Abstract: The present invention relates to a strategy for combining a berberine analog with a JAK inhibitor in the treatment of inflammatory diseases of the gastrointestinal tract. Specifically, provided by the present invention is a pharmaceutical composition containing the berberine analog and the JAK inhibitor, and a use thereof in the treatment of inflammatory diseases of the gastrointestinal tract. The composition may exhibit an improved effect over the use of berberine or the JAK inhibitor alone.

Abstract: The present invention relates to a codrug that cleaved in the gut, preparation therefor, and a use thereof. Specifically, provided is a codrug compound in formula I. Also provided are a method of using the present compound for the treatment of gastrointestinal tract autoimmune diseases, inflammatory diseases, and cancers, as well as a method and an intermediate for preparing the present compound.

Abstract: Provided are a JAK kinase inhibitor, preparation and use thereof. In particular, provided is a compound of Formula I, wherein each group is as described in the specification. The compound has an excellent JAK inhibitory activity, and therefore can be used to prepare pharmaceutical compositions for the treatment of cancer and other diseases related to JAK activity.

Abstract: A character recognition method and apparatus are disclosed, relate to the field of image recognition technologies, reduce a calculation time, and increase character recognition efficiency.

Abstract: In an optical character recognition system, a word segmentation method, comprising: acquiring a sample image comprising a word spacing marker or a non-word spacing marker; processing the sample image with a convolutional neural network to obtain a first eigenvector corresponding to the sample image, a word spacing probability value and/or a non-word spacing probability value corresponding to the first eigenvector; acquiring a to-be-tested image, and processing the to-be-tested image with the convolutional neural network to obtain a second eigenvector corresponding to the to-be-tested image, a word spacing probability value or a non-word spacing probability value corresponding to the second eigenvector; and performing word segmentation on the to-be-tested image by using the just obtained word spacing probability value or the non-word spacing probability value.

Abstract: A character recognition method and apparatus are disclosed, relate to the field of image recognition technologies, reduce a calculation time, and increase character recognition efficiency.

Abstract: In an optical character recognition system, a word segmentation method, comprising: acquiring a sample image comprising a word spacing marker or a non-word spacing marker; processing the sample image with a convolutional neural network to obtain a first eigenvector corresponding to the sample image, a word spacing probability value and/or a non-word spacing probability value corresponding to the first eigenvector; acquiring a to-be-tested image, and processing the to-be-tested image with the convolutional neural network to obtain a second eigenvector corresponding to the to-be-tested image, a word spacing probability value or a non-word spacing probability value corresponding to the second eigenvector; and performing word segmentation on the to-be-tested image by using the just obtained word spacing probability value or the non-word spacing probability value.