Electrochemical detection and degradation of ibuprofen from water on multi-walled carbon nanotubes-epoxy composite electrode

This work describes the electrochemical behaviour of ibuprofen on two types of multi-walled carbon nanotubes based composite electrodes,i.e.,multi-walled carbon nanotubes-epoxy(MWCNT) and silver-modified zeolite-multi-walled carbon nanotubes-epoxy(AgZMWCNT) composites electrodes.The composite electrodes were obtained using two-roll mill procedure.SEM images of surfaces of the composites revealed a homogeneous distribution of the composite components within the epoxy matrix.AgZMWCNT composite electrode exhibited the better electrical conductivity and larger electroactive surface area.The electrochemical determination of ibuprofen(IBP) was achieved using AgZMWCNT by cyclic voltammetry,differential-pulsed voltammetry,square-wave voltammetry and chronoamperometry.The IBP degradation occurred on both composite electrodes under controlled electrolysis at 1.2 and 1.75 V vs.Ag/AgCl,and IBP concentration was determined comparatively by differential-pulsed voltammetry,under optimized conditions using AgZMWCNT electrode and UV-Vis spectrophotometry methods to determine the IBP degradation performance for each electrode.AgZMWCNT electrode exhibited a dual character allowing a double application in IBP degradation process and its control.     

Flower formation induced by kinetin and vitamin E treatment in long-day plant (Arabidopsis thaliana) grown in short day

The Science of Nature -     

Fuzzy clustering analysis of the first 10 MEIC chemicals

In this paper, we discuss the classification results of the toxicological responses of 32 in vivo and in vitro test systems to the first 10 MEIC chemicals. In this order we have used different fuzzy clustering algorithms, namely hierarchical fuzzy clustering, hierarchical and horizontal fuzzy characteristics clustering and a new clustering technique, namely fuzzy hierarchical cross-classification. The characteristics clustering technique produces fuzzy partitions of the characteristics (chemicals) involved and thus it is a useful tool for studying the (dis)similarities between different chemicals and for essential chemicals selection. The cross-classification algorithm produces not only a fuzzy partition of the test systems analyzed, but also a fuzzy partition of the considered 10 MEIC (multicentre evaluation of in vitro cytotoxicity) chemicals. In this way it is possible to identify which chemicals are responsible for the similarities or differences observed between different groups of test systems. In another way, there is a specific sensitivity of a chemical for one or more toxicological tests.