University of Bremen

About: University of Bremen is a education organization based out in Bremen, Germany. It is known for research contribution in the topics: Population & Glacial period. The organization has 14563 authors who have published 37279 publications receiving 970381 citations. The organization is also known as: Universität Bremen.

Automatic liver tumor segmentation in CT with fully convolutional neural networks and object-based postprocessing

Abstract: Automatic liver tumor segmentation would have a big impact on liver therapy planning procedures and follow-up assessment, thanks to standardization and incorporation of full volumetric information. In this work, we develop a fully automatic method for liver tumor segmentation in CT images based on a 2D fully convolutional neural network with an object-based postprocessing step. We describe our experiments on the LiTS challenge training data set and evaluate segmentation and detection performance. Our proposed design cascading two models working on voxel- and object-level allowed for a significant reduction of false positive findings by 85% when compared with the raw neural network output. In comparison with the human performance, our approach achieves a similar segmentation quality for detected tumors (mean Dice 0.69 vs. 0.72), but is inferior in the detection performance (recall 63% vs. 92%). Finally, we describe how we participated in the LiTS challenge and achieved state-of-the-art performance.

Real limits in the virtual world: self-limiting behavior of Internet gamblers.

Abstract: The recent expansion of Internet gambling has stimulated debate, policy, and research on this relatively new phenomenon and its potential consequences. The current study focuses on bettors experiencing problems by sampling Internet gamblers who imposed limits on the amount they were allowed to deposit to a betting site. We analyzed the betting transactions over 18 months of all gamblers who subscribed to an online betting site in February, 2005 (N = 47,134), 567 of whom utilized the site's self-limit feature. Self-limiting gamblers played a wider variety of games and placed more bets than others prior to imposing limits. After imposing limits, self-limiters reduced their activity, but did not reduce the amount they wagered per bet. Time spent gambling, not just money spent, appears to be an important indicator of gambling problems. Self-limit programs appear to be promising options for Internet gamblers at-risk for gambling problems.

Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm

Abstract: . Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO2 ( X CO 2 ) for the roughly 100 000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25 %, is required in order to accurately infer carbon sources and sinks from X CO 2 , significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20 % over land and 40 % over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO2 data record continues to expand.

Effects of ice coverage and ice-rafted material on sedimentation in the fram strait

Abstract: As little is known about pelagic sedimentation processes in Arctic environments1, the interpretation of biological and chemical processes, as well as the reconstruction of ancient conditions, including those in the glacial North Atlantic, is difficult. Here we provide sediment-trap results, which show that the position of the sea-ice boundary significantly influences the particle flux. The seasonal variability of the particle flux differed markedly in the various sediment-trap sites in Fram Strait, depending on the behaviour of the sea ice. Under complete ice cover, sedimentation is very low, whereas maximum sedimentation is found at the ice margin. The highest particle flux observed, showing a large lithogenic component, was observed at the ice edge where the water was warmer (>2 °C). We find that high biogenic opal fluxes are characteristic of the summer ice margin, indicating that the sedimentary record of opal fluxes may allow the position of ice margins in the past to be reconstructed.