5,012 research outputs found
Classificação de embriões bovinos produzidos in vivo.
bitstream/item/65449/1/COT-59-Classificacao-de-embrioes.pd
Optimal Cosmic-Ray Detection for Nondestructive Read Ramps
Cosmic rays are a known problem in astronomy, causing both loss of data and
data inaccuracy. The problem becomes even more extreme when considering data
from a high-radiation environment, such as in orbit around Earth or outside the
Earth's magnetic field altogether, unprotected, as will be the case for the
James Webb Space Telescope (JWST). For JWST, all the instruments employ
nondestructive readout schemes. The most common of these will be "up the ramp"
sampling, where the detector is read out regularly during the ramp. We study
three methods to correct for cosmic rays in these ramps: a two-point difference
method, a deviation from the fit method, and a y-intercept method. We apply
these methods to simulated nondestructive read ramps with single-sample groups
and varying combinations of flux, number of samples, number of cosmic rays,
cosmic-ray location in the exposure, and cosmic-ray strength. We show that the
y-intercept method is the optimal detection method in the read-noise-dominated
regime, while both the y-intercept method and the two-point difference method
are best in the photon-noise-dominated regime, with the latter requiring fewer
computations.Comment: To be published in PASP. This paper is 12 pages long and includes 15
figure
Random walks in directed modular networks
Because diffusion typically involves symmetric interactions, scant attention
has been focused on studying asymmetric cases. However, important networked
systems underlain by diffusion (e.g. cortical networks and WWW) are inherently
directed. In the case of undirected diffusion, it can be shown that the
steady-state probability of the random walk dynamics is fully correlated with
the degree, which no longer holds for directed networks. We investigate the
relationship between such probability and the inward node degree, which we call
efficiency, in modular networks. Our findings show that the efficiency of a
given community depends mostly on the balance between its ingoing and outgoing
connections. In addition, we derive analytical expressions to show that the
internal degree of the nodes do not play a crucial role in their efficiency,
when considering the Erd\H{o}s-R\'enyi and Barab\'asi-Albert models. The
results are illustrated with respect to the macaque cortical network, providing
subsidies for improving transportation and communication systems
Pursuing Parameters for Critical Density Dark Matter Models
We present an extensive comparison of models of structure formation with
observations, based on linear and quasi-linear theory. We assume a critical
matter density, and study both cold dark matter models and cold plus hot dark
matter models. We explore a wide range of parameters, by varying the fraction
of hot dark matter , the Hubble parameter and the spectral
index of density perturbations , and allowing for the possibility of
gravitational waves from inflation influencing large-angle microwave background
anisotropies. New calculations are made of the transfer functions describing
the linear power spectrum, with special emphasis on improving the accuracy on
short scales where there are strong constraints. For assessing early object
formation, the transfer functions are explicitly evaluated at the appropriate
redshift. The observations considered are the four-year {\it COBE} observations
of microwave background anisotropies, peculiar velocity flows, the galaxy
correlation function, and the abundances of galaxy clusters, quasars and damped
Lyman alpha systems. Each observation is interpreted in terms of the power
spectrum filtered by a top-hat window function. We find that there remains a
viable region of parameter space for critical-density models when all the dark
matter is cold, though must be less than 0.5 before any fit is found and
significantly below unity is preferred. Once a hot dark matter component is
invoked, a wide parameter space is acceptable, including . The
allowed region is characterized by \Omega_\nu \la 0.35 and 0.60 \la n \la
1.25, at 95 per cent confidence on at least one piece of data. There is no
useful lower bound on , and for curious combinations of the other parameters
it is possible to fit the data with as high as 0.65.Comment: 19 pages LaTeX file (uses mn.sty). Figures *not* included due to
length. We strongly recommend obtaining the full paper, either by WWW at
http://star-www.maps.susx.ac.uk/papers/lsstru_papers.html (UK) or
http://www.bartol.udel.edu/~bob/papers (US), or by e-mailing ARL. Final
version, to appear MNRAS. Main revision is update to four-year COBE data.
Miscellaneous other changes and reference updates. No significant changes to
principal conclusion
The use of GIS and additional information to check soil classification maps.
The aim of this work was to check the limits of the soil classification map using GlS tools and additional information. The information from the geology map, the digital elevation model, Aster images and the detailed soil classification map was used to establish the criteria for automatic classification, using some classification attributes as local elevation, slope and pixels values in images. The new reclassified soil map was compared to the original, and sampling was performed in points in field where the maps didn't match to access the quality of results. The results showed that this method is a promising tool to obtain better quality in digital soil information and to direct sampling, but the accuracy may be limited by the resolution of the available data, and field validation is necessary
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