A methodology to assess the impact on bees of dust from coated seeds

contribution to session IVTest methodology

Behavior of honey bees; a guideline to assess troubles in bee foraging activity under insect-proof tunnels

contribution to session IVTest methodology

ICPBR-Working Group Risks posed by dusts: overview of the area and recommendations

Background: In 2008 the poisoning of about 12000 bee colonies was reported from Germany. These poisonings were caused by the drift of dust particles containing the insecticidal substance clothianidin following the seeding of maize seeds, inadequately treated with the insecticide Poncho Pro. Results: Investigations were done on the dust load contained in seed packages of different crops, on the experimental abrasion of dust from treated seeds using the Heubach-Dustmeter as well as on the actual dust drift during the sowing operation of treated seeds with different machinery under field conditions. Resistance to abrasion of treated seeds and subsequent dust drift during sowing operations differ significantly between crops, coating recipes and facilities. Furthermore dust drift depends on particle size, sowing technology as well as on environmental conditions (e.g. wind speed, soil humidity). Conclusions: The drift of dust from treated seeds may pose a risk to honeybees, which needs to be appropriately considered within the authorization process of pesticides. The total quantity of abraded dust as well as the actual emission of dust during the sowing operation can be significantly reduced by technical means (e.g. coating recipe and facility equipment, deflector technology) and by additional mitigation measures (e.g. maximum wind speed). Keywords: honeybee, poisoning, risk, seed treatment, dust, drif

Evaluation of Personalised Canine Electromechanical Models

International audienceCardiac modelling aims at understanding cardiac diseases and predicting cardiac responses to therapies. By generating the elec-trical propagation, the contraction and the mechanical response, we are able to simulate cardiac motion from non-invasive imaging techniques. Four healthy canine clinical data (left ventricles) were provided by the STACOM'2014 challenge. Our study is based on Bestel-Clement-Sorine mechanical modelling, while the electrophysiological phenomena is driven by an Eikonal model. Our model has been calibrated by a quantitative sensitivity study as well as a personalized automatic calibration. Results and comparison with clinical measures are shown in terms of left ventricular volume, flow, pressure and ejection fraction

Sparse Bayesian Non-linear Regression for Multiple Onsets Estimation in Non-invasive Cardiac Electrophysiology

Best paper award FIMH 2017, category: ElectrophysiologyInternational audienceIn the scope of modelling cardiac electrophysiology (EP) for understanding pathologies and predicting the response to therapies, patient-specific model parameters need to be estimated. Although per-sonalisation from non-invasive data (body surface potential mapping, BSPM) has been investigated on simple cases mostly with a single pacing site, there is a need for a method able to handle more complex situations such as sinus rhythm with several onsets. In the scope of estimating cardiac activation maps, we propose a sparse Bayesian kernel-based regression (relevance vector machine, RVM) from a large patient-specific simulated database. RVM additionally provides a confidence on the result and an automatic selection of relevant features. With the use of specific BSPM descriptors and a reduced space for the myocardial geometry, we detail this framework on a real case of simultaneous biventricular pacing where both onsets were precisely localised. The obtained results (mean distance to the two ground truth pacing leads is 18.4mm) demonstrate the usefulness of this non-linear approach