Electroplating of Ni-Cr on steel with pulse plating

It has been difficult to electrolytically obtain crack- free chromium plating because of the high stresses caused by several factors. Accordingly, electroplating of nickel- chromium also encounters a similar problem. Cracks in chromium- containing plating was ascribed, in a certain sense, to the formation of a hydride formed through hydrogen adsorption from the electrolyte. A periodical pulse reverse plating current would enhance the release of hydrogen and hence the elimination of cracking. The present work describes a successful process for obtaining crack- free nickel- chromium plating and the effects of experimental variables on plating compositions.     

Segmentation of virus particle candidates in transmission electron microscopy images

In this paper, we present an automatic segmentation method that detects virus particles of various shapes in transmission electron microscopy images. The method is based on a statistical analysis of local neighbourhoods of all the pixels in the image followed by an object width discrimination and finally, for elongated objects, a border refinement step. It requires only one input parameter, the approximate width of the virus particles searched for. The proposed method is evaluated on a large number of viruses. It successfully segments viruses regardless of shape, from polyhedral to highly pleomorphic.     

Recycling and regeneration of used perfluorosulfonic membranes for polymer electrolyte fuel cells

This paper describes a method for the recycling and regeneration of used perfluorosulfonic Nafion^® (Dupont) membranes by dissolution and recasting. The dissolution of the used Nafion^® membranes from polymer electrolyte fuel cells is realized using dimethyl sulfoxide as a solvent under atmospheric pressure and 190 °C. A mechanically robust membrane can be reproduced by a recast process of the dissolved Nafion^® solution at 170 °C. The recycled membrane has shown a good crystalline structure and high mechanical strength. Membrane properties, including water uptake, exchange capacity and resistance are similar to that of the as-received Nafion^® 115 membrane. Fuel cells prepared by the recycled membrane demonstrate a comparable performance to that of the fresh fuel cell.     

Gradient based intensity normalization

Intensity normalization is important in quantitative image analysis, especially when extracting features based on intensity. In automated microscopy, particularly in large cellular screening experiments, each image contains objects of similar type (e.g. cells) but the object density (number and size of the objects) may vary markedly from image to image. Standard intensity normalization methods, such as matching the grey-value histogram of an image to a target histogram from, i.e. a reference image, only work well if both object type and object density are similar in the images to be matched. This is typically not the case in cellular screening and many other types of images where object type varies little from image to image, but object density may vary dramatically. In this paper, we propose an improved form of intensity normalization which uses grey-value as well as gradient information. This method is very robust to differences in object density. We compare and contrast our method with standard histogram normalization across a range of image types, and show that the modified procedure performs much better when object density varies between images.     

Combining intensity, edge and shape information for 2D and 3D segmentation of cell nuclei in tissue sections

We present a region‐based segmentation method in which seeds representing both object and background pixels are created by combining morphological filtering of both the original image and the gradient magnitude of the image. The seeds are then used as starting points for watershed segmentation of the gradient magnitude image. The fully automatic seeding is done in a generous fashion, so that at least one seed will be set in each foreground object. If more than one seed is placed in a single object, the watershed segmentation will lead to an initial over‐segmentation, i.e. a boundary is created where there is no strong edge. Thus, the result of the initial segmentation is further refined by merging based on the gradient magnitude along the boundary separating neighbouring objects. This step also makes it easy to remove objects with poor contrast. As a final step, clusters of nuclei are separated, based on the shape of the cluster. The number of input parameters to the full segmentation procedure is only five. These parameters can be set manually using a test image and thereafter be used on a large number of images created under similar imaging conditions. This automated system was verified by comparison with manual counts from the same image fields. About 90% correct segmentation was achieved for two‐ as well as three‐dimensional images.