Wake Development behind Paired Wings with Tip and Root Trailing Vortices: Consequences for Animal Flight Force Estimates

Recent experiments on flapping flight in animals have shown that a variety of unrelated species shed a wake behind left and right wings consisting of both tip and root vortices. Here we present an investigation using Particle Image Velocimetry (PIV) of the behaviour and interaction of trailing vortices shed by paired, fixed wings that simplify and mimic the wake of a flying animal with a non-lifting body. We measured flow velocities at five positions downstream of two adjacent NACA 0012 aerofoils and systematically varied aspect ratio, the gap between the wings (corresponding to the width of a non-lifting body), angle of attack, and the Reynolds number. The range of aspect ratios and Reynolds number where chosen to be relevant to natural fliers and swimmers, and insect flight in particular. We show that the wake behind the paired wings deformed as a consequence of the induced flow distribution such that the wingtip vortices convected downwards while the root vortices twist around each other. Vortex interaction and wake deformation became more pronounced further downstream of the wing, so the positioning of PIV measurement planes in experiments on flying animals has an important effect on subsequent force estimates due to rotating induced flow vectors. Wake deformation was most severe behind wings with lower aspect ratios and when the distance between the wings was small, suggesting that animals that match this description constitute high-risk groups in terms of measurement error. Our results, therefore, have significant implications for experimental design where wake measurements are used to estimate forces generated in animal flight. In particular, the downstream distance of the measurement plane should be minimised, notwithstanding the animal welfare constraints when measuring the wake behind flying animals

Laboratory diagnosis of Lyme neuroborreliosis: a comparison of three CSF anti-Borrelia antibody assays

The diagnosis of Lyme neuroborreliosis (LNB) requires the detection of intrathecal synthesis of Borrelia-specific antibodies, but in very early disease, the sensitivity may be low. We compared the performance of the second-generation IDEIA Lyme Neuroborreliosis test (Oxoid), based on purified native flagellum antigen, with two newly developed tests based on several recombinant antigens for the diagnosis of LNB. Patients investigated for LNB during 2003 through 2007 were included (n = 175); 52 with definite LNB, four with possible LNB and 119 non-LNB patients. Serum and cerebrospinal fluid (CSF) were analysed with the IDEIA Lyme Neuroborreliosis (Oxoid), VIDAS Lyme IgG (bioMérieux) and recomBead Borrelia IgM and IgG (Mikrogen) assays. Intrathecal antibody indices (AIs) were calculated according to the manufacturers’ protocols. The IDEIA test performed with an overall sensitivity (IgM and IgG AIs taken together) of 88 % and a specificity of 99 %. The VIDAS test showed a sensitivity of 86 % and a specificity of 97 %. An overall sensitivity of 100 % and a specificity of 97 % were achieved by the recomBead test. We conclude that the three assays performed equally well regarding specificity, but our data suggest an improved diagnostic sensitivity with the recomBead Borrelia test

ECU-oriented models for NOx prediction. Part 2: adaptive estimation by using an NOx sensor

The implantation of nitrogen oxide sensors in diesel engines is necessary in order to track emissions at the engine exhaust line for diagnosis and control of the after-treatment devices. However, the use of models is still necessary since the sensor outputs are delayed and filtered. The present paper deals with the problem of the nitrogen oxide estimation in two parts; Part 1 deals with a control-oriented model for the nitrogen oxide estimation, while Part 2 presents data fusion of the model and the sensor to improve the estimation, which is presented in the following. The use of models for the nitrogen oxide estimation is an alternative but the drift and the ageing are still issues. In order to overcome this problem, the fusion of different signals can be carried out in a smart way by means of a Kalman filter. There exist different ways of presenting this fusion, from directly tracking the bias to updating the model parameters. For this, different algorithms are proposed in this paper with the aim of correcting the model output. Furthermore, the estimation of the actual nitrogen oxide concentration, by preventing sensor delay and filtering, is also integrated in the algorithm, which is a suitable strategy for combining nitrogen oxide sensors and models on an onboard basis.Guardiola, C.; Climent, H.; Pla Moreno, B.; Blanco-Rodriguez, D. (2015). ECU-oriented models for NOx prediction. Part 2: adaptive estimation by using an NOx sensor. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 229(10):1345-1360. doi:10.1177/0954407014561278S134513602291