Cumulative Index

Diffuse liver disease is a growing problem and a major cause of death worldwide. In the final stages the treatment often involves liver resection or transplant and in deciding what course of action is to be taken it is crucial to have a correct assessment of the function of the liver. The current “gold standard” for this assessment is to take a liver biopsy which has a number of disadvantages. As an alternative, a method involving magnetic resonance imaging and mechanistic modeling of the liver has been developed at Linköping University. One of the obstacles for this method to overcome in order to reach clinical implementation is the speed of the parameter estimation. In this project the methodology of metamodeling is tested as a possible solution to this speed problem. Metamodeling involve making models of models using extensive model simulations and mathematical tools. With the use of regression methods, clustering algorithms, and optimization, different methods for parameter estimation have been evaluated. The results show that several, but not all, of the parameters could be accurately estimated using metamodeling and that metamodeling could be a highly useful tool when modeling biological systems. With further development, metamodeling could bring this non-invasive method for estimation of liver function a major step closer to application in the clinic

Pennygången. 12 familjer 36 vänskaper

The residential area Pennygången in Gothenburg is planned to be restored in a very expensive way. As a consequence the rents will increase dramatically and about 80% of the people living there today will have to move. Excisting social networks might be disrupted. The aim of this project is to illustrate a part of the present social network at Pennygången in the form of a photobook. I have photographed 12 families in their homes. These families know each other in 36 different ways. The final photobook illustrates all these friendships by presenting the families knowing each other in pairs

Metamodeling for ultra-fast parameter estimation : Theory and evaluation of use in real-time diagnosis of diffuse liver disease

Diffuse liver disease is a growing problem and a major cause of death worldwide. In the final stages the treatment often involves liver resection or transplant and in deciding what course of action is to be taken it is crucial to have a correct assessment of the function of the liver. The current “gold standard” for this assessment is to take a liver biopsy which has a number of disadvantages. As an alternative, a method involving magnetic resonance imaging and mechanistic modeling of the liver has been developed at Linköping University. One of the obstacles for this method to overcome in order to reach clinical implementation is the speed of the parameter estimation. In this project the methodology of metamodeling is tested as a possible solution to this speed problem. Metamodeling involve making models of models using extensive model simulations and mathematical tools. With the use of regression methods, clustering algorithms, and optimization, different methods for parameter estimation have been evaluated. The results show that several, but not all, of the parameters could be accurately estimated using metamodeling and that metamodeling could be a highly useful tool when modeling biological systems. With further development, metamodeling could bring this non-invasive method for estimation of liver function a major step closer to application in the clinic

The land-surface scheme of the Rossby Centre regional atmospheric climate model (RCA3)

This report describes the physical processes as part of the Land-Surface Scheme (LSS) in the Rossby Centre Regional Atmospheric Climate Model (RCA3). The LSS is a tiled scheme with the three main tiles with respect to temperature: forest, open land, and snow. The open land tile is divided into a vegetated and a bare soil part for latent heat flux calculations. The individual fluxes of heat and momentum from these tiles are weighted in order to obtain grid-averaged values at the lowest atmospheric model level according to the fractional areas of the tiles. The forest tile is internally divided into three sub-tiles: forest canopy, forest floor soil, and snow on forest floor. All together this gives three to five different surface energy balances depending on if snow is present or not.The soil is divided into five layers with respect to temperature, with a no-flux boundary condition at three meters depth, and into two layers with respect to soil moisture, with a maximum depth of just above 2.2 meters. Runoff generated at the bottom of the deep soil layer may be used as input to a routing scheme.In addition to the soil moisture storages there are six more water storages in the LSS: interception of water on open land vegetation and on forest canopy, snow water equivalent of open land and forest snow, and liquid water content in both snow storages.Diagnostic variables of temperature and humidity at 2m and wind at 10m are calculated individually for each tile

An energy balance model for prediction of surface temperatures

From the winter season 1988/89 and onwards an energy balance model has been used to estimate surface temperatures within a weather seivice system for the road authorities in "Östergötlands" and "Göteborg-Bohuslän" in Sweden. It is based on a simplified form of the energy balance equation at the surface and a numerical model with ten layers in the ground or road. In the road seivice system manually given forecasts of clouds and wind are used as input into the model. The initial values of surface temperatures are obtained on-line from the road stations involved. Forecasts of surface temperatures have been made for up to five hours and give significantly better results than e.g. perstistency or linear trend forecasts. The model has also been generalized to run directly on model output clouds an winds and to give forecasts for a large area. As starting values we then use screen temperatures analysed in a grid net with a resolution of about 20 km covering Scandinavia. Initial surface temperatures are obtained through extrapolation to the ground. Through a relaxation formula forecasted surface temperatures are then transformed back to screen level. The temperature forecasts obtained in this way seem to be much better than the LAM-model gives where the daily amplitude is too small. This latter model is henceforth called the objective system while the former is called the road seivice system. The two aystems have large parts in common. Differing parts are indicated in section headings ant text

Mesan, an operational mesoscale analysis system

A system for mesoscale analyses of selected variables has been developed. The analysed parameters are of general interest in operational weather forecasting, but normally not available from NWP systems, or available, but with a significantly lower quality than achieved by the mesoscale analysis system. A supplementary objective is to produce initial information to be used for now-casting techniques. Examples of parameters are precipitation, temperature, humidity, visibility, wind and clouds. The basis of the analysis system is the optimal interpolation technique (OI). The use of observations from automatic stations, radars and satellites have been investigated. The investigation indicates that a dense network of ordinary precipitation gauge measurements can produce more accurate analyses than more elaborate systems like radar that suffers from anomalous echoes and other errors