Previously, we reported that hyposmotic swelling evoked transient vascular smooth muscle cell (SMC) contraction that was completely abolished by L-type Ca(2+) channel blockers. In contrast, sustained contraction revealed in hyper- and isoosmotically-shrunken SMCs was insensitive to L-type channel blockers and was diminished in Ca(2+)-free medium by only 30-50%. Several research groups reported ...

Shrunken Pore Syndrome was recently suggested for the pathophysiologic state in patients characterized by an estimation of their glomerular filtration rate (GFR) based upon cystatin  C, which is lower or equal to 60% of their estimated GFR based upon creatinine, i.e. when eGFR cystatin  C ≤ 60% of eGFR creatinine. Not only the cystatin C level, but also the levels of other low molecular mass pr...

Stein’s result has transformed common belief in statistical world that the maximum likelihood estimator, which is in common use for more than a century, is optimal. Charles Stein showed in 1955 that it is possible to uniformly improve the maximum likelihood estimator (MLE) for the Gaussian model in terms of total squared error risk when several parameters are estimated simultaneously from indep...

We prove that the quasi-score estimator in a mean-variance model is optimal in the class of (unbiased) linear score estimators, in the sense that the difference of the asymptotic covariance matrices of the linear score and quasi-score estimator is positive semi-definite. We also give conditions under which this difference is zero or under which it is positive definite. This result can be applie...

This paper shows how a multivariate Bayes estimator can be adjusted to satisfy a set of linear constraints. In the direct approach, the constraint is enforced by a restriction on the class of admissible estimators. In an alternative approach, the constraint is merely encouraged by a mixed risk function which penalises misbalance between the estimator and the constraint. The adjustment to the op...

The standard estimator used in conjunction with importance sampling in Monte Carlo integration is unbiased but inefficient. An alternative estimator is discussed, based on the idea of a difference estimator, which is asymptotically optimal. The improved estimator uses the importance weight as a control variate, as previously studied by Hesterberg (Ph.D. Dissertation, Stanford University (1988);...

AbstructWe consider the problem of estimating the order of a stationary ergodic Markov chain. Our focus is on estimators which satisfy a generalized Neyman-Pearson criterion of optimality. Specifically, the optimal estimator minimizes the probability of underestimation among all estimators with probability of overestimation not exceeding a given value. Our main result identifies the best expone...

This paper proposes a model averaging method based on Kullback-Leibler distance under a homoscedastic normal error term. The resulting model average estimator is proved to be asymptotically optimal. When combining least squares estimators, the model average estimator is shown to have the same large sample properties as the Mallows model average (MMA) estimator developed by Hansen (2007). We sho...

In this article, we present an approach towards a new nonintrusive speech quality estimator. The proposed method facilitates the evaluation of speech telephony services and provides diagnostic information by assessing dimensions of the perceptual quality space. One of these quality dimensions is Loudness, which describes a non optimal sound level. As an important part of the proposed model, a n...

We consider the problem of estimating, in the presence of model uncertainties, a random vector x that is observed through a linear transformation H and corrupted by additive noise. We first assume that both the covariance of x and the transformation H are not completely specified, and develop the linear estimator that minimizes the worst-case mean-squared error (MSE) across all possible covaria...