712 research outputs found

    Heat transport in rotating convection without Ekman layers

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    Numerical simulation of rotating convection in plane layers with free slip boundaries show that the convective flows can be classified according to a quantity constructed from the Reynolds, Prandtl and Ekman numbers. Three different flow regimes appear: Laminar flow close to the onset of convection, turbulent flow in which the heat flow approaches the heat flow of non-rotating convection, and an intermediate regime in which the heat flow scales according to a power law independent of thermal diffusivity and kinematic viscosity.Comment: 4 pages, 4 figure

    Using geophysical techniques to characterize tillage effect on soil properties

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    Tillage practices influence physical, chemical, and biological soil properties, which also affect soil quality and consequently plant growth. In this study, the main objective was to evaluate the effect of different tillage systems on soil physical properties by using geophysical methods, namely, ground-penetrating radar (far-field and near-field GPR), capacitance probes (ThetaProbe and 5TE), electromagnetic induction (EMI) (Profiler and EM38), soil sampling, and by soil penetrometer. Since 2005, three contrasting tillage systems were applied on different plots of an agricultural field: i) conventional tillage (CT) with mouldboard ploughing to 27 cm depth, ii) deep loosening tillage (DL) with a heavy tine cultivator to 30 cm depth, and iii) reduced tillage (RT) with a spring tine cultivator to 10 cm depth. The geophysical and soil strength measurements were performed in April 2010. We observed that tillage influences the soil resistance (deeper tillage decreases soil resistance), which could be partly seen in the radar data. Soil water content reference measurements (capacitance probes and soil sampling) were in a relatively good agreement with the water content estimates from far-field GPR. We also observed that the tillage influences surface water content. Mean surface water content was significantly lower for CT than for DL and RT, which was partly explained by lower macropore connectivity between the topsoil and the deeper layers after conventional tillage. This study confirms the potential of GPR and EMI sensors for soil physical properties determination at the field scale and for the characterization of agricultural management practices

    C-reactive protein binds to alphaIIbbeta3.

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    C-reactive protein binds to alphaIIbbeta3

    Green vehicle technology to enhance the performance of a European port: a simulation model with a cost-benefit approach

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    In this paper, we study the impact of using a new intelligent vehicle technology on the performance and total cost of a European port, in comparison with existing vehicle systems like trucks. Intelligent autonomous vehicles (IAVs) are a new type of automated guided vehicles (AGVs) with better maneuverability and a special ability to pick up/drop off containers by themselves. To identify the most economical fleet size for each type of vehicle to satisfy the port's performance target, and also to compare their impact on the performance/cost of container terminals, we developed a discrete-event simulation model to simulate all port activities in micro-level (low-level) details. We also developed a cost model to investigate the present values of using two types of vehicle, given the identified fleet size. Results of using the different types of vehicles are then compared based on the given performance measures such as the quay crane net moves per hour and average total discharging/loading time at berth. Besides successfully identifying the optimal fleet size for each type of vehicle, simulation results reveal two findings: first, even when not utilising their ability to pick up/drop off containers, the IAVs still have similar efficacy to regular trucks thanks to their better maneuverability. Second, enabling IAVs ability to pick up/drop off containers significantly improves the port performance. Given the best configuration and fleet size as identified by the simulation, we use the developed cost model to estimate the total cost needed for each type of vehicle to meet the performance target. Finally, we study the performance of the case study port with advanced real-time vehicle dispatching/scheduling and container placement strategies. This study reveals that the case study port can greatly benefit from upgrading its current vehicle dispatching/scheduling strategy to a more advanced one

    Nonoperative Modalities to Treat Symptomatic Cervical Spondylosis

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    Cervical spondylosis is a common and disabling condition. It is generally felt that the initial management should be nonoperative, and these modalities include physiotherapy, analgesia and selective nerve root injections. Surgery should be reserved for moderate to severe myelopathy patients who have failed a period of conservative treatment and patients whose symptoms are not adequately controlled by nonoperative means. A review of the literature supporting various modalities of conservative management is presented, and it is concluded that although effective, nonoperative treatment is labour intensive, requiring regular review and careful selection of medications and physical therapy on a case by case basis

    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.

    Impact of Tumour Epithelial Subtype on Circulating MicroRNAs in Breast Cancer Patients

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    While a range of miRNAs have been shown to be dysregulated in the circulation of patients with breast cancer, little is known about the relationship between circulating levels and tumour characteristics. The aim of this study was to analyse alterations in circulating miRNA expression during tumour progression in a murine model of breast cancer, and to detemine the clinical relevance of identified miRNAs at both tissue and circulating level in patient samples. Athymic nude mice received a subcutaneous or mammary fat pad injection of MDA-MB-231 cells. Blood sampling was performed at weeks 1, 3 and 6 following tumour induction, and microRNA extracted. MicroRNA microArray analysis was performed comparing samples harvested at week 1 to those collected at week 6 from the same animals. Significantly altered miRNAs were validated across all murine samples by RQ-PCR (n = 45). Three miRNAs of interest were then quantified in the circulation(n = 166) and tissue (n = 100) of breast cancer patients and healthy control individuals. MicroArray-based analysis of murine blood samples revealed levels of 77 circulating microRNAs to be changed during disease progression, with 44 demonstrating changes .2-fold. Validation across all samples revealed miR-138 to be significantly elevated in the circulation of animals during disease development, with miR-191 and miR-106a levels significantly decreased. Analysis of patient tissue and blood samples revealed miR-138 to be significantly up-regulated in the circulation of patients with breast cancer, with no change observed in the tissue setting. While not significantly changed overall in breast cancer patients compared to controls, circulating miR-106a and miR-191 were significantly decreased in patients with basal breast cancer. In tissue, both miRNAs were significantly elevated in breast cancer compared to normal breast tissue. The data demonstrates an impact of tumour epithelial subtype on circulating levels of miRNAs, and highlights divergent miRNA profiles between tissue and blood samples from breast cancer patients

    Deep Learning Formulation of ECGI for Data-driven Integration of Spatiotemporal Correlations and Imaging Information

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    International audienceThe challenge of non-invasive Electrocardiographic Imaging (ECGI) is to recreate the electrical activity of the heart using body surface potentials. Specifically, there are numerical difficulties due to the ill-posed nature of the problem. We propose a novel method based on Conditional Variational Autoencoders using Deep generative Neural Networks to overcome this challenge. By conditioning the electrical activity on heart shape and electrical potentials, our model is able to generate activation maps with good accuracy on simulated data (mean square error, MSE = 0.095). This method differs from other formulations because it naturally takes into account spatio-temporal correlations as well as the imaging substrate through convolutions and conditioning. We believe these features can help improving ECGI results
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