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We propose a novel approach to similarity assessment for graphic symbols. Symbols are represented as 2D kernel densities and their similarity is measured by the Kullback-Leibler divergence. Symbol orientation is found by gradient-based angle searching or independent component analysis. Experimental results show the outstanding performance of this approach(More)
Tissue stromal cells interact with leukaemia cells and profoundly affect their viability and drug sensitivity. Here we show a biochemical mechanism by which bone marrow stromal cells modulate the redox status of chronic lymphocytic leukaemia (CLL) cells and promote cellular survival and drug resistance. Primary CLL cells from patients exhibit a limited(More)
Triple-negative breast cancer (TNBC) is a subtype of highly malignant breast cancer with poor prognosis. TNBC is not amenable to endocrine therapy and often exhibit resistance to current chemotherapeutic agents, therefore, further understanding of the biological properties of these cancer cells and development of effective therapeutic approaches are(More)
Manganese (Mn) is an essential trace element for plants. Recently, the genes responsible for uptake of Mn in plants were identified in Arabidopsis and rice. However, the mechanism of Mn distribution in plants has not been clarified. In the present study we identified a natural resistance-associated macrophage protein (NRAMP) family gene in rice, OsNRAMP3,(More)
Visual similarity evaluation plays an important role in intelligent graphics system. In this paper, we focus on the domain of symbolic image recognition and introduce the Directional Division Tree representation to extract and describe the content information of an image. The conducted experiment shows that similarity evaluation algorithm based on this(More)
A severe potential security problem in utilization of Unicode in the Web is identified, which is resulted from the fact that there are many similar characters in the Unicode Character Set (UCS). The foundation of our solution relies on evaluating the similarity of characters in UCS. We develop a solution bsed on the renowned Kernel Density Estimation (KDE)(More)