INSPEX: design and integration of a portable/wearable smart spatial exploration system

The INSPEX H2020 project main objective is to integrate automotive-equivalent spatial exploration and obstacle detection functionalities into a portable/wearable multi-sensor, miniaturised, low power device. The INSPEX system will detect and localise in real-time static and mobile obstacles under various environmental conditions in 3D. Potential applications range from safer human navigation in reduced visibility, small robot/drone obstacle avoidance systems to navigation for the visually/mobility impaired, this latter being the primary use-case considered in the project

Selection of orthogonal reversed-phase HPLC systems by univariate and auto-associative multivariate regression trees

In order to select chromatographic starting conditions to be optimized during further method development of the separation of a given mixture, so-called generic orthogonal chromatographic systems could be explored in parallel. In this paper the use of univariate and multivariate regression trees (MRT) was studied to define the most orthogonal subset from a given set of chromatographic systems. Two data sets were considered, which contain the retention data of 68 structurally diversive drugs on sets of 32 and 38 chromatographic systems, respectively. For both the univariate and multivariate approaches no other data but the measured retention factors are needed to build the decision trees. Since multivariate regression trees are used in an unsupervised way, they are called auto-associative multivariate regression trees (AAMRT). For all decision trees used, a variable importance list of the predictor variables can be derived. It was concluded that based on these ranked lists, both for univariate and multivariate regression trees, a selection of the most orthogonal systems from a given set of systems can be obtained in a user-friendly and fast way

Evaluation of chemometric techniques to select orthogonal chromatographic systems.

Several chemometric techniques were compared for their performance to determine the orthogonality and similarity between chromatographic systems. Pearson's correlation coefficient (r) based color maps earlier were used to indicate selectivity differences between systems. These maps, in which the systems were ranked according to decreasing or increasing dissimilarities observed in the weighted-average-linkage dendrogram, were now applied as reference method. A number of chemometric techniques were evaluated as potential alternative (visualization) methods for the same purpose. They include hierarchical clustering techniques (single, complete, unweighted-average-linkage, centroid and Ward's method), the Kennard and Stone algorithm, auto-associative multivariate regression trees (AAMRT), and the generalized pairwise correlation method (GPCM) with McNemar's statistical test. After all, the reference method remained our preferred technique to select orthogonal and identify similar systems.info:eu-repo/semantics/publishe

Lessons learnt on exposure assessment process after a chemical incident: case study of the contamination patterns of acrylonitrile

Background: A train which was transporting chemicals derailed and exploded on the 4th of May, 2013 in Wetteren, Belgium. Objective: To describe the trends of air distribution and concentration of acrylonitrile (ACN) in order to determine environmental contamination in the areas exposed to ACN. Methods: Ambient air monitoring was used to describe the exposure of ACN. Samples of ACN air concentrations from indoor and outdoor locations were collected during the three weeks following the train accident. A series of maps showing the distribution and concentration, and thus exposure hotspots, were produced with ArcGIS. Statistical hypothesis tests were used to establish whether differences existed between the ACN air concentration samples collected from these places. Potential risk levels were defined according to the “Intervention Values for Emergency Response” (French and Dutch limit values were available and used in 2013). Results: Of the 3006 geo-referenced samples, four areas presented high and alarming levels of ACN concentrations in the air (> 90 ppm) namely, near the train accident, in the sewers and nearby the Waste Water Treatment Plant (WWTP). Polluted environments which were categorised as having an immediate risk level were in sewers leading from the site of the train accident to the WWTP through the city (330 ppm), directly above manhole covers (196 ppm) and in private bathrooms and lavatories (98 ppm). Findings showed peaks of ACN concentration up to seventeen days after the release of the chemical as well as at a distance from the train accident. Discussion and conclusion: The data description analysis provides further information about the demarcation of risk areas and the routes of ACN distribution. Besides air contamination, water was a significant pathway for ACN and water must therefore considered during the process of exposure assessment. The distribution of ACN concentrations collected in this study, which was based on environmental monitoring, were in line with previous studies conducted on human biomonitoring. The results are able to determine an anticipatory approach directly focusing on the identification of environmental areas at risk during a chemical exposure and to show that individuals were exposed to high levels of concentration in various places.info:eu-repo/semantics/publishe