Automated image analysis has been applied to scanning electron micrographs (transmission mode; STEM) of metallic nanoparticles (silver and gold; about 10 nm to 20 nm). For a reliable particle identification, scanning electron microscopic images must be recorded with distinct contrast and resolution parameters. The particles were separated from the background and classified according to shape and size by machine learning (machine learning). Training images were created with model particles cut out of real electron microscopic images. The automated analysis of the particle size (expressed as area) was well possible, but overlapping particles could not be safely separated. The assignment of particle to six different shape classes (sphere, triangle, square, pentagon, hexagon, rod) by automated analysis was difficult. The fact that real particles never have an ideal geometrical shape but are always distorted or have rough edges or cropped tips is the fundamental reason of this problem. This effect also occurred with human image evaluators and poses a considerable obstacle in the training process for machine learning. Image analysis by machine learning techniques is difficult if different human evaluators disagree on the shape assignment of given particles because a proper training cannot be provided.

Particles depicted in scanning electron micrographs are automatically identified and classified according to size and shape with a deep-learning algorithm. The procedure works for both SE images and STEM images.

Particle assemblies created by software package Blender are converted into artificial scanning electron micrographs (SEM) with a generative adversarial network (GAN). The introduction of height maps (i.e., surface topography or relief structure) considerably enhances the quality of the artificial SEM images by providing 3D information on the input data. These artificial images serve as input data to train a convolutional neural network (CNN) to identify and classify nanoparticles. Although the performance of the CNN trained with artificial SEM images is slightly inferior to the same CNN trained with real SEM images, this offers a pathway to create training data for segmentation and classification networks for SEM image analysis by deep learning algorithms.

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strength of structural coupling that exists between the economic system on one hand and the legal and political systems on the other, at both the EU and the global levels.Given the rhetoric that exists within the EU in relation to the social dimension (without, of course, forgetting the undoubted historical successes in this sphere), these findings make for uncomfortable reading. But they are the persuasive outcome of what we might call the thoroughgoing second-order observation that characterises Hartzén's work; that is, the concern to focus the attention of the research on observing how other systems observe. There is no claim of a privileged access to reality, no denial of the inevitable division of the unmarked space according to the binary code of the research project. But there is the production of a different and, this reviewer would contend, a more adequately complex map of the landscape, which reveals different features as being more important than might otherwise have been appreciated.At various points in this book, it is clear that Hartzén situates her work squarely in a post-financial crisis world, with all that that extraordinary event appeared to imply for the economic and the social in the still-new century. In the relatively short period since the book was published, it is surely fair to say that the financial crisis as an overarching concern has given way to a new set of worries (some, of course, no doubt generated by or further enhanced by it). Not least in Europe we now worry, with good cause, about fracture, the crisis of traditional politics and the re-emergence of populism. In this setting, far from being overtaken by events, Hartzén's book has only become even more relevant. If the European project is to survive, it is surely going to have to demonstrate its relevance to every citizen more clearly than it has heretofore managed to do. In this regard, a counterbalance to the economic imperatives in the shape of a functioning social institution would play an important role.The European Social Dialogue in Perspective does not, of course, have all the answers, but it is an important and richly argued contribution to the wider and now urgent conversation. If all the participants in that effort display the rigour, insight and balance of Hartzén, then there is every reason to be hopeful.