Fatal lymphoproliferation and acute monocytic leukemia-like disease following infectious mononucleosis in the elderly

Three elderly patients are reported, in whom serologically confirmed recent infectious mononucleosis is followed by fatal lymphoproliferation (case 1), by acute monocytic leukemia (case 2), and by acute probably monocytic leukemia (case 3)

Three strongly correlated charged bosons in a one-dimensional harmonic trap: natural orbital occupancies

We study a one-dimensional system composed of three charged bosons confined in an external harmonic potential. More precisely, we investigate the ground-state correlation properties of the system, paying particular attention to the strong-interaction limit. We explain for the first time the nature of the degeneracies appearing in this limit in the spectrum of the reduced density matrix. An explicit representation of the asymptotic natural orbitals and their occupancies is given in terms of some integral equations.Comment: 6 pages, 4 figures, To appear in European Physical Journal

Bose-Hubbard model with occupation dependent parameters

We study the ground-state properties of ultracold bosons in an optical lattice in the regime of strong interactions. The system is described by a non-standard Bose-Hubbard model with both occupation-dependent tunneling and on-site interaction. We find that for sufficiently strong coupling the system features a phase-transition from a Mott insulator with one particle per site to a superfluid of spatially extended particle pairs living on top of the Mott background -- instead of the usual transition to a superfluid of single particles/holes. Increasing the interaction further, a superfluid of particle pairs localized on a single site (rather than being extended) on top of the Mott background appears. This happens at the same interaction strength where the Mott-insulator phase with 2 particles per site is destroyed completely by particle-hole fluctuations for arbitrarily small tunneling. In another regime, characterized by weak interaction, but high occupation numbers, we observe a dynamical instability in the superfluid excitation spectrum. The new ground state is a superfluid, forming a 2D slab, localized along one spatial direction that is spontaneously chosen.Comment: 16 pages, 4 figure

Feasibility of Inconspicuous GAN-generated Adversarial Patches against Object Detection

Standard approaches for adversarial patch generation lead to noisy conspicuous patterns, which are easily recognizable by humans. Recent research has proposed several approaches to generate naturalistic patches using generative adversarial networks (GANs), yet only a few of them were evaluated on the object detection use case. Moreover, the state of the art mostly focuses on suppressing a single large bounding box in input by overlapping it with the patch directly. Suppressing objects near the patch is a different, more complex task. In this work, we have evaluated the existing approaches to generate inconspicuous patches. We have adapted methods, originally developed for different computer vision tasks, to the object detection use case with YOLOv3 and the COCO dataset. We have evaluated two approaches to generate naturalistic patches: by incorporating patch generation into the GAN training process and by using the pretrained GAN. For both cases, we have assessed a trade-off between performance and naturalistic patch appearance. Our experiments have shown, that using a pre-trained GAN helps to gain realistic-looking patches while preserving the performance similar to conventional adversarial patches

Effects of rising temperature on pelagic biogeochemistry in mesocosm systems: a comparative analysis of the AQUASHIFT Kiel experiments

A comparative analysis of data, obtained during four indoor-mesocosm experiments with natural spring plankton communities from the Baltic Sea, was conducted to investigate whether biogeochemical cycling is affected by an increase in water temperature of up to 6 °C above present-day conditions. In all experiments, warming stimulated in particular heterotrophic bacterial processes and had an accelerating effect on the temporal development of phytoplankton blooms. This was also mirrored in the build-up and partitioning of organic matter between particulate and dissolved phases. Thus, warming increased both the magnitude and rate of dissolved organic carbon (DOC) build-up, whereas the accumulation of particulate organic carbon (POC) and phosphorus (POP) decreased with rising temperature. In concert, the observed temperature-mediated changes in biogeochemical components suggest strong shifts in the functioning of marine pelagic food webs and the ocean’s biological carbon pump, hence providing potential feedback mechanisms to Earth’s climate system

Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental Study

Autonomous vehicles need to have a semantic understanding of the three-dimensional world around them in order to reason about their environment. State of the art methods use deep neural networks to predict semantic classes for each point in a LiDAR scan. A powerful and efficient way to process LiDAR measurements is to use two-dimensional, image-like projections. In this work, we perform a comprehensive experimental study of image-based semantic segmentation architectures for LiDAR point clouds. We demonstrate various techniques to boost the performance and to improve runtime as well as memory constraints. First, we examine the effect of network size and suggest that much faster inference times can be achieved at a very low cost to accuracy. Next, we introduce an improved point cloud projection technique that does not suffer from systematic occlusions. We use a cyclic padding mechanism that provides context at the horizontal field-of-view boundaries. In a third part, we perform experiments with a soft Dice loss function that directly optimizes for the intersection-over-union metric. Finally, we propose a new kind of convolution layer with a reduced amount of weight-sharing along one of the two spatial dimensions, addressing the large difference in appearance along the vertical axis of a LiDAR scan. We propose a final set of the above methods with which the model achieves an increase of 3.2% in mIoU segmentation performance over the baseline while requiring only 42% of the original inference time.Comment: Accepted at IEEE Intelligent Vehicles Symposium (IV) 2020. The code can be found here: http://ltriess.github.io/scan-semse

A Realism Metric for Generated LiDAR Point Clouds

A considerable amount of research is concerned with the generation of realistic sensor data. LiDAR point clouds are generated by complex simulations or learned generative models. The generated data is usually exploited to enable or improve downstream perception algorithms. Two major questions arise from these procedures: First, how to evaluate the realism of the generated data? Second, does more realistic data also lead to better perception performance? This paper addresses both questions and presents a novel metric to quantify the realism of LiDAR point clouds. Relevant features are learned from real-world and synthetic point clouds by training on a proxy classification task. In a series of experiments, we demonstrate the application of our metric to determine the realism of generated LiDAR data and compare the realism estimation of our metric to the performance of a segmentation model. We confirm that our metric provides an indication for the downstream segmentation performance

Enhanced biological carbon consumption in a high CO2 ocean

The oceans have absorbed nearly half of the fossil-fuel carbon dioxide (CO2) emitted into the atmosphere since pre-industrial times1, causing a measurable reduction in seawater pH and carbonate saturation2. If CO2 emissions continue to rise at current rates, upper-ocean pH will decrease to levels lower than have existed for tens of millions of years and, critically, at a rate of change 100 times greater than at any time over this period3. Recent studies have shown effects of ocean acidification on a variety of marine life forms, in particular calcifying organisms4, 5, 6. Consequences at the community to ecosystem level, in contrast, are largely unknown. Here we show that dissolved inorganic carbon consumption of a natural plankton community maintained in mesocosm enclosures at initial CO2 partial pressures of 350, 700 and 1,050 μatm increases with rising CO2. The community consumed up to 39% more dissolved inorganic carbon at increased CO2 partial pressures compared to present levels, whereas nutrient uptake remained the same. The stoichiometry of carbon to nitrogen drawdown increased from 6.0 at low CO2 to 8.0 at high CO2, thus exceeding the Redfield carbon:nitrogen ratio of 6.6 in today’s ocean7. This excess carbon consumption was associated with higher loss of organic carbon from the upper layer of the stratified mesocosms. If applicable to the natural environment, the observed responses have implications for a variety of marine biological and biogeochemical processes, and underscore the importance of biologically driven feedbacks in the ocean to global change