Identification and antifungal susceptibility of a large collection of yeast strains isolated in Tunisian hospitals.

Abstract In this study, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was used as a rapid method to identify yeasts isolated from patients in Tunisian hospitals. When identification could not be exstablished with this procedure, sequencing of the internal transcribed spacer with 5.8S ribosomal DNA (rDNA) (ITS1-5.8S-ITS2) and D1/D2 domain of large-subunit (LSU rDNA) were employed as a molecular approach for species differentiation. Candida albicans was the dominant species (43.37% of all cases), followed by C. glabrata (16.55%), C. parapsilosis (13.23%), C. tropicalis (11.34%), C. dubliniensis (4.96%), and other species more rarely encountered in human diseases such as C. krusei, C. metapsilosis, C. lusitaniae, C. kefyr, C. palmioleophila, C. guilliermondii, C. intermedia, C. orthopsilosis, and C. utilis. In addition, other yeast species were obtained including Saccharomyces cerevisiae, Debaryomyces hansenii (anamorph known as C. famata), Hanseniaspora opuntiae, Kodamaea ohmeri, Pichia caribbica (anamorph known as C. fermentati), Trichosporon spp. and finally a novel yeast species, C. tunisiensis. The in vitro antifungal activities of fluconazole and voriconazole were determined by the agar disk diffusion test and Etest, while the susceptibility to additional antifungal agents was determined with the Sensititre YeastOne system. Our results showed low incidence of azole resistance in C. albicans (0.54%), C. tropicalis (2.08%) and C. glabrata (4.28%). In addition, caspofungin was active against most isolates of the collection with the exception of two K. ohmeri isolates. This is the first report to describe caspofungin resistant isolates of this yeast.

Iowa Egg Council, June 30, 2001 & June 30, 2002

State Agency Audit Report

Art painting Data Collection

The classification of Art painting images is a computer vision applications that isgrowing considerably. The goal of this technology, is to classify an art paintingimage automatically, in terms of artistic style, technique used, or its author. For thispurpose, the image is analyzed extracting some visual features. Many articlesrelated with these problems have been issued, but in general the proposed solutionsare focused in a very specific field. In particular, algorithms are tested using imagesat different resolutions, acquired under different illumination conditions. Thatmakes complicate the performance comparison of the different methods. In thiscontext, it will be very interesting to construct a public art image database, in orderto compare all the existing algorithms under the same conditions. This paperpresents a large art image database, with their corresponding labels according to thefollowing characteristics: title, author, style and technique. Furthermore, a tool thatmanages this database have been developed, and it can be used to extract differentvisual features for any selected image. This data can be exported to a file in CSVformat, allowing researchers to analyze the data with other tools. During the datacollection, the tool stores the elapsed time in the calculation. Thus, this tool alsoallows to compare the efficiency, in computation time, of different mathematicalprocedures for extracting image data.

Catalogue des dessins et estampes... composant la collection de M. L. P. M. Norblin... / [expert] Mannheim

[Vente. Estampes. 1855-02-05. Paris]

Catalogue d'une très-belle collection de tabatières... [collections Prince Demidoff, Comte Potocki] ... vente... 15 février 1861... / [expert] Mannheim

[Vente. Art. 1861-02-15 - 1861-02-16. Paris]

Catalogue d'une précieuse et rare collection de 124 miniatures anciennes... [Guérin-Laurens] / [expert] Mannheim

[Vente. Art. 1860-03-23 - 1860-03-24. Paris]