Weighted and robust learning of subspace representations

A reliable system for visual learning and recognition should enable a selective treatment of individual parts of input data and should successfully deal with noise and occlusions. These requirements are not satisfactorily met when visual learning is approached by appearance-based modeling of objects and scenes using the traditional PCA approach. In this paper we extend standard PCA approach to overcome these shortcomings. We first present a weighted version of PCA, which, unlike the standard approach, considers individual pixels and images selectively, depending on the corresponding weights. Then we propose a robust PCA method for obtaining a consistent subspace representation in the presence of outlying pixels in the training images. The method is based on the EM algorithm for estimation of principal subspaces in the presence of missing data. We demonstrate the efficiency of the proposed methods in a number of experiments.     

Synthesis and Evaluation of N‐Phenylpyrrolamides as DNA Gyrase B Inhibitors

ATP‐competitive inhibitors of DNA gyrase and topoisomerase IV are among the most interesting classes of antibacterial drugs that are unrepresented in the antibacterial pipeline. We developed 32 new N‐phenylpyrrolamides and evaluated them against DNA gyrase and topoisomerase IV from E. coli and Staphylococcus aureus. Antibacterial activities were studied against Gram‐positive and Gram‐negative bacterial strains. The most potent compound displayed an IC₅₀ of 47 nm against E. coli DNA gyrase, and a minimum inhibitory concentration (MIC) of 12.5 μm against the Gram‐positive Enterococcus faecalis. Some compounds displayed good antibacterial activities against an efflux‐pump‐deficient E. coli strain (MIC=6.25 μm ) and against wild‐type E. coli in the presence of efflux pump inhibitor PAβN (MIC=3.13 μm ). Here we describe new findings regarding the structure–activity relationships of N‐phenylpyrrolamide DNA gyrase B inhibitors and investigate the factors that are important for the antibacterial activity of this class of compounds.     

Combining reconstructive and discriminative subspace methods for robust classification and regression by subsampling

Linear subspace methods that provide sufficient reconstruction of the data, such as PCA, offer an efficient way of dealing with missing pixels, outliers, and occlusions that often appear in the visual data. Discriminative methods, such as LDA, which, on the other hand, are better suited for classification tasks, are highly sensitive to corrupted data. We present a theoretical framework for achieving the best of both types of methods: an approach that combines the discrimination power of discriminative methods with the reconstruction property of reconstructive methods which enables one to work on subsets of pixels in images to efficiently detect and reject the outliers. The proposed approach is therefore capable of robust classification with a high-breakdown point. We also show that subspace methods, such as CCA, which are used for solving regression tasks, can be treated in a similar manner. The theoretical results are demonstrated on several computer vision tasks showing that the proposed approach significantly outperforms the standard discriminative methods in the case of missing pixels and images containing occlusions and outliers.     

Ag5Pb2O6/CuO Composite, an Approach to Ambient Temperature Superconductivity

Byström?CEvers compound Ag₅Pb₂O₆ is highly conducting oxide, and it was prepared from the components Ag₂O and PbO₂ fired in a 300 bar O₂ atmosphere and 623 K. Compound was milled, and particles were dispersed in a powdered CuO matrix. For low concentrations of metallic particles (<38 w/w percents), the composite is semiconductor or insulator, while for concentrations >48 w/w percents material is metallic down to liquid helium temperatures. For intermediate concentrations, the composite exhibits properties characteristic for superconductors with transition temperatures 178 K<T _c<356 K, dependent on the size of dissolved metallic particles and their mutual distance. Magnetic data support a presumption of novel superconductivity. Samples were prepared with SC transition temperature T _c=138 K, and in the temperature range 145?C800 K electric resistance obeys the temperature dependence ln?R??(T ₀/T)^1/2, and this indicates a possible 1-dimensional conduction mechanism.