Flow cytometric method to measure urea-resistant alkaline phosphatase from blood neutrophils for use in the prenatal screening of Down's syndrome

The histochemical measurement of urea-resistant alkaline phosphatase from maternal blood neutrophils is known to have a high detection rate for the prenatal detection of Down's syndrome pregnancies. However, because the histochemical method is laborious and subjective to use, it has not gained widespread acceptance in prenatal screening programmes. We present a simple and objective method for the measurement of urea-resistant alkaline phosphatase by flow cytometry. The method should allow the design of larger studies aimed at evaluating the role of neutrophil urea-resistant alkaline phosphatase in the prenatal screening for Down's syndrome.     

Transport of particulate matter in natural waters — modelling and in situ-measurements

The significant processes controlling the fate of particulates are convection an dispersion on one hand, and sedimentation on the other hand. Due to inteparticulated reactions, larger aggregates can be formed from smaller units thus changing the sedimentation characteristics. These phenomena are summarized in a mathematical model whereby hydrodynamic effects as well as the control mechanisms of the dissolved phase are included. A relationship was derived on the basis of energy considerations leading to the formulation of a critical sedimentation velocity of the suspensa, which determines the transport capacity of the flowing system. The sedimentation term is calculated from the above discussed transport capacity, hydro-dynamic parameters and suspending media properties. Aggregation effects are taken into account as an increase of sedimentation velocities of the particles. The equations are solved in a particular computational routine such that the horizontal distribution of suspended solids in a natural system can be describe as function of the above discussed phenomena. The model was tested with in situ-measurements. It was found that the observed processes are described satisfactorily by this model.     

Using digital image projections to visualize forest landscape changes due to management activities and forest growth

A pedagogic problem in forestry and landscape management is to visualize future landscape effects of forest growth and current management activities in the forest. This paper presents a method for forecasting digital image projections of forest landscape dynamics. Static nonlinear regression functions estimate the digital numbers in a Landsat Thematic Mapper image. Regressors used are forest stand variables. By estimating the future forest stand data, based on intermediate treatment and growth, future satellite digital images are created. In a case study example, the future landscape of a forest block in the province of Västernorrland, Sweden, is projected to demonstrate the application of this visualization technique.