Influence of Block Ratio on Thermal, Optical, and Photovoltaic Properties of Poly(3-hexylthiophene)-b-poly(3-butylthiophene)-b-poly(3-octylthiophene).

Efforts to improve the solar power conversion efficiencies of binary bulk heterojunction-type organic photovoltaic devices using an active layer consisting of a poly-(3-alkylthiophene) (P3AT) homopolymer and a suitable fullerene derivative face barriers caused by the intrinsic properties of homopolymers. To overcome such barriers, researchers might be able to chemically tailor homopolymers by means of monomer ratio-balanced block copolymerization to obtain preferable properties. Triblock copolymers consisting of three components-3-hexylthiophene (HT), 3-butylthiophene (BT), and 3-octylthiophene (OT)-were synthesized via Grignard metathesis (GRIM) polymerization. The component ratios of the synthesized block copolymers were virtually the same as the feeding ratios of the monomers, a fact which was verified using 1H-NMR spectra. All the copolymers exhibited comparable crystalline and melting temperatures, which increased when one type of monomer became dominant. In addition, their power conversion efficiencies and photoluminescence properties were governed by the major components of the copolymers. Interestingly, the HT component-dominated block copolymer indicated the highest power conversion efficiency, comparable to that of its homopolymer, although its molecular weight was significantly shorter.

Identification of cichlid fishes from Lake Malawi using computer vision.

BACKGROUND: The explosively radiating evolution of cichlid fishes of Lake Malawi has yielded an amazing number of haplochromine species estimated as many as 500 to 800 with a surprising degree of diversity not only in color and stripe pattern but also in the shape of jaw and body among them. As these morphological diversities have been a central subject of adaptive speciation and taxonomic classification, such high diversity could serve as a foundation for automation of species identification of cichlids. METHODOLOGY/PRINCIPAL FINDING: Here we demonstrate a method for automatic classification of the Lake Malawi cichlids based on computer vision and geometric morphometrics. For this end we developed a pipeline that integrates multiple image processing tools to automatically extract informative features of color and stripe patterns from a large set of photographic images of wild cichlids. The extracted information was evaluated by statistical classifiers Support Vector Machine and Random Forests. Both classifiers performed better when body shape information was added to the feature of color and stripe. Besides the coloration and stripe pattern, body shape variables boosted the accuracy of classification by about 10%. The programs were able to classify 594 live cichlid individuals belonging to 12 different classes (species and sexes) with an average accuracy of 78%, contrasting to a mere 42% success rate by human eyes. The variables that contributed most to the accuracy were body height and the hue of the most frequent color. CONCLUSIONS: Computer vision showed a notable performance in extracting information from the color and stripe patterns of Lake Malawi cichlids although the information was not enough for errorless species identification. Our results indicate that there appears an unavoidable difficulty in automatic species identification of cichlid fishes, which may arise from short divergence times and gene flow between closely related species.