1,809 research outputs found

    Quantitative criteria for choosing targets and indicators for sustainable use of ecosystems

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    The authors thank Simon Greenstreet, Cristina Herbon, Simon Jennings, Tiziana Luisetti, Lucille Paltriguera, and Christian Wilson for comments on previous versions of this paper. This work has resulted from the DEVOTES (DEVelopment Of innovative Tools for understanding marine biodiversity and assessing Good Environmental Status) project funded by the EU under the 7th Framework Programme, ‘The Ocean of Tomorrow’ Theme (No. 308392), www.devotes-project.eu. Further, A.G.R. was partially funded by the Natural Environment Research Council and the UK Department for Food, Environment and Rural Affairs (Defra) within the Marine Ecosystems Research Program (MERP), C.P.L. by Defra (M1228), A.Z. by BIOsingle bondC3 within the joint Baltic Sea Research and Development Programme (EU 7th and Research Council of Lithuania, BONUS-1/2014), and M.C.U. by the Spanish Programme for talent and employability in I + D + i ‘Torres Quevedo’

    Chemotaxis When Bacteria Remember: Drift versus Diffusion

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    {\sl Escherichia coli} ({\sl E. coli}) bacteria govern their trajectories by switching between running and tumbling modes as a function of the nutrient concentration they experienced in the past. At short time one observes a drift of the bacterial population, while at long time one observes accumulation in high-nutrient regions. Recent work has viewed chemotaxis as a compromise between drift toward favorable regions and accumulation in favorable regions. A number of earlier studies assume that a bacterium resets its memory at tumbles -- a fact not borne out by experiment -- and make use of approximate coarse-grained descriptions. Here, we revisit the problem of chemotaxis without resorting to any memory resets. We find that when bacteria respond to the environment in a non-adaptive manner, chemotaxis is generally dominated by diffusion, whereas when bacteria respond in an adaptive manner, chemotaxis is dominated by a bias in the motion. In the adaptive case, favorable drift occurs together with favorable accumulation. We derive our results from detailed simulations and a variety of analytical arguments. In particular, we introduce a new coarse-grained description of chemotaxis as biased diffusion, and we discuss the way it departs from older coarse-grained descriptions.Comment: Revised version, journal reference adde

    Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment

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    Osteosarcoma is the most common malignant primary bone tumor. Standard treatment includes pre-operative chemotherapy followed by surgical resection. The response to treatment as measured by ratio of necrotic tumor area to overall tumor area is a known prognostic factor for overall survival. This assessment is currently done manually by pathologists by looking at glass slides under the microscope which may not be reproducible due to its subjective nature. Convolutional neural networks (CNNs) can be used for automated segmentation of viable and necrotic tumor on osteosarcoma whole slide images. One bottleneck for supervised learning is that large amounts of accurate annotations are required for training which is a time-consuming and expensive process. In this paper, we describe Deep Interactive Learning (DIaL) as an efficient labeling approach for training CNNs. After an initial labeling step is done, annotators only need to correct mislabeled regions from previous segmentation predictions to improve the CNN model until the satisfactory predictions are achieved. Our experiments show that our CNN model trained by only 7 hours of annotation using DIaL can successfully estimate ratios of necrosis within expected inter-observer variation rate for non-standardized manual surgical pathology task.Comment: Accepted at MICCAI 202

    Flavour physics constraints in the BMSSM

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    We study the implications of the presence of the two leading-order, non-renormalizable operators in the Higgs sector of the MSSM to flavour physics observables. We identify the constraints of flavour physics on the parameters of the BMSSM when we: a) focus on a region of parameters for which electroweak baryogenesis is feasible, b) use a CMSSM-like parametrization, and c) consider the case of a generic NUHM-type model. We find significant differences as compared to the standard MSSM case.Comment: 22 pages, 7 figure

