A new procedure to optimize the selection of groups in a classification tree

Agglomerative cluster analyses encompass many techniques, which have been widely used in various fields of science. In biology, and specifically ecology, datasets are generally highly variable and may contain outliers, which increase the difficulty to identify the number of clusters. Here we present a new criterion to determine statistically the optimal level of partition in a classification tree. The criterion robustness is tested against perturbated data (outliers) using an observation or variable with values randomly generated. The technique, called Random Simulation Test (RST), is tested on (1) the well-known Iris dataset [Fisher, R.A., 1936. The use of multiple measurements in taxonomic problems. Ann. Eugenic. 7, 179–188], (2) simulated data with predetermined numbers of clusters following Milligan and Cooper [Milligan, G.W., Cooper, M.C., 1985. An examination of procedures for determining the number of clusters in a data set. Psychometrika 50, 159–179] and finally (3) is applied on real copepod communities data previously analyzed in Beaugrand et al. [Beaugrand, G., Ibanez, F., Lindley, J.A., Reid, P.C., 2002. Diversity of calanoid copepods in the North Atlantic and adjacent seas: species associations and biogeography. Mar. Ecol. Prog. Ser. 232, 179–195]. The technique is compared to several standard techniques. RST performed generally better than existing algorithms on simulated data and proved to be especially efficient with highly variable datasets.

Ocean Virtual Laboratory: A new way to explore multi-sensor synergy demonstrated over the Agulhas region

Ocean Virtual Laboratory is an ESA-funded project to prototype the concept of a single point of access for all satellite remote-sensing data with ancillary model output and in situ measurements for a given region. The idea is to provide easy access for the non-specialist to both data and state-of-the-art processing techniques and enable their easy analysis and display. The project, led by OceanDataLab, is being trialled in the region of the Agulhas Current, as it contains signals of strong contrast (due to very energetic upper ocean dynamics) and special SAR data acquisitions have been recorded there. The project also encourages the take up of Earth Observation data by developing training material to help those not in large scientific or governmental organizations make the best use of what data are available. The website for access is: http://ovl-project.oceandatalab.com/

A new route to synthesize high degree polythiophene in a room temperature melt medium

Conducting polymers suffer from folds and kinks because of random nucleation and solvation of a free radical cation to yield a cross linked/disordered polymer and therefore a solvent free electrochemical polymerization in a room temperature melt medium is adopted to yield a high degree polymer with high electronic conductivity. Electropolymerization of thiophene was performed on platinum/ITO substrates using cyclic voltametry or galvenostatic mode in chloroaluminate room temperature melt medium to obtain a reddish brown free standing film which can be peeled off from the electrode surface after a minimum of 10 cycles. The conductivity was found to be around 102 S/cm. The degree of polymerization was calculated to be around 44 from IR studies. A layered structure supportive for high degree of polymerization was witnessed from potential step technique. From UV spectra the charge carriers were found to be bipolarons. The morphology of the film was found to be crystalline from SEM and XRD studies. Capacitative impedance properties for doped samples were interpreted from impedance spectroscopy.