The strength and effect of Coulomb correlations in the (superconducting when hydrated) x ≈1/3 regime of NaxCoO2 have been evaluated using the correlated band theory LDA+U method. Our results, neglecting quantum fluctuations, are: (1) there is a critical Uc = 3 eV, above which charge ordering occurs at x=1/3, (2) in this charge-ordered state, antiferromagnetic coupling is favored over ferromagne...

Atomic hydrogen diffuses in semiconductor lattices and binds to impurities by forming complexes that can lead to a full neutralization of the impurity effects. In the present paper, the structural, vibrational, electronic and magnetic properties of complexes formed by H in the MnxGa1−xAs (x=0.03) dilute magnetic semiconductor have been investigated by using first-principles DFT-LSD and LDA+U th...

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...

Linear discriminant analysis (LDA) is one of the most popular methods of classification. For high-dimensional microarray data classification, due to the small number of samples and large number of features, classical LDA has sub-optimal performance corresponding to the singularity and instability of the within-group covariance matrix. Two modified LDA approaches (MLDA and NLDA) were applied for...

Lithium diisopropylamide (LDA)-mediated ortholithiations of 2-fluoropyridine and 2,6-difluoropyridine in tetrahydrofuran at -78 °C were studied using a combination of IR and NMR spectroscopic and computational methods. Rate studies show that a substrate-assisted deaggregation of LDA dimer occurs parallel to an unprecedented tetramer-based pathway. Standard and competitive isotope effects confir...

Linear discriminant analysis (LDA) is one of the most popular classification algorithms for brain-computer interfaces (BCI). LDA assumes Gaussian distribution of the data, with equal covariance matrices for the concerned classes, however, the assumption is not usually held in actual BCI applications, where the heteroscedastic class distributions are usually observed. This paper proposes an enha...