Nilotinib as a type of anticancer drug was designed for the treatment of chronic myeloid leukemia that is resistant to imatinib. Presently, very few studies of nilotinib polymorphs have been reported because of the sparing solubility of the free base compared with its salt forms. Besides, there are also hardly reports for its solvates. Notably, in this study, eight different nilotinib solid-state forms, including six new solvates (form H1, form H2a, form H2b, form H2c, form H3, and form H4) and two desolvated polymorphs (form C and form D) were initially obtained. The crystallography data of form H2a, form H2b, and form H2c were obtained using single-crystal X-ray diffraction. We found that form H2a, form H2b, and form H2c were isolated site solvates. Besides, form H1 and form H3 are suspected to be isolated site solvates based on their thermal characterizations. Furthermore, we performed antisolvent experiments and used the diffusion theory to explain the mechanism successfully. In addition, we performed a series of solventmediated phase transformation experiments of the solid-state forms specifically and studied the transformation between nilotinib solvates. To the best of our knowledge, this is the first study to report the eight new crystal forms of nilotinib. Therefore, the present study fulfills the research blank in the crystallography field of nilotinib.

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The aim of dimensionality reduction is to construct a low-dimensional representation of high dimensional input data in such a way, that important parts of the structure of the input data are preserved. This paper proposes to apply the dimensionality reduction to intrusion detection data based on the parallel Lanczos-SVD (PLSVD) with the cloud technologies. The massive input data is stored on distribution files system, like HDFS. And the Map/Reduce method is used for the parallel analysis on many cluster nodes. Our experiment results show that, compared with the PCA algorithm, PLSVD algorithm has better scalability and flexibility.

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