OBJECTIVES The objectives of this study are to examine the efficacy and safety of low-dose aspirin (LDA) vs LDA plus low-intensity warfarin (LDA + W) in the primary thrombosis prevention of aPL-positive patients with SLE and/or obstetric morbidity and the role of clinical and serological markers in the development of thrombosis. METHODS In this 5-year prospective, randomized, open, controlled...

The identification and discrimination of 2 closely related and morphologically similar species of Gyrodactylus, G. salaris and G. thymalli, were assessed using the statistical classification methodologies Linear Discriminant Analysis (LDA) and k-Nearest Neighbours (KNN). These statistical methods were applied to morphometric measurements made on the gyrodactylid attachment hooks. The mean estim...

Source-normalised Linear Discriminant Analysis (SNLDA) was recently introduced to improve speaker recognition using i-vectors extracted from multiple speech sources. SNLDA normalises for the effect of speech source in the calculation of the between-speaker covariance matrix. Sourcenormalised-and-weighted (SNAW) LDA computes a weighted average of source-normalised covariance matrices to better e...

We calculate the electronic structure of several atoms and small molecules by direct minimization of the Self-Interaction Corrected Local Density Approximation (SIC-LDA) functional. To do this we rst derive an expression for the gradient of this functional under the constraint that the orbitals be orthogonal and show that previously given expressions do not correctly incorporate this constraint...

In latent Dirichlet allocation (LDA), topics are multinomial distributions over the entire vocabulary. However, the vocabulary usually contains many words that are not relevant in forming the topics. We adopt a variable selection method widely used in statistical modeling as a dimension reduction tool and combine it with LDA. In this variable selection model for LDA (vsLDA), topics are multinom...

We calculate the electronic structure of several atoms and small molecules by direct minimization of the self-interaction-corrected–local-density-approximation ~SIC-LDA! functional. To do this, we first derive an expression for the gradient of this functional under the constraint that the orbitals be orthogonal and then show that previously given expressions do not correctly incorporate this co...

To clarify the pathophysiology of left displaced abomasum (LDA), beef cattle fed high-starch diets were examined. The abomasal pH in beef cattle with LDA was lower than that in non-LDA reference animals (data from beef cattle at an abattoir), suggesting that it facilitated acidity. Bacteriological examinations of the abomasal fluid in cattle with LDA revealed the presence of Pseudomonas spp., C...

Linear Discriminant Analysis (LDA) technique is an important and well-developed area of image recognition and to date many linear discrimination methods have been put forward. Despite these efforts, there persist in the traditional LDA some weaknesses. In this paper, we propose a new LDA-based method called Block LDA (BLDA) that can outperform the traditional Linear Dicriminant Analysis (LDA) m...

The consumption of low-dose aspirin (LDA) to prevent cardiovascular disease continues to increase worldwide. Consequently, the number of chronic LDA users seeking dental procedures that require complementary acute anti-inflammatory medication has also grown. Considering the lack of literature evaluating this interaction, we analyzed the gastric and renal effects caused by a selective COX-2 inhi...

Linear Discriminant Analysis (LDA) is among the most optimal dimension reduction methods for classification, which provides a high degree of class separability for numerous applications from science and engineering. However, problems arise with this classical method when one or both of the scatter matrices is singular. Singular scatter matrices are not unusual in many applications, especially f...