Forecasting sudden changes in environmental pollution patterns

The lack of reliable forecasts for the spread of oceanic and atmospheric contamination hinders the effective protection of the ecosystem, society, and the economy from the fallouts of environmental disasters. The consequences can be dire, as evidenced by the Deepwater Horizon oil spill in the Gulf of Mexico in 2010. We present a methodology to predict major short-term changes in environmental contamination patterns, such as oil spills in the ocean and ash clouds in the atmosphere. Our approach is based on new mathematical results on the objective (frame-independent) identification of key material surfaces that drive tracer mixing in unsteady, finite-time flow data. Some of these material surfaces, known as Lagrangian coherent structures (LCSs), turn out to admit highly attracting cores that lead to inevitable material instabilities even under future uncertainties or unexpected perturbations to the observed flow. These LCS cores have the potential to forecast imminent shape changes in the contamination pattern, even before the instability builds up and brings large masses of water or air into motion. Exploiting this potential, the LCS-core analysis developed here provides a model-independent forecasting scheme that relies only on already observed or validated flow velocities at the time the prediction is made. We use this methodology to obtain high-precision forecasts of two major instabilities that occurred in the shape of the Deepwater Horizon oil spill. This is achieved using simulated surface currents preceding the prediction times and assuming that the oil behaves as a passive tracer.     

Looking for a Learning Curve in EVAR Based on the Zenith Stent Graft

The purpose of this study was to report the learning curve of endovascular aneurysm repair (EVAR) based on the Zenith stent graft (Cook Medical Inc., Bloomington, IN). In the last 9 years, 101 patients were treated with a Zenith stent graft. To display the learning curve, a cumulative sum (CUSUM) failure analysis curve of the 30-day technical success rate was calculated. For detailed analysis, our EVAR patient cohort was chronologically divided into three groups. Technical and clinical results, basic patient parameters, and procedural data were compared. The CUSUM graph indicated an initial sharp rise within the first 35 cases and a plateau thereafter. The 30-day technical success rate significantly increased from the first to the second group (83 vs. 100%; p = 0.019), as did the primary technical success rate (66 vs. 97%; p = 0.001). EVAR based on the Zenith stent graft required ∼35 cases to reach a stably high rate of short-term technical success.