels or pathological features such as protein deposits appear as sectional profiles in a two-dimensional section. These objects may not be randomly distributed within the section but exhibit a spatial pattern, a departure from randomness either towards regularity or clustering. The methods described include simple tests of whether the planar distribution of a histological feature departs significantly from randomness using randomized points, lines or sample fields and more complex methods that employ grids or transects of contiguous fields, and which can detect the intensity of aggregation and the sizes, distribution and spacing of clusters. The usefulness of these methods in understanding the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Creutzfeldt-Jakob disease is discussed. © 2006 The Royal Microscopical Society.

Dynamic network rating for low carbon distribution network operation:a U.K. application

Dynamic asset rating (DAR) is one of the number of techniques that could be used to facilitate low carbon electricity network operation. Previous work has looked at this technique from an asset perspective. This paper focuses, instead, from a network perspective by proposing a dynamic network rating (DNR) approach. The models available for use with DAR are discussed and compared using measured load and weather data from a trial network area within Milton Keynes in the central area of the U.K. This paper then uses the most appropriate model to investigate, through a network case study, the potential gains in dynamic rating compared to static rating for the different network assets - transformers, overhead lines, and cables. This will inform the network operator of the potential DNR gains on an 11-kV network with all assets present and highlight the limiting assets within each season.

Weather forecasting to predict practical dynamic asset rating of overhead lines

This paper describes the potential of pre-setting 11kV overhead line ratings over a time period of sufficient length to be useful to the real-time management of overhead lines. This forecast is based on short and long term freely available weather forecasts and is used to help investigate the potential for realising dynamic rating benefits on the electricity network. A comparison between the realisable benefits in ratings using this forecast data, over the period of a year has been undertaken.