Surface mixing and biological activity in the four Eastern Boundary Upwelling Systems

Eastern Boundary Upwelling Systems (EBUS) are characterized by a high productivity of plankton associated with large commercial fisheries, thus playing key biological and socio-economical roles. The aim of this work is to make a comparative study of these four upwelling systems focussing on their surface stirring, using the Finite Size Lyapunov Exponents (FSLEs), and their biological activity, based on satellite data. First, the spatial distribution of horizontal mixing is analysed from time averages and from probability density functions of FSLEs. Then we studied the temporal variability of surface stirring focussing on the annual and seasonal cycle. There is a global negative correlation between surface horizontal mixing and chlorophyll standing stocks over the four areas. To try to better understand this inverse relationship, we consider the vertical dimension by looking at the Ekman-transport and vertical velocities. We suggest the possibility of a changing response of the phytoplankton to sub/mesoscale turbulence, from a negative effect in the very productive coastal areas to a positive one in the open ocean.Comment: 12 pages. NPG Special Issue on "Nonlinear processes in oceanic and atmospheric flows". Open Access paper, available also at the publisher site: http://www.nonlin-processes-geophys.net/16/557/2009

A quantitative mesoscale characterization of the mechanical behaviour of Ceramic Matrix Composites

An experimental micro-macro kinematic description of matrix cracking in unidirectionnal ceramic matrix composites is proposed. It has been enlighten by observations performed during an in situ tensile test in a Scanning Electron Microscope. The characterization of matrix crack nucleation, propagation and coalescence has been done with new parameters and related to the macroscopic behaviour

Distinguishing Healthy Ageing from Dementia: A Biomechanical Simulation of Brain Atrophy Using Deep Networks

Biomechanical modeling of tissue deformation can be used to simulate different scenarios of longitudinal brain evolution. In this work, we present a deep learning framework for hyper-elastic strain modelling of brain atrophy, during healthy ageing and in Alzheimer’s Disease. The framework directly models the effects of age, disease status, and scan interval to regress regional patterns of atrophy, from which a strain-based model estimates deformations. This model is trained and validated using 3D structural magnetic resonance imaging data from the ADNI cohort. Results show that the framework can estimate realistic deformations, following the known course of Alzheimer’s disease, that clearly differentiate between healthy and demented patterns of ageing. This suggests the framework has potential to be incorporated into explainable models of disease, for the exploration of interventions and counterfactual examples

Climate change projections of West Nile virus infections in Europe: implications for blood safety practices

Background: West Nile virus (WNV) is transmitted by mosquitoes in both urban as well as in rural environments and can be pathogenic in birds, horses and humans. Extrinsic factors such as temperature and land use are determinants of WNV outbreaks in Europe, along with intrinsic factors of the vector and virus. Methods: With a multivariate model for WNV transmission we computed the probability of WNV infection in 2014, with July 2014 temperature anomalies. We applied the July temperature anomalies under the balanced A1B climate change scenario (mix of all energy sources, fossil and non-fossil) for 2025 and 2050 to model and project the risk of WNV infection in the future. Since asymptomatic infections are common in humans (which can result in the contamination of the donated blood) we estimated the predictive prevalence of WNV infections in the blood donor population. Results: External validation of the probability model with 2014 cases indicated good prediction, based on an Area Under Curve (AUC) of 0.871 (SD = 0.032), on the Receiver Operating Characteristic Curve (ROC). The climate change projections for 2025 reveal a higher probability of WNV infection particularly at the edges of the current transmission areas (for example in Eastern Croatia, Northeastern and Northwestern Turkey) and an even further expansion in 2050. The prevalence of infection in (blood donor) populations in the outbreak-affected districts is expected to expand in the future. Conclusions Predictive modelling of environmental and climatic drivers of WNV can be a valuable tool for public health practice. It can help delineate districts at risk for future transmission. These areas can be subjected to integrated disease and vector surveillance, outreach to the public and health care providers, implementation of personal protective measures, screening of blood donors, and vector abatement activities. (Résumé d'auteur

Automatic C-Plane Detection in Pelvic Floor Transperineal Volumetric Ultrasound

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

First Results of the Phase II SIMPLE Dark Matter Search

We report results of a 14.1 kgd measurement with 15 superheated droplet detectors of total active mass 0.208 kg, comprising the first stage of a 30 kgd Phase II experiment. In combination with the results of the neutron-spin sensitive XENON10 experiment, these results yield a limit of |a_p| < 0.32 for M_W = 50 GeV/c2 on the spin-dependent sector of weakly interacting massive particle-nucleus interactions with a 50% reduction in the previously allowed region of the phase space formerly defined by XENON, KIMS and PICASSO. In the spin-independent sector, a limit of 2.3x10-5 pb at M_W = 45 GeV/c2 is obtained.Comment: 4 pages, 4 figures; PRL-accepted version with corrected SI contour (Fig. 4