the purpose of this paper is to analyze in detail a special nonlinear partial differentialequation (npde) of the second order which is important in physical, chemical and technicalapplications. the present npde describes nonlinear diffusion and is of interest in several partsof physics, chemistry and engineering problems alike. since nature is not linear intrinsicallythe nonlinear case is there...

the objective of research was to explore the suitability of lipids like compritol 888 ato and stearic acid as release retardant to develop sustained release (sr) tablets. the sr micromatrices of lipid (s) and glipizide were prepared (lm1- lm6) as intermediate product by fusion method and assessed for various pharmacotechnical properties. micromatrices were formulated as sr tablets (f1-f6) by di...

Sparse representations are widely used tools in image super-resolution (SR) tasks. In the sparsity-based SR methods, linear sparse representations are often used for image description. However, the non-linear data distributions in images might not be well represented by linear sparse models. Moreover, many sparsity-based SR methods require the image patch self-similarity assumption; however, th...

Spectral methods have recently emerged as a powerful tool for dimensionality reduction and manifold learning. These methods use information contained in the eigenvectors of a data affinity (i.e., item-item similarity) matrix to reveal the low dimensional structure in the high dimensional data. The most popular manifold learning algorithms include Locally Linear Embedding, ISOMAP, and Laplacian ...

Spectral methods have recently emerged as a powerful tool for dimensionality reduction and manifold learning. These methods use information contained in the eigenvectors of a data affinity (i.e., item-item similarity) matrix to reveal low dimensional structure in high dimensional data. The most popular manifold learning algorithms include Locally Linear Embedding, Isomap, and Laplacian Eigenmap...

Spectral methods have recently emerged as a powerful tool for dimensionality reduction and manifold learning. These methods use information contained in the eigenvectors of a data affinity (i.e., item-item similarity) matrix to reveal low dimensional structure in high dimensional data. The most popular manifold learning algorithms include Locally Linear Embedding, Isomap, and Laplacian Eigenmap...

In this paper a video coding scheme with Layered Block Matching Super-resolution (LBM-SR) is presented. At the encoder side, it divides the video frames into key and non-key frames, which are encoded at original resolution and reduced resolution respectively. During the resolution reduction process, most of the high frequency information in non-key frames is dropped to save the bit-rate. At the...

The objective of research was to explore the suitability of lipids like compritol 888 ATO and stearic acid as release retardant to develop sustained release (SR) tablets. The SR micromatrices of lipid (s) and glipizide were prepared (LM1- LM6) as intermediate product by fusion method and assessed for various pharmacotechnical properties. Micromatrices were formulated as SR tablets (F1-F6) by di...

The SR proteins, a group of abundant arginine/serine (RS)-rich proteins, are essential pre-mRNA splicing factors that are localized in the nucleus. The RS domain of these proteins serves as a nuclear localization signal. We found that RS domain-bearing proteins do not utilize any of the known nuclear import receptors and identified a novel nuclear import receptor specific for SR proteins. The S...