194 research outputs found

    The backbone of the climate network

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    We propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system, relying on the nonlinear mutual information of time series analysis and betweenness centrality of complex network theory. We show, that this approach reveals a rich internal structure in complex climate networks constructed from reanalysis and model surface air temperature data. Our novel method uncovers peculiar wave-like structures of high energy flow, that we relate to global surface ocean currents. This points to a major role of the oceanic surface circulation in coupling and stabilizing the global temperature field in the long term mean (140 years for the model run and 60 years for reanalysis data). We find that these results cannot be obtained using classical linear methods of multivariate data analysis, and have ensured their robustness by intensive significance testing.Comment: 6 pages, 5 figure

    Retinal boundary segmentation in stargardt disease optical coherence tomography images using automated deep learning

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    Purpose: To use a deep learning model to develop a fully automated method (fully semantic network and graph search [FS-GS]) of retinal segmentation for optical coherence tomography (OCT) images from patients with Stargardt disease. Methods: Eighty-seven manually segmented (ground truth) OCT volume scan sets (5171 B-scans) from 22 patients with Stargardt disease were used for training, validation and testing of a novel retinal boundary detection approach (FS-GS) that combines a fully semantic deep learning segmentation method, which generates a per-pixel class prediction map with a graph-search method to extract retinal boundary positions. The performance was evaluated using the mean absolute boundary error and the differences in two clinical metrics (retinal thickness and volume) compared with the ground truth. The performance of a separate deep learning method and two publicly available software algorithms were also evaluated against the ground truth. Results: FS-GS showed an excellent agreement with the ground truth, with a boundary mean absolute error of 0.23 and 1.12 pixels for the internal limiting membrane and the base of retinal pigment epithelium or Bruch's membrane, respectively. The mean difference in thickness and volume across the central 6 mm zone were 2.10 µm and 0.059 mm3. The performance of the proposed method was more accurate and consistent than the publicly available OCTExplorer and AURA tools. Conclusions: The FS-GS method delivers good performance in segmentation of OCT images of pathologic retina in Stargardt disease. Translational Relevance: Deep learning models can provide a robust method for retinal segmentation and support a high-throughput analysis pipeline for measuring retinal thickness and volume in Stargardt disease

    Fluctuation Properties of Steady-State Langevin Systems

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    Motivated by stochastic models of climate phenomena, the steady-state of a linear stochastic model with additive Gaussian white noise is studied. Fluctuation theorems for nonequilibrium steady-states provide a constraint on the character of these fluctuations. The properties of the fluctuations which are unconstrained by the fluctuation theorem are investigated and related to the model parameters. The irreversibility of trajectory segments, which satisfies a fluctuation theorem, is used as a measure of nonequilibrium fluctuations. The moments of the irreversibility probability density function (pdf) are found and the pdf is seen to be non-Gaussian. The average irreversibility goes to zero for short and long trajectory segments and has a maximum for some finite segment length, which defines a characteristic timescale of the fluctuations. The initial average irreversibility growth rate is equal to the average entropy production and is related to noise-amplification. For systems with a separation of deterministic timescales, modes with timescales much shorter than the trajectory timespan and whose noise amplitudes are not asymptotically large, do not, to first order, contribute to the irreversibility statistics, providing a potential basis for dimensional reduction.Comment: 8 pages, to be published in Physical Review

    Generation and Structure of Solitary Rossby Vortices in Rotating Fluids

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    The formation of zonal flows and vortices in the generalized Charney-Hasegawa-Mima equation is studied. We focus on the regime when the size of structures is comparable to or larger than the deformation (Rossby) radius. Numerical simulations show the formation of anticyclonic vortices in unstable shear flows and ring-like vortices with quiescent cores and vorticity concentrated in a ring. Physical mechanisms that lead to these phenomena and their relevance to turbulence in planetary atmospheres are discussed.Comment: 3 pages in REVTeX, 5 postscript figures separately, submitted to Phys. Rev.

    Bradykinin, but not muscarinic, inhibition of M-current in rat sympathetic ganglion neurons involves phospholipase C-beta 4.

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    Rat superior cervical ganglion (SCG) neurons express low-threshold noninactivating M-type potassium channels (I-K(M)), which can be inhibited by activation of M-1 muscarinic receptors (M-1 mAChR) and bradykinin (BK) B-2 receptors. Inhibition by the M1 mAChR agonist oxotremorine methiodide (Oxo-M) is mediated, at least in part, by the pertussis toxin-insensitive G-protein G alpha (q) (Caulfield et al., 1994; Haley et al., 1998a), whereas BK inhibition involves G alpha (q) and/or G alpha (11) (Jones et al., 1995). G alpha (q) and G alpha (11) can stimulate phospholipase C-beta (PLC-beta), raising the possibility that PLC is involved in I-K(M) inhibition by Oxo-M and BK. RT-PCR and antibody staining confirmed the presence of PLC-beta1, - beta2, - beta3, and - beta4 in rat SCG. We have tested the role of two PLC isoforms (PLC-beta1 and PLC-beta4) using antisense-expression constructs. Antisense constructs, consisting of the cytomegalovirus promoter driving antisense cRNA corresponding to the 3'-untranslated regions of PLC-beta1 and PLC-beta4, were injected into the nucleus of dissociated SCG neurons. Injected cells showed reduced antibody staining for the relevant PLC-beta isoform when compared to uninjected cells 48 hr later. BK inhibition of I-K(M) was significantly reduced 48 hr after injection of the PLC-beta4, but not the PLC-beta1, antisense-encoding plasmid. Neither PLC-beta antisense altered M-1 mAChR inhibition by Oxo-M. These data support the conclusion of Cruzblanca et al. (1998) that BK, but not M-1 mAChR, inhibition of I-K(M) involves PLC and extends this finding by indicating that PLC-beta4 is involved

