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The structure and anion recognition dynamics between calix[4]pyrroles and azide (N 3 − ) anions in the form of its TBA + and Na + salts were investigated in dimethyl sulfoxide solutions by Fourier transform infrared (FTIR) spectroscopy and ultrafast IR spectroscopy. Vibrational energy redistribution of the N 3 − anion in the complex is accelerated through hydrogen bonding interactions with the N−H proton of the receptor. Rotational dynamics of the bound N 3 − is greatly restricted, demonstrating a distinct countercation effect. The detailed binding modes of N 3 − with the receptor were further evaluated by the density functional theoretical (DFT) calculations and nuclear magnetic resonance (NMR) spectroscopy. All of these measurements support the notion that the calix [4]pyrroles are capable of capturing the azide anion in solution. However, the calix[4]pyrroles may not necessarily undergo a conformational change to a conelike geometry when they bind to the azide anion in the solution.

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The large-amplitude-oscillation experiment was carried out with two levels of freedom to provide data. Based on the wind tunnel data, polynomial regression, least-square support vector machines and radial basis function neural networks are studied and compared in this paper. An improved model was also developed in this work for unsteady nonlinear aerodynamics on the basis of standard boosting approach. The results on the wind tunnel data show that the predictions of the method are almost consistent with the actual data, thus demonstrating that these methods can model highly nonlinear aerodynamics. The results also indicate that improved boosting model has better accuracy than the other methods.

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Alarm classification and visualization of historical data is significant and sophisticated in the area of smart management in telecom network due to alarm flood and propagation. In this article, we propose a heterogeneous distance to compute the similarity distance matrix of alarms, which is applied to alarm classification. By using Multidimensional Scaling, alarm data in high dimension is translated into a 2-dimensional graph in alarm windows. Then alarm attention and relation are clearly shown by comparing current and past alarms. Experiments show MDS based on the heterogeneous distance has a better classifying effect than other distance measures. The case study demonstrates the method can show alarm correlation easily and help to locate faults when applied to the analysis of telecom alarm data.