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Plant mechanical strength is an important agronomic trait. To understand the molecular mechanism that controls the plant mechanical strength of crops, we characterized the classic rice mutant brittle culm1 (bc1) and isolated BC1 using a map-based cloning approach. BC1, which encodes a COBRA-like protein, is expressed mainly in developing sclerenchyma cells(More)
Kinesins are encoded by a large gene family involved in many basic processes of plant development. However, the number of functionally identified kinesins in rice is very limited. Here, we report the functional characterization of Brittle Culm12 (BC12), a gene encoding a kinesin-4 protein. bc12 mutants display dwarfism resulting from a significant reduction(More)
Cellulose represents the most abundant biopolymer in nature and has great economic importance. Cellulose chains pack laterally into crystalline forms, stacking into a complicated crystallographic structure. However, the mechanism of cellulose crystallization is poorly understood. Here, via functional characterization, we report that Brittle Culm1 (BC1), a(More)
BACKGROUND Hepatitis B virus (HBV) infection is endemic in China; perinatal transmission is the main source of chronic HBV infection. Simultaneous administration of hepatitis B immune globulin (HBIG) and hepatitis B vaccine is highly effective to prevent perinatal transmission of HBV; however, the effectiveness also depends on full adherence to the(More)
—In this paper, we propose a multi-kernel classifier learning algorithm to optimize a given nonlinear and nonsmoonth multivariate classifier performance measure. Moreover, to solve the problem of kernel function selection and kernel parameter tuning, we proposed to construct an optimal kernel by weighted linear combination of some candidate kernels. The(More)
In this paper, we study the problem of using contextual data points of a data point for its classification problem. We propose to represent a data point as the sparse linear reconstruction of its context, and learn the sparse context to gather with a linear classifier in a supervised way to increase its discriminative ability. We proposed a novel(More)
The problem of tag completion is to learn the missing tags of an image. In this paper, we propose to learn a tag scoring vector for each image by local linear learning. A local linear function is used in the neighborhood of each image to predict the tag scoring vectors of its neighboring images. We construct a unified objective function for the learning of(More)
The cell wall is important for pollen tube growth, but little is known about the molecular mechanism that controls cell wall deposition in pollen tubes. Here, the functional characterization of the pollen-expressed Arabidopsis cellulose synthase-like D genes CSLD1 and CSLD4 that are required for pollen tube growth is reported. Both CSLD1 and CSLD4 are(More)