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 $\Omega_{\nu}$, the Hubble parameter $h$ and the spectral index of density perturbations $n$, 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 $h$ must be less than 0.5 before any fit is found and $n$ significantly below unity is preferred. Once a hot dark matter component is invoked, a wide parameter space is acceptable, including $n\simeq 1$. 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 $h$, and for curious combinations of the other parameters it is possible to fit the data with $h$ 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