    Recent Advances Concerning Certain Class of Geophysical Flows

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    This paper is devoted to reviewing several recent developments concerning certain class of geophysical models, including the primitive equations (PEs) of atmospheric and oceanic dynamics and a tropical atmosphere model. The PEs for large-scale oceanic and atmospheric dynamics are derived from the Navier-Stokes equations coupled to the heat convection by adopting the Boussinesq and hydrostatic approximations, while the tropical atmosphere model considered here is a nonlinear interaction system between the barotropic mode and the first baroclinic mode of the tropical atmosphere with moisture. We are mainly concerned with the global well-posedness of strong solutions to these systems, with full or partial viscosity, as well as certain singular perturbation small parameter limits related to these systems, including the small aspect ratio limit from the Navier-Stokes equations to the PEs, and a small relaxation-parameter in the tropical atmosphere model. These limits provide a rigorous justification to the hydrostatic balance in the PEs, and to the relaxation limit of the tropical atmosphere model, respectively. Some conditional uniqueness of weak solutions, and the global well-posedness of weak solutions with certain class of discontinuous initial data, to the PEs are also presented.Comment: arXiv admin note: text overlap with arXiv:1507.0523

    Magazine and reader constructions of 'metrosexuality' and masculinity: a membership categorisation analysis

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    Since the launch of men's lifestyle magazines in the 1980s, academic literature has predominantly focused on them as a cultural phenomenon arising from entrepreneurial and commercial initiatives and/or as cultural texts that proffer representations of masculinity such as 'new lad' and 'new dad'. This paper steps aside from the focus on culture and, instead, treats magazine content as a discursive space in which gender and sexuality are oriented to, negotiated, and accomplished within and beyond the magazine itself (i.e. through readers' responses). Specifically, membership categorisation analysis is deployed to explore how the relatively new (and perhaps alternative) category for men - 'metrosexual' - is presented and received. Our analysis suggests that masculinity concerns are central in debates about 'metrosexuality', with self-identified 'metrosexuals' invoking heterosexual prowess and self-respect on the one hand, and critics (e.g. selfidentified 'real men') lamenting 'metrosexuality' for its perceived effeminacy and lack of authenticity on the other. Implications for understanding contemporary masculinities are discussed

    T helper cell subsets specific for pseudomonas aeruginosa in healthy individuals and patients with cystic fibrosis

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    Background: We set out to determine the magnitude of antigen-specific memory T helper cell responses to Pseudomonas aeruginosa in healthy humans and patients with cystic fibrosis. Methods: Peripheral blood human memory CD4+ T cells were co-cultured with dendritic cells that had been infected with different strains of Pseudomonas aeruginosa. The T helper response was determined by measuring proliferation, immunoassay of cytokine output, and immunostaining of intracellular cytokines. Results: Healthy individuals and patients with cystic fibrosis had robust antigen-specific memory CD4+ T cell responses to Pseudomonas aeruginosa that not only contained a Th1 and Th17 component but also Th22 cells. In contrast to previous descriptions of human Th22 cells, these Pseudomonal-specific Th22 cells lacked the skin homing markers CCR4 or CCR10, although were CCR6+. Healthy individuals and patients with cystic fibrosis had similar levels of Th22 cells, but the patient group had significantly fewer Th17 cells in peripheral blood. Conclusions: Th22 cells specific to Pseudomonas aeruginosa are induced in both healthy individuals and patients with cystic fibrosis. Along with Th17 cells, they may play an important role in the pulmonary response to this microbe in patients with cystic fibrosis and other conditions

    Multi-level Dynamical Systems: Connecting the Ruelle Response Theory and the Mori-Zwanzig Approach

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    In this paper we consider the problem of deriving approximate autonomous dynamics for a number of variables of a dynamical system, which are weakly coupled to the remaining variables. In a previous paper we have used the Ruelle response theory on such a weakly coupled system to construct a surrogate dynamics, such that the expectation value of any observable agrees, up to second order in the coupling strength, to its expectation evaluated on the full dynamics. We show here that such surrogate dynamics agree up to second order to an expansion of the Mori-Zwanzig projected dynamics. This implies that the parametrizations of unresolved processes suited for prediction and for the representation of long term statistical properties are closely related, if one takes into account, in addition to the widely adopted stochastic forcing, the often neglected memory effects.Comment: 14 pages, 1 figur

    Coupling dynamic equations and satellite images for modelling ocean surface circulation

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    International audienceSatellite image sequences visualise the ocean surface and allow assessing its dynamics. Processing these data is then of major interest to get a better understanding of the observed processes. As demonstrated by state-of-the-art, image assimilation permits to retrieve surface motion, based on assumptions on the dynamics. In this paper, we demonstrate that a simple heuristics, such as the Lagrangian constancy of velocity, can be used and successfully replaces the complex physical properties described by the Navier-Stokes equations for assessing surface circulation from satellite images. A data assimilation method is proposed that adds an acceleration term a(t) to this Lagrangian constancy equation, which summarises all physical processes other than advection. A cost function is designed that quantifies discrepancy between satellite data and model values. This cost function is minimised by the BFGS solver with a dual method of data assimilation. The result is the initial motion field and the acceleration terms a(t) on the whole temporal interval. These values a(t) model the forces, other than advection, that contribute to surface circulation. Our approach was tested on synthetic data and with Sea Surface Temperature images acquired on Black Sea. Results are quantified and compared to those of state-of-the-art methods
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