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The solubility of two erlotinib hydrochloride polymorphs (form A and form B) in methanol, ethanol, isopropanol, acetone, methyl ethyl ketone, and methyl isobutyl ketone from 273.15 to 323.15 K were determined by means of high-performance liquid chromatography (HPLC). The modified Apelblat equation and the Buchowski–Ksiazczak λh equation were used to correlate the experimental solubility data. The results showed that the solubility of both forms generally increased with the temperature and at a given temperature decreased with the increase of the carbon number of alcohols; furthermore, methyl isobutyl ketone showed the largest solubility in the studied ketones. Meanwhile form A had a higher solubility than form B which demonstrated that form A was the metastable form. Furthermore, both models mentioned above gave satisfactory correlation results, in which the modified Apelblat equation worked better than the Buchowski–Ksiazczak λh equation.

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The Controller Placement Problem (CPP) is a key research topic in Software Defined Network (SDN), as the communication delay is influenced by the position of controllers and switches. On that basis, the network failures may happen occasionally, which can cause the increase of propagation latency and the reduction of network performance. As a result, it is essential to research the Controller Placement problem for Link Failures (CPLF). In this paper, authors propose a method based on the cross entropy to solve CPP after link failures, and adopt the Halton sequence to reduce the computation overhead of simulating link failures while guaranteeing the accuracy. In the experiments, we measure and compare the worst-case delay among three methods: our proposed cross entropy-based controller placement algorithm, the optimized controller placement algorithm and a greedy-based controller placement algorithm, and conduct experiments on six real network topologies. The experimental results verify that our proposed method can reduce the worst-case delay by [Formula: see text] in comparison with GPA. Moreover, the proposed method can always find optimized controller placement schemes no matter how the network scale or the number of controller varies, with a less than [Formula: see text] error when compared with the optimal solution.