MOTIVATION: Comparison of RNA 3D structures can be used to infer functional relationship of RNA molecules. Most of the current RNA structure alignment programs are built on size-dependent scales, which complicate the interpretation of structure and functional relations. Meanwhile, the low speed prevents the programs from being applied to large-scale RNA structural database search. RESULTS: We developed an open-source algorithm, RNA-align, for RNA 3D structure alignment which has the structure similarity scaled by a size-independent and statistically interpretable scoring metric. Large-scale benchmark tests show that RNA-align significantly outperforms other state-of-the-art programs in both alignment accuracy and running speed. The major advantage of RNA-align lies at the quick convergence of the heuristic alignment iterations and the coarse-grained secondary structure assignment, both of which are crucial to the speed and accuracy of RNA structure alignments. AVAILABILITY AND IMPLEMENTATION: https://zhanglab.ccmb.med.umich.edu/RNA-align/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Acoustic echo is a very trouble question in the live teaching system where teacher's speech will be echoed in the classroom after a moment. This paper presents a speech enhancement framework shaping for live teaching system based on a novel hybrid double-talk detector (DTD). The proposed double-talk detection algorithm consists of two decision stages. First, double-talk is detected based on the classic energy-based approach. While a further judgment for silence situation is made in the second stage. If silence is announced, the microphone channel is shut down to reduce the bandwidth requirement. After simulation and experiment, it is found that not only the proposed approach is effective in enhancing the speech quality but also can it save the network bandwidth for e-learning system