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Many types of buildings have been widely constructed in the vicinity of subway lines in China. Normal life and business activities are hampered by excessive subway-induced vibrations. This study aims to determine the influence of structure characteristics on structure-borne vibrations, generally based on experimental results. Vibration measurements were performed in four typical sites in Wuxi, China, involving over-track buildings, along-track buildings, frame structure buildings and a masonry building. Special structure designs like structure transfer floor were also included. Then, the captured data was analyzed in the time domain and the frequency domain. Furthermore, the influence of building location, structure type and structure layout was investigated. Finally, vibrations were evaluated with ISO and Chinese criteria and structure optimization for vibration attenuation was proposed. It is found that over-track buildings are more severely affected than along-track buildings. Higher frequency contents (20–60 Hz) in over-track buildings and lower frequency contents (0–10 Hz) in along-track buildings should be seriously considered in vibration control. Weaker structure member joints and lower material strength would be beneficial to over-track buildings while the inverse situation would be beneficial to along-track buildings. The application of structure transfer floor — generally stiffer structure members and structure discontinuity-is also beneficial.

To observe the clinical efficacy of thunder-fire moxibustion for hypomenorrhea after induced abortion. A total of 74 patients with hypomenorrhea after induced abortion were randomized into two groups, with 37 cases in each group. The control group was treated with conventional hormone sequential therapy, and the observation group was treated with thunder-fire moxibustion. The course of treatment was 3 menstrual cycles. The traditional Chinese medicine (TCM) symptom scores, menstrual volume, endometrial thickness and the sex hormone levels were observed before and after treatment. The clinical efficacy was compared after treatment. The total effective rate in the observation group and the control group was 91.4% and 73.5%, respectively, and the difference between the two groups was statistically significant (P

Additional file 1: Supplementary materials.

Deep learning based speaker localization has shown its advantage in reverberant scenarios. However, it mostly focuses on the direction-of-arrival (DOA) estimation subtask of speaker localization, where the DOA instead of the 2-dimensional (2D) coordinates is obtained only. To obtain the 2D coordinates of multiple speakers with random positions, this paper proposes a deep-learning-based 2D speaker localization method with large ad-hoc microphone arrays, where an ad-hoc microphone array is a set of randomly-distributed microphone nodes with each node set to a traditional microphone array, e.g. a linear array. Specifically, a convolutional neural network is applied to each node to get the direction-of-arrival (DOA) estimation of speech sources. Then, a triangulation and clustering method integrates the DOA estimations of the nodes for estimating the 2D positions of the speech sources. To further improve the estimation accuracy, we propose a softmax-based node selection algorithm. Experimental results with large-scale ad-hoc microphone arrays show that the proposed method achieves significantly better performance than conventional methods in both simulated and real-world environments. The softmax-based node selection further improves the performance.