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The complex aerodynamic footprint of desert locusts revealed by large-volume tomographic particle image velocimetry.

ABSTRACT: Particle image velocimetry has been the preferred experimental technique with which to study the aerodynamics of animal flight for over a decade. In that time, hardware has become more accessible and the software has progressed from the acquisition of planes through the flow field to the reconstruction of small volumetric measurements. Until now, it has not been possible to capture large volumes that incorporate the full wavelength of the aerodynamic track left behind during a complete wingbeat cycle. Here, we use a unique apparatus to acquire the first instantaneous wake volume of a flying animal's entire wingbeat. We confirm the presence of wake deformation behind desert locusts and quantify the effect of that deformation on estimates of aerodynamic force and the efficiency of lift generation. We present previously undescribed vortex wake phenomena, including entrainment around the wing-tip vortices of a set of secondary vortices borne of Kelvin-Helmholtz instability in the shear layer behind the flapping wings.

SUBMITTER: Henningsson P

PROVIDER: S-EPMC4528577 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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The complex aerodynamic footprint of desert locusts revealed by large-volume tomographic particle image velocimetry.

Henningsson Per P Michaelis Dirk D Nakata Toshiyuki T Schanz Daniel D Geisler Reinhard R Schröder Andreas A Bomphrey Richard J RJ

Journal of the Royal Society, Interface 20150701 108

Particle image velocimetry has been the preferred experimental technique with which to study the aerodynamics of animal flight for over a decade. In that time, hardware has become more accessible and the software has progressed from the acquisition of planes through the flow field to the reconstruction of small volumetric measurements. Until now, it has not been possible to capture large volumes that incorporate the full wavelength of the aerodynamic track left behind during a complete wingbeat ...[more]

PMID: 26040598

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Project description:An experimental set-up is presented for the in vitro characterization of the fluid dynamics in personalized phantoms of healthy and stenosed coronary arteries. The proposed set-up was fine-tuned with the aim of obtaining a compact, flexible, low-cost test-bench for biomedical applications. Technically, velocity vector fields were measured adopting a so-called smart-PIV approach, consisting of a smartphone camera and a low-power continuous laser (30 mW). Experiments were conducted in realistic healthy and stenosed 3D-printed phantoms of left anterior descending coronary artery reconstructed from angiographic images. Time resolved image acquisition was made possible by the combination of the image acquisition frame rate of last generation commercial smartphones and the flow regimes characterizing coronary hemodynamics (velocities in the order of 10 cm/s). Different flow regimes (Reynolds numbers ranging from 20 to 200) were analyzed. The smart-PIV approach was able to provide both qualitative flow visualizations and quantitative results. A comparison between smart-PIV and conventional PIV (i.e., the gold-standard experimental technique for bioflows characterization) measurements showed a good agreement in the measured velocity vector fields for both the healthy and the stenosed coronary phantoms. Displacement errors and uncertainties, estimated by applying the particle disparity method, confirmed the soundness of the proposed smart-PIV approach, as their values fell within the same range for both smart and conventional PIV measured data (≈5% for the normalized estimated displacement error and below 1.2 pixels for displacement uncertainty). In conclusion, smart-PIV represents an easy-to-implement, low-cost methodology for obtaining an adequately robust experimental characterization of cardiovascular flows. The proposed approach, to be intended as a proof of concept, candidates to become an easy-to-handle test bench suitable for use also outside of research labs, e.g., for educational or industrial purposes, or as first-line investigation to direct and guide subsequent conventional PIV measurements.

Project description:BackgroundThe technical development of imaging techniques in life sciences has enabled the three-dimensional recording of living samples at increasing temporal resolutions. Dynamic 3D data sets of developing organisms allow for time-resolved quantitative analyses of morphogenetic changes in three dimensions, but require efficient and automatable analysis pipelines to tackle the resulting Terabytes of image data. Particle image velocimetry (PIV) is a robust and segmentation-free technique that is suitable for quantifying collective cellular migration on data sets with different labeling schemes. This paper presents the implementation of an efficient 3D PIV package using the Julia programming language-quickPIV. Our software is focused on optimizing CPU performance and ensuring the robustness of the PIV analyses on biological data.ResultsQuickPIV is three times faster than the Python implementation hosted in openPIV, both in 2D and 3D. Our software is also faster than the fastest 2D PIV package in openPIV, written in C++. The accuracy evaluation of our software on synthetic data agrees with the expected accuracies described in the literature. Additionally, by applying quickPIV to three data sets of the embryogenesis of Tribolium castaneum, we obtained vector fields that recapitulate the migration movements of gastrulation, both in nuclear and actin-labeled embryos. We show normalized squared error cross-correlation to be especially accurate in detecting translations in non-segmentable biological image data.ConclusionsThe presented software addresses the need for a fast and open-source 3D PIV package in biological research. Currently, quickPIV offers efficient 2D and 3D PIV analyses featuring zero-normalized and normalized squared error cross-correlations, sub-pixel/voxel approximation, and multi-pass. Post-processing options include filtering and averaging of the resulting vector fields, extraction of velocity, divergence and collectiveness maps, simulation of pseudo-trajectories, and unit conversion. In addition, our software includes functions to visualize the 3D vector fields in Paraview.

Project description:Phenotypic plasticity allows animals to modify their behavior, physiology, and morphology to adapt to environmental change. The global pest, the desert locust, shows two extreme phenotypes; a solitarious phase that is relatively harmless and a gregarious phase that forms swarms and causes extensive agricultural and economic damage. In the field, environmental conditions can drive isolated animals into crowded populations and previous studies have identified the biogenic amine serotonin as a key determinant of this transition. Here we take an integrated approach to investigate the neurochemical, physiological, and behavioral correlates defined by a laboratory based paradigm that mimics facets of swarm break down as gregarious locusts become isolated. Following isolation there was an increased propensity of locusts to avoid conspecifics, and show a reduced locomotion. Changes in choice behavior occurred within 1 h of isolation although isolation-related changes progressed with increased isolation time. Isolation was accompanied by changes in the levels of the biogenic amines dopamine, octopamine, and serotonin within the CNS within 1 h. Dopamine levels were higher in isolated animals and we focused on the role played by this transmitter in synaptic changes that may underpin solitarization. Dopamine reduced synaptic efficacy at a key central synapse between campaniform sensilla (CS) and a fast extensor tibiae motor neuron that is involved in limb movement. We also show that dopamine injection into the haemocoel was sufficient to induce solitarious-like behavior in otherwise gregarious locusts. Further, injection of a dopamine antagonist, fluphenazine, into isolated locusts induced gregarious-like behavior. This highlights that dopaminergic modulation plays an important role in the plasticity underpinning phase transition and sets a context to deepen the understanding of the complementary role that distinct neuromodulators play in polyphenism in locusts.

Dataset Information

The complex aerodynamic footprint of desert locusts revealed by large-volume tomographic particle image velocimetry.

Publications

The complex aerodynamic footprint of desert locusts revealed by large-volume tomographic particle image velocimetry.

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