Discovery of new Milky Way star cluster candidates in the 2MASS point source catalog III. Follow-up observations of cluster candidates in the Galactic Center region

This paper is part of a project to search the inner Milky Way for hidden massive clusters and to address the question of whether our Galaxy still forms clusters similar to the progenitors of the present-day globular clusters. We report high angular resolution deep near-infrared imaging of 21 cluster candidates selected from the catalogues of Bica et al. (2003) and Dutra et al.(2003) in a region around the Galactic Center. These catalogues were created from visual inspection of the 2MASS images. Seven objects appear to be genuine clusters, and for these objects we present estimates of extinction, distance and in some cases age and mass. Our estimated masses range from 1200 to 5500 solar masses. These clusters are thus significantly smaller than any Galactic globular cluster, and indicate that the formation of massive young clusters such as Arches and Quintuplet is not common in the present-day Milky Way. The remaining 14 objects are either not clusters or cannot be classified based on our data.Comment: 8 pages, 19 figures, accepted for publication in A&

Linfadenite tuberculoide em suínos: o que pode ser feito para seu controle.

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Evaluation of SIR-A (Shuttle Imaging Radar) images from the Tres Marias region (Minas Gerais State, Brazil) using derived spatial features and registration with MSS-LANDSAT images

Two image processing experiments are described using a MSS-LANDSAT scene from the Tres Marias region and a shuttle Imaging Radar SIR-A image digitized by a vidicon scanner. In the first experiment the study area is analyzed using the original and preprocessed SIR-A image data. The following thematic classes are obtained: (1) water, (2) dense savanna vegetation, (3) sparse savanna vegetation, (4) reforestation areas and (5) bare soil areas. In the second experiment, the SIR-A image was registered together with MSS-LANDSAT bands five, six, and seven. The same five classes mentioned above are obtained. These results are compared with those obtained using solely MSS-LANDSAT data. The spatial information as well as coregistered SIR-A and MSS-LANDSAT data can increase the separability between classes, as compared to the use of raw SIR-A data solely

Efeito do porta-enxerto na formação de mudas de cajueiro anão precoce cultivadas em tubetes e submetidas a diferentes doses de adubo foliar.

O objetivo do presente trabalho e estudar o comportamento de quatro porta-enxertos com relacao a contribuicao de cada um deles na nutricao, como tambem testar o efeito da adubacao via foliar ...bitstream/CNPAT-2010/5387/1/Pa-069.pd

Estudo da transmissao horizontal de Mycobacterium avium-intracellulare em suinos.

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Evaluation of entropy and JM-distance criterions as features selection methods using spectral and spatial features derived from LANDSAT images

A study area near Ribeirao Preto in Sao Paulo state was selected, with predominance in sugar cane. Eight features were extracted from the 4 original bands of LANDSAT image, using low-pass and high-pass filtering to obtain spatial features. There were 5 training sites in order to acquire the necessary parameters. Two groups of four channels were selected from 12 channels using JM-distance and entropy criterions. The number of selected channels was defined by physical restrictions of the image analyzer and computacional costs. The evaluation was performed by extracting the confusion matrix for training and tests areas, with a maximum likelihood classifier, and by defining performance indexes based on those matrixes for each group of channels. Results show that in spatial features and supervised classification, the entropy criterion is better in the sense that allows a more accurate and generalized definition of class signature. On the other hand, JM-distance criterion strongly reduces the misclassification within training areas

The XDSPRES CL-based package for reducing OSIRIS cross-dispersed spectra

We present a description of the CL-based package XDSPRES, which aims at being a complete reducing facility for cross-dispersed spectra taken with the Ohio State Infrared Imager/Spectrometer, as installed at the SOAR telescope. This instrument provides spectra in the range between 1.2um and 2.35um in a single exposure, with resolving power of R ~ 1200. XDSPRES consists of two tasks, namely xdflat and doosiris. The former is a completely automated code for preparing normalized flat field images from raw flat field exposures. Doosiris was designed to be a complete reduction pipeline, requiring a minimum of user interaction. General steps towards a fully reduced spectrum are explained, as well as the approach adopted by our code. The software is available to the community through the web site http://www.if.ufrgs.br/~ruschel/software.Comment: 14 pages, 10 figure