5,097 research outputs found

    The large‐scale freshwater cycle of the Arctic

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    This paper synthesizes our understanding of the Arctic\u27s large‐scale freshwater cycle. It combines terrestrial and oceanic observations with insights gained from the ERA‐40 reanalysis and land surface and ice‐ocean models. Annual mean freshwater input to the Arctic Ocean is dominated by river discharge (38%), inflow through Bering Strait (30%), and net precipitation (24%). Total freshwater export from the Arctic Ocean to the North Atlantic is dominated by transports through the Canadian Arctic Archipelago (35%) and via Fram Strait as liquid (26%) and sea ice (25%). All terms are computed relative to a reference salinity of 34.8. Compared to earlier estimates, our budget features larger import of freshwater through Bering Strait and larger liquid phase export through Fram Strait. While there is no reason to expect a steady state, error analysis indicates that the difference between annual mean oceanic inflows and outflows (∼8% of the total inflow) is indistinguishable from zero. Freshwater in the Arctic Ocean has a mean residence time of about a decade. This is understood in that annual freshwater input, while large (∼8500 km3), is an order of magnitude smaller than oceanic freshwater storage of ∼84,000 km3. Freshwater in the atmosphere, as water vapor, has a residence time of about a week. Seasonality in Arctic Ocean freshwater storage is nevertheless highly uncertain, reflecting both sparse hydrographic data and insufficient information on sea ice volume. Uncertainties mask seasonal storage changes forced by freshwater fluxes. Of flux terms with sufficient data for analysis, Fram Strait ice outflow shows the largest interannual variability

    Snowmass 2001: Jet Energy Flow Project

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    Conventional cone jet algorithms arose from heuristic considerations of LO hard scattering coupled to independent showering. These algorithms implicitly assume that the final states of individual events can be mapped onto a unique set of jets that are in turn associated with a unique set of underlying hard scattering partons. Thus each final state hadron is assigned to a unique underlying parton. The Jet Energy Flow (JEF) analysis described here does not make such assumptions. The final states of individual events are instead described in terms of flow distributions of hadronic energy. Quantities of physical interest are constructed from the energy flow distribution summed over all events. The resulting analysis is less sensitive to higher order perturbative corrections and the impact of showering and hadronization than the standard cone algorithms.Comment: REVTeX4, 13 pages, 6 figures; Contribution to the P5 Working Group on QCD and Strong Interactions at Snowmass 200

    Газификация промышленных отходов непрерывным лазерным излучением

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    Liposome-encapsulated corticosteroids have shown to exert strong beneficial effects in inflammatory diseases, such as arthritis and cancer. To extend the clinical applicability of these potent nanomedicines, the therapeutic effect of dexamethasone phosphate loaded long-circulating liposomes (LCL-DXP) was evaluated in animal models of multiple sclerosis (MS) and Crohn's disease (CD). In mice with experimental autoimmune encephalitis (EAE), a model for MS, treatment with LCL-DXP, but not free DXP, resulted in a decrease in disease activity when compared to PBS treated mice. In contrast, in mice with chronic DSS-induced colitis, a model for CD, treatment with LCL-DXP did not induce an improvement, but in fact worsened the fecal blood loss after treatment, indicating an aggravation of the disease. It is hypothesized that modulation of macrophage polarization towards a M2 phenotype underlies the efficacy of corticosteroid-based drug delivery systems, which is supported by the presented data. On the one hand, M1 polarized macrophages are part of the pathogenesis of MS; the modulation to M2-polarization by LCL-DXP is therefore beneficial. On the other hand, M1-polarized intestinal macrophages fulfill a protective and inflammation-suppressing role in intestinal homeostasis; changing their phenotype to M2 causes reduced protection to invading microorganisms, leading to a more severe intestinal inflammation. These findings therefore indicate that the interplay between the specific phenotype of macrophages and the specific inflammatory context of the inflammatory disease in question may be an important determining factor in the therapeutic applicability of liposomal corticosteroids in inflammatory disease

    Automatic C-Plane Detection in Pelvic Floor Transperineal Volumetric Ultrasound

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    © 2020, Springer Nature Switzerland AG. Transperineal volumetric ultrasound (US) imaging has become routine practice for diagnosing pelvic floor disease (PFD). Hereto, clinical guidelines stipulate to make measurements in an anatomically defined 2D plane within a 3D volume, the so-called C-plane. This task is currently performed manually in clinical practice, which is labour-intensive and requires expert knowledge of pelvic floor anatomy, as no computer-aided C-plane method exists. To automate this process, we propose a novel, guideline-driven approach for automatic detection of the C-plane. The method uses a convolutional neural network (CNN) to identify extreme coordinates of the symphysis pubis and levator ani muscle (which define the C-plane) directly via landmark regression. The C-plane is identified in a postprocessing step. When evaluated on 100 US volumes, our best performing method (multi-task regression with UNet) achieved a mean error of 6.05 mm and 4.81 and took 20 s. Two experts blindly evaluated the quality of the automatically detected planes and manually defined the (gold standard) C-plane in terms of their clinical diagnostic quality. We show that the proposed method performs comparably to the manual definition. The automatic method reduces the average time to detect the C-plane by 100 s and reduces the need for high-level expertise in PFD US assessment

    Disentangling the effects of plant species invasion and urban development on arthropod community composition

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    Urban development and species invasion are two major global threats to biodiversity. These threats often co-occur, as developed areas are more prone to species invasion. However, few empirical studies have tested if both factors affect biodiversity in similar ways. Here we study the individual and combined effects of urban development and plant invasion on the composition of arthropod communities. We assessed 36 paired invaded and non-invaded sample plots, invaded by the plant Antigonon leptopus, with half of these pairs located in natural and the other half in developed land-use types on the Caribbean island of St. Eustatius. We used several taxonomic and functional variables to describe community composition and diversity. Our results show that both urban development and A. leptopus invasion affected community composition, albeit in different ways. Development significantly increased species richness and exponential Shannon diversity, while invasion had no effect on these variables. However, invasion significantly increased arthropod abundance and caused biotic homogenization. Specifically, uninvaded arthropod communities were distinctly different in species composition between developed and natural sites, while they became undistinguishable after A. leptopus invasion. Moreover, functional variables were significantly affected by species invasion, but not by urban development. Invaded communities had higher community-weighted mean body size and the feeding guild composition of invaded arthropod communities was characterized by the exceptional numbers of nectarivores, herbivores, and detritivores. With the exception of species richness and exponential Shannon diversity, invasion influenced four out of six response variables to a greater degree than urban development did. Hence, we can conclude that species invasion is not just a passenger of urban development but also a driver of change
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