AIM To investigate the effect of abciximab on microvascular integrity and left ventricular (LV) functional recovery in patients with acute myocardial infarction (MI) treated by primary coronary angioplasty (PTCA). METHODS AND RESULTS Thirty-one patients (27 males; age 39-76 years) with first, acute MI (<6 h after onset) were randomized to receive either abciximab+primary PTCA (n=17) or primar...

OBJECTIVE The aim of this study was to evaluate the value of real-time myocardial contrast echocardiography (RT-MCE) for detecting coronary microcirculation (CM) function in coronary artery disease (CAD) patients. METHODS Sixty-five consecutive patients were divided into CAD (n=52) and no-CAD (n=13) groups using coronary angiography (CAG). All patients underwent RT-MCE at rest and CAG within ...

AIMS We hypothesized that molecular imaging of endothelial P-selectin expression with targeted myocardial contrast echocardiography (MCE) could identify recently ischaemic myocardium without infarction. METHODS AND RESULTS The microvascular behaviour of P-selectin-targeted (MB(p)) and control (MB(c)) microbubbles was assessed by intravital microscopy of the cremaster muscle in mice. Targeted ...

U p to 30% of patients with acute myocardial infarction (AMI) treated with reperfusion and with an apparently successful result have microvascular dysfunction. Multiple techniques are available for the diagnosis of this condition, but little information is available comparing their ability to predict ventricular recovery after AMI. The objective of our study was to compare the accuracy of myoca...

Discriminative training of hidden Markov models (HMMs) using segmental minimum classi cation error (MCE) training has been shown to work extremely well for certain speech recognition applications. It is, however, somewhat prone to overspecialization. This study investigates various techniques which improve performance and generalization of the MCE algorithm. Improvements of up to 7% in relative...

This article shows that the Minimum Classification Error (MCE) criterion function commonly used for discriminative design of speech recognition systems is equivalent to a Parzen window based estimate of the theoretical Bayes classification risk. In this analysis, each training token is mapped to the center of a Parzen kernel in the domain of a suitably defined random variable. The kernels are s...

We discuss some inference problems associated with the fractional Ornstein-Uhlenbeck (fO-U) process driven by the fractional Brownian motion (fBm). In particular, we are concerned with the estimation of the drift parameter, assuming that the Hurst parameter H is known and is in [1/2, 1). Under this setting we compute the distributions of the maximum likelihood estimator (MLE) and the minimum co...

The concept of multifunctional use of marine offshore areas receives increased significance in the light of sustainable development in heavily used marine areas. Here we defined potential areas in the German EEZ for the co-utilization of offshore wind farms and offshore aquaculture applying integrated multi-trophic aquaculture (IMTA) approaches. We combined a geographic information system (GIS)...

In this paper, we extend the Maximum Likelihood (ML) training algorithm to the Minimum Classiica-tion Error (MCE) training algorithm for discriminatively estimating the state-dependent polynomial coeecients in the stochastic trajectory model or the trended HMM originally proposed in 2]. The main motivation of this extension is the new model space for smoothness-constrained, state-bound speech t...

Both microwave absorption and magnetocaloric effect (MCE) are two essential performances of magnetic materials. We observe that LaFe(11.6)Si(1.4)C(0.2)H(1.7) intermetallic compound exhibits the advantages of both giant microwave absorption exceeding -42 dB and magnetic entropy change of -20 Jkg(-1)K(-1). The excellent electromagnetic wave absorption results from the large magnetic loss and diel...