Politische Ordnungsbildung wider Willen - ein Forschungsprogramm zu transnationalen Konflikten und Institutionen

"In diesem Discussion-paper wird das Forschungsprogramm der Abteilung 'Transnationale Konflikte und internationale Institutionen' (TKI) vorgestellt. Das Forschungsprogramm richtet den Blick auf eine Entwicklungsdynamik, die durch die Errichtung der internationalen Institutionen nach dem Zweiten Weltkrieg ausgelöst wurde und im Ergebnis zu einer politischen Ordnung jenseits des Nationalstaates in einer normativ gehaltvollen Bedeutung führen kann. Im ersten Teil des Papiers werden zunächst die Erfolge und Misserfolge internationaler Institutionen nach dem Zweiten Weltkrieg in den Blick genommen. Darauf aufbauend werden die beiden zentralen Forschungsthesen des Programms entwickelt. Der ersten These zufolge hat die Verlagerung des Regierens auf internationale Institutionen einen nicht intendierten Trend zur Supra- und Transnationalisierung der politischen Steuerung zur Folge. Die zweite These geht davon aus, dass die zunehmende Eingriffstiefe und der Bedeutungszuwachs von trans- und supranationalen Organisationen im Laufe der Zeit zu einer gesellschaftlichen Politisierung und zu Legitimationsproblemen politischer Steuerung jenseits des Nationalstaats führen. Im letzten Teil des Papiers werden schließlich die geplanten und bereits begonnenen Forschungsprojekte vorgestellt, die die beiden Thesen mit unterschiedlicher Schwerpunktsetzung überprüfen. Dabei erheben die einzelnen Projekte nicht den Anspruch, das vorliegende Forschungsprogramm als Ganzes abzubilden. Vielmehr konzentrieren sie sich auf einzelne Aspekte, die jedoch in der Summe empirisch abgestützte Aussagen zu den Kernthesen ermöglichen." (Autorenreferat)"This discussion paper introduces the new program of the research unit, 'Transnational Conflicts and International Institutions' (TKI) at the Social Science Research Center Berlin (WZB). The research program focuses on the developmental dynamics that were initiated with the creation of international institutions following the Second World War and which may lead to the establishment of a new, normatively significant political order beyond the nation-state. The first part of the paper considers the successes and failures of post-World-War-II institutions and, based on these results, develops the two core theses of the program. The first thesis is that the shift of governance and governing to international institutions results in a trend toward the transnationalization or supranationalization of policies, as an unintended side-effect. The second thesis is that the increasing depth of intervention, and the steady accumulation and concentration of power by supranational organizations will, over time, result in the politicizing of society and subsequent problems of legitimacy for forms of governance beyond the nation-state. The final part of the paper discusses the projects that have been initiated in the research unit, or are in the planning stages, each of which analyzes a different aspect of this problem in order to test our main hypotheses. The cumulative research will provide sufficient collective empirical evidence to probe our core theses." (author's abstract

A Multi-Organ Nucleus Segmentation Challenge

Generalized nucleus segmentation techniques can contribute greatly to reducing the time to develop and validate visual biomarkers for new digital pathology datasets. We summarize the results of MoNuSeg 2018 Challenge whose objective was to develop generalizable nuclei segmentation techniques in digital pathology. The challenge was an official satellite event of the MICCAI 2018 conference in which 32 teams with more than 80 participants from geographically diverse institutes participated. Contestants were given a training set with 30 images from seven organs with annotations of 21,623 individual nuclei. A test dataset with 14 images taken from seven organs, including two organs that did not appear in the training set was released without annotations. Entries were evaluated based on average aggregated Jaccard index (AJI) on the test set to prioritize accurate instance segmentation as opposed to mere semantic segmentation. More than half the teams that completed the challenge outperformed a previous baseline. Among the trends observed that contributed to increased accuracy were the use of color normalization as well as heavy data augmentation. Additionally, fully convolutional networks inspired by variants of U-Net, FCN, and Mask-RCNN were popularly used, typically based on ResNet or VGG base architectures. Watershed segmentation on predicted semantic segmentation maps was a popular post-processing strategy. Several of the top techniques compared favorably to an individual human annotator and can be used with confidence for nuclear morphometrics

A multi-organ nucleus segmentation challenge

Generalized nucleus segmentation techniques can contribute greatly to reducing the time to develop and validate visual biomarkers for new digital pathology datasets. We summarize the results of MoNuSeg 2018 Challenge whose objective was to develop generalizable nuclei segmentation techniques in digital pathology. The challenge was an official satellite event of the MICCAI 2018 conference in which 32 teams with more than 80 participants from geographically diverse institutes participated. Contestants were given a training set with 30 images from seven organs with annotations of 21,623 individual nuclei. A test dataset with 14 images taken from seven organs, including two organs that did not appear in the training set was released without annotations. Entries were evaluated based on average aggregated Jaccard index (AJI) on the test set to prioritize accurate instance segmentation as opposed to mere semantic segmentation. More than half the teams that completed the challenge outperformed a previous baseline. Among the trends observed that contributed to increased accuracy were the use of color normalization as well as heavy data augmentation. Additionally, fully convolutional networks inspired by variants of U-Net, FCN, and Mask-RCNN were popularly used, typically based on ResNet or VGG base architectures. Watershed segmentation on predicted semantic segmentation maps was a popular post-processing strategy. Several of the top techniques compared favorably to an individual human annotator and can be used with confidence for nuclear morphometrics