An Adaptive Remeshing Procedure for Proximity Maneuvering Spacecraft Formations

We consider a methodology to optimally obtain reconfigurations of spacecraft formations. It is based on the discretization of the time interval in subintervals (called the mesh) and the obtainment of local solutions on them as a result of a variational method. Applied to a libration point orbit scenario, in this work we focus on how to find optimal meshes using an adaptive remeshing procedure and on the determination of the parameter that governs it

Acylation of chiral alcohols: a simple procedure for chiral GC analysis

The use of iodine as a catalyst and either acetic or trifluoroacetic acid as a derivatizing reagent for determining the enantiomeric composition of acyclic and cyclic aliphatic chiral alcohols was investigated. Optimal conditions were selected according to the molar ratio of alcohol to acid, the reaction time, and the reaction temperature. Afterwards, chiral stability of chiral carbons was studied. Although no isomerization was observed when acetic acid was used, partial isomerization was detected with the trifluoroacetic acid. A series of chiral alcohols of a widely varying structural type were then derivatized with acetic acid using the optimal conditions. The resolution of the enantiomeric esters and the free chiral alcohols was measured using a capillary gas chromatograph equipped with a CP Chirasil-DEX CB column. The best resolutions were obtained with 2-pentyl acetates (α = 3.00) and 2-hexyl acetates (α = 1.95). This method provides a very simple and efficient experimental workup procedure for analyzing chiral alcohols by chiral-phase GC.

ICA Cleaning procedure for EEG signals analysis: application to Alzheimer's disease detection

To develop systems in order to detect Alzheimer’s disease we want to use EEG signals. Available database is raw, so the first step must be to clean signals properly. We propose a new way of ICA cleaning on a database recorded from patients with Alzheimer's disease (mildAD, early stage). Two researchers visually inspected all the signals (EEG channels), and each recording's least corrupted (artefact-clean) continuous 20 sec interval were chosen for the analysis. Each trial was then decomposed using ICA. Sources were ordered using a kurtosis measure, and the researchers cleared up to seven sources per trial corresponding to artefacts (eye movements, EMG corruption, EKG, etc), using three criteria: (i) Isolated source on the scalp (only a few electrodes contribute to the source), (ii) Abnormal wave shape (drifts, eye blinks, sharp waves, etc.), (iii) Source of abnormally high amplitude ( �100 �V). We then evaluated the outcome of this cleaning by means of the classification of patients using multilayer perceptron neural networks. Results are very satisfactory and performance is increased from 50.9% to 73.1% correctly classified data using ICA cleaning procedure.