    On the computation of zone and double zone diagrams

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    Classical objects in computational geometry are defined by explicit relations. Several years ago the pioneering works of T. Asano, J. Matousek and T. Tokuyama introduced "implicit computational geometry", in which the geometric objects are defined by implicit relations involving sets. An important member in this family is called "a zone diagram". The implicit nature of zone diagrams implies, as already observed in the original works, that their computation is a challenging task. In a continuous setting this task has been addressed (briefly) only by these authors in the Euclidean plane with point sites. We discuss the possibility to compute zone diagrams in a wide class of spaces and also shed new light on their computation in the original setting. The class of spaces, which is introduced here, includes, in particular, Euclidean spheres and finite dimensional strictly convex normed spaces. Sites of a general form are allowed and it is shown that a generalization of the iterative method suggested by Asano, Matousek and Tokuyama converges to a double zone diagram, another implicit geometric object whose existence is known in general. Occasionally a zone diagram can be obtained from this procedure. The actual (approximate) computation of the iterations is based on a simple algorithm which enables the approximate computation of Voronoi diagrams in a general setting. Our analysis also yields a few byproducts of independent interest, such as certain topological properties of Voronoi cells (e.g., that in the considered setting their boundaries cannot be "fat").Comment: Very slight improvements (mainly correction of a few typos); add DOI; Ref [51] points to a freely available computer application which implements the algorithms; to appear in Discrete & Computational Geometry (available online

    Preferential Paths of Air-water Two-phase Flow in Porous Structures with Special Consideration of Channel Thickness Effects.

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    Accurate understanding and predicting the flow paths of immiscible two-phase flow in rocky porous structures are of critical importance for the evaluation of oil or gas recovery and prediction of rock slides caused by gas-liquid flow. A 2D phase field model was established for compressible air-water two-phase flow in heterogenous porous structures. The dynamic characteristics of air-water two-phase interface and preferential paths in porous structures were simulated. The factors affecting the path selection of two-phase flow in porous structures were analyzed. Transparent physical models of complex porous structures were prepared using 3D printing technology. Tracer dye was used to visually observe the flow characteristics and path selection in air-water two-phase displacement experiments. The experimental observations agree with the numerical results used to validate the accuracy of phase field model. The effects of channel thickness on the air-water two-phase flow behavior and paths in porous structures were also analyzed. The results indicate that thick channels can induce secondary air flow paths due to the increase in flow resistance; consequently, the flow distribution is different from that in narrow channels. This study provides a new reference for quantitatively analyzing multi-phase flow and predicting the preferential paths of immiscible fluids in porous structures

    Proximity of Iron Pnictide Superconductors to a Quantum Tricritical Point

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    We determine the nature of the magnetic quantum critical point in the doped LaFeAsO using a set of constrained density functional calculations that provide ab initio coefficients for a Landau order parameter analysis. The system turns out to be remarkably close to a quantum tricritical point, where the nature of the phase transition changes from first to second order. We compare with the effective field theory and discuss the experimental consequences.Comment: 4 pages, 4 figure

    The polo-like kinase 1 (PLK1) inhibitor NMS-P937 is effective in a new model of disseminated primary CD56+ acute monoblastic leukaemia

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    CD56 is expressed in 15–20% of acute myeloid leukaemias (AML) and is associated with extramedullary diffusion, multidrug resistance and poor prognosis. We describe the establishment and characterisation of a novel disseminated model of AML (AML-NS8), generated by injection into mice of leukaemic blasts freshly isolated from a patient with an aggressive CD56+ monoblastic AML (M5a). The model reproduced typical manifestations of this leukaemia, including presence of extramedullary masses and central nervous system involvement, and the original phenotype, karyotype and genotype of leukaemic cells were retained in vivo. Recently Polo-Like Kinase 1 (PLK1) has emerged as a new candidate drug target in AML. We therefore tested our PLK1 inhibitor NMS-P937 in this model either in the engraftment or in the established disease settings. Both schedules showed good efficacy compared to standard therapies, with a significant increase in median survival time (MST) expecially in the established disease setting (MST = 28, 36, 62 days for vehicle, cytarabine and NMS-P937, respectively). Importantly, we could also demonstrate that NMS-P937 induced specific biomarker modulation in extramedullary tissues. This new in vivo model of CD56+ AML that recapitulates the human tumour lends support for the therapeutic use of PLK1 inhibitors in AML
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