In this paper, an ultrasonic signal processing method is proposed to improve depth evaluation of phased array ultrasonic non-destructive testing in composite structures. The proposed algorithm is based on an improved adaptive time–frequency analysis algorithm, and is a combination of empirical mode decomposition, correlation coefficient analysis, a fuzzy entropy algorithm and Hilbert transform. The ultrasonic signal is decomposed into intrinsic mode functions (IMFs) using an improved complete ensemble empirical mode decomposition with adaptive noises. Subsequently, the correlation coefficient and fuzzy entropy are used to select the optimal IMFs to reconstruct the signal. Then, Hilbert transform is executed to obtain the envelope of the reconstructed signal. Finally, the arrival time of the ultrasonic echo is estimated through the signal envelope, and then used to calculate the defect depth. The simulation and experimental results demonstrated that the proposed method has high evaluation accuracy in processing intense noisy signals or overlapped echoes. For simulated signals with different signal-to-noise ratios, the maximum estimation error of arrival time is 0.06 µs. Compared with the traditional gating method, the defect depth evaluation result is significantly improved. In particular, for near-surface defects, the maximum depth detection error is reduced from 0.13 mm to 0.06 mm.

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Background: The most convenient circulating tumor cells (CTCs) identification method is direct analysis of cells under bright field microscopy by which CTCs can be comprehensive studied based on morphology, phenotype or even cellular function. However, universal cell markers and a standard tumour cell map do not exist, thus limiting the clinical application of CTCs. Results: This paper focuses on an automatic and convenient negative depletion strategy for circulating tumour cell identification under bright field microscopy. In this strategy, immune microparticles (IMPs) are applied to negatively label white blood cells rather than the tumour cells, such that tumour cells can be directly distinguished under brightfield of the microscopy. In this way, all of the heterogeneous tumour cells and their phenotype properties can be retained for further cancer-related studies. In addition, a wedge-shaped microfluidic chip is constructed for heterogeneous CTC pre-purification and enrichment by size, thus significantly decreasing the interference of haematological cells. Additionally, all cell treatments are processed automatically, and the tumour cells can be rapidly counted and distinguished via customized cell analytical software, showing high detection efficiency and automation. This IMPs based negative cell labelling strategy can also be combined with other classic cell identification methods, thus demonstrating its excellent compatibility. Conclusion: This identification strategy features simple and harmless for tumour cells, as well as excellent accuracy and efficiency. And the low equipment demand and high automation level make it promise for extensive application in basic medical institutions.

The existed multiplex biomarker detections are limited by the high demand for coding material and expensive detection equipment. This paper has proposed a convenient and precise coding method based on...

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