A characterization of the scientific impact of Brazilian institutions

In this paper we studied the research activity of Brazilian Institutions for all sciences and also their performance in the area of physics between 1945 and December 2008. All the data come from the Web of Science database for this period. The analysis of the experimental data shows that, within a nonextensive thermostatistical formalism, the Tsallis \emph{q}-exponential distribution $N(c)$ can constitute a new characterization of the research impact for Brazilian Institutions. The data examined in the present survey can be fitted successfully by applying a universal curve namely, $N(c) \propto 1/[1+(q-1) c/T]^{\frac{1}{q-1}}$ with $q\simeq 4/3$ for {\it all} the available citations $c$, $T$ being an "effective temperature". The present analysis ultimately suggests that via the "effective temperature" $T$, we can provide a new performance metric for the impact level of the research activity in Brazil, taking into account the number of the publications and their citations. This new performance metric takes into account the "quantity" (number of publications) and the "quality" (number of citations) for different Brazilian Institutions. In addition we analyzed the research performance of Brazil to show how the scientific research activity changes with time, for instance between 1945 to 1985, then during the period 1986-1990, 1991-1995, and so on until the present. Finally, this work intends to show a new methodology that can be used to analyze and compare institutions within a given country.Comment: 7 pages, 5 figure

Homotheties and topology of tangent sphere bundles

We prove a Theorem on homotheties between two given tangent sphere bundles $S_rM$ of a Riemannian manifold $M,g$ of $\dim\geq 3$, assuming different variable radius functions $r$ and weighted Sasaki metrics induced by the conformal class of $g$. New examples are shown of manifolds with constant positive or with constant negative scalar curvature, which are not Einstein. Recalling results on the associated almost complex structure $I^G$ and symplectic structure ${\omega}^G$ on the manifold $TM$, generalizing the well-known structure of Sasaki by admitting weights and connections with torsion, we compute the Chern and the Stiefel-Whitney characteristic classes of the manifolds $TM$ and $S_rM$.Comment: 15 pages, to appear in Journal of Geometr

Are citations of scientific papers a case of nonextensivity ?

The distribution $N(x)$ of citations of scientific papers has recently been illustrated (on ISI and PRE data sets) and analyzed by Redner [Eur. Phys. J. B {\bf 4}, 131 (1998)]. To fit the data, a stretched exponential ($N(x) \propto \exp{-(x/x_0)^{\beta}}$) has been used with only partial success. The success is not complete because the data exhibit, for large citation count $x$, a power law (roughly $N(x) \propto x^{-3}$ for the ISI data), which, clearly, the stretched exponential does not reproduce. This fact is then attributed to a possibly different nature of rarely cited and largely cited papers. We show here that, within a nonextensive thermostatistical formalism, the same data can be quite satisfactorily fitted with a single curve (namely, $N(x) \propto 1/[1+(q-1) \lambda x]^{q/{q-1}}$ for the available values of $x$. This is consistent with the connection recently established by Denisov [Phys. Lett. A {\bf 235}, 447 (1997)] between this nonextensive formalism and the Zipf-Mandelbrot law. What the present analysis ultimately suggests is that, in contrast to Redner's conclusion, the phenomenon might essentially be one and the same along the entire range of the citation number $x$.Comment: Revtex,1 Figure postscript;[email protected]

A Neural Network Gravitational Arc Finder based on the Mediatrix filamentation Method

Automated arc detection methods are needed to scan the ongoing and next-generation wide-field imaging surveys, which are expected to contain thousands of strong lensing systems. Arc finders are also required for a quantitative comparison between predictions and observations of arc abundance. Several algorithms have been proposed to this end, but machine learning methods have remained as a relatively unexplored step in the arc finding process. In this work we introduce a new arc finder based on pattern recognition, which uses a set of morphological measurements derived from the Mediatrix Filamentation Method as entries to an Artificial Neural Network (ANN). We show a full example of the application of the arc finder, first training and validating the ANN on simulated arcs and then applying the code on four Hubble Space Telescope (HST) images of strong lensing systems. The simulated arcs use simple prescriptions for the lens and the source, while mimicking HST observational conditions. We also consider a sample of objects from HST images with no arcs in the training of the ANN classification. We use the training and validation process to determine a suitable set of ANN configurations, including the combination of inputs from the Mediatrix method, so as to maximize the completeness while keeping the false positives low. In the simulations the method was able to achieve a completeness of about 90% with respect to the arcs that are input to the ANN after a preselection. However, this completeness drops to $\sim$ 70% on the HST images. The false detections are of the order of 3% of the objects detected in these images. The combination of Mediatrix measurements with an ANN is a promising tool for the pattern recognition phase of arc finding. More realistic simulations and a larger set of real systems are needed for a better training and assessment of the efficiency of the method.Comment: Updated to match published versio

O aplicativo computacional "Irrigafácil" implementado via web para o manejo de irrigação dos campos experimentais da Embrapa Milho e Sorgo.

bitstream/item/79197/1/ct-203.pd

A necessidade de irrigar o milho.

bitstream/item/73151/1/Necessidade-irrigar.pd

Estratégias de manejo de irrigação: exemplos de cálculo.

bitstream/item/25532/1/Circ-136.pd