4,531 research outputs found
Formalin Exposure on the Rats Feeding Diet on Antioxidant Enzymatic activity and Oxidative Damage of Rats Liver Tissue
Using formalin or formaldehyde as a illegal preservative on food and ingredient Is very danger for health because formalin is a toxic and carcinogenic substance that potent as a sources of reactive oxygen species (ROS) and free radical exogenous. The aim of this research was to know the potent of formalin toxicities that exposure through the rats feeding diet on antioxidant enzymatic activity (SOD and GSH) and effect on oxidative damages of rats hepar tissue (MDA). Twenty five of male rats of 8 to 10 weeks old, with the body weigh 100 to 120 g, were divided into 5 groups. Group I was the control group, treated with a standard pellet feeding diet without formalin. Group II, III, IV and V were administrated with treatment feeding diet with formalin content of each were 25 ppm, 50 ppm, 75 ppm and 100 ppm. The result showed that formalin exposure through the feeding diet of rats (Rattus novegicus) affect decreasing highly significantly (P<0,01) on antioxidant enzymatic (GSH) and increasing oxidative damage (MDA) of liver tissue of rat (Rattus norvegicus)
Cramer-Rao Bound for Sparse Signals Fitting the Low-Rank Model with Small Number of Parameters
In this paper, we consider signals with a low-rank covariance matrix which
reside in a low-dimensional subspace and can be written in terms of a finite
(small) number of parameters. Although such signals do not necessarily have a
sparse representation in a finite basis, they possess a sparse structure which
makes it possible to recover the signal from compressed measurements. We study
the statistical performance bound for parameter estimation in the low-rank
signal model from compressed measurements. Specifically, we derive the
Cramer-Rao bound (CRB) for a generic low-rank model and we show that the number
of compressed samples needs to be larger than the number of sources for the
existence of an unbiased estimator with finite estimation variance. We further
consider the applications to direction-of-arrival (DOA) and spectral estimation
which fit into the low-rank signal model. We also investigate the effect of
compression on the CRB by considering numerical examples of the DOA estimation
scenario, and show how the CRB increases by increasing the compression or
equivalently reducing the number of compressed samples.Comment: 14 pages, 1 figure, Submitted to IEEE Signal Processing Letters on
December 201
Subspace Leakage Analysis and Improved DOA Estimation with Small Sample Size
Classical methods of DOA estimation such as the MUSIC algorithm are based on
estimating the signal and noise subspaces from the sample covariance matrix.
For a small number of samples, such methods are exposed to performance
breakdown, as the sample covariance matrix can largely deviate from the true
covariance matrix. In this paper, the problem of DOA estimation performance
breakdown is investigated. We consider the structure of the sample covariance
matrix and the dynamics of the root-MUSIC algorithm. The performance breakdown
in the threshold region is associated with the subspace leakage where some
portion of the true signal subspace resides in the estimated noise subspace. In
this paper, the subspace leakage is theoretically derived. We also propose a
two-step method which improves the performance by modifying the sample
covariance matrix such that the amount of the subspace leakage is reduced.
Furthermore, we introduce a phenomenon named as root-swap which occurs in the
root-MUSIC algorithm in the low sample size region and degrades the performance
of the DOA estimation. A new method is then proposed to alleviate this problem.
Numerical examples and simulation results are given for uncorrelated and
correlated sources to illustrate the improvement achieved by the proposed
methods. Moreover, the proposed algorithms are combined with the pseudo-noise
resampling method to further improve the performance.Comment: 37 pages, 10 figures, Submitted to the IEEE Transactions on Signal
Processing in July 201
Convergence of optimal control problems governed by second kind parabolic variational inequalities
We consider a family of optimal control problems where the control variable
is given by a boundary condition of Neumann type. This family is governed by
parabolic variational inequalities of the second kind. We prove the strong
convergence of the optimal controls and state systems associated to this family
to a similar optimal control problem. This work solves the open problem left by
the authors in IFIP TC7 CSMO2011
Electron-electron and spin-orbit interactions in armchair graphene ribbons
The effects of intrinsic spin-orbit and Coulomb interactions on low-energy
properties of finite width graphene armchair ribbons are studied by means of a
Dirac Hamiltonian. It is shown that metallic states subsist in the presence of
intrinsic spin-orbit interactions as spin-filtered edge states, in contrast
with the insulating behavior predicted for graphene planes. A charge-gap opens
due to Coulomb interactions in neutral ribbons, that vanishes as , with a gapless spin sector. Weak intrinsic spin-orbit interactions do
not change the insulating behavior. Explicit expressions for the
width-dependent gap and various correlation functions are presented.Comment: Will appear in PR
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