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Transmitter-receiver (T-R) probes are widely used in the eddy-current testing of carbon fibre reinforced plastics (CFRP). However, T-R probes have the disadvantage of being highly sensitive to lift-off. On this basis, lift-off interference can be eliminated by differential structure. However, due to the electrical anisotropy of CFRP, the detection sensitivity of the side-by-side T-R probe and traditional R-T-R differential probe are greatly affected by the scanning angle, and the probe often needs to scan the sample along a specific path to achieve the ideal required detection effect. To solve these problems, a symmetrical dual-transmit-dual-receive (TR-TR) differential probe is designed in this paper. The detection performance of the TR-TR probe was verified by simulation and experiments. Results show that the TR-TR probe is less affected by the scanning angle and lift-off when used in CFRP defect detection, and has high detection sensitivity. However, the imaging results of the TR-TR probe do not show the defect characteristics straightforwardly. To solve this problem, a defect feature extraction algorithm is proposed in this paper. The results show that the defect feature extraction algorithm can locate and size the defect more accurately and improve the signal-to-noise ratio. [ABSTRACT FROM AUTHOR]

Based on Appraisal Theory and critical discourse analysis, this corpus-assisted study examines how China Daily (CD) and South China Morning Post (SCMP) used appraisal resources to express their respective stances towards the anti-extradition bill movement. The results show that both newspapers employed negative resources of Judgement and the predication strategy to convey their stance, but SCMP seemed more refrained in the use of appraisal resources. CD openly stated that any illegal actions should be punished, and SCMP also criticised these actions. Besides, CD emphasized the consequences brought by violence and attributed the breakout of the protests to the opposition camp's political intention for their own benefit, whereas SCMP highlighted Hong Kongers' widespread opposition to the bill. These differences in language use and stance might be explained by the different press systems they respectively belong to and related to their respective historical and socio-political contexts. [ABSTRACT FROM AUTHOR]

Ocean surface waves are essential to navigation safety, coastal activities, and climate systems. Numerical simulations are still the primary methods used in wave climate research, especially in future climate change scenarios. Recently, First Institute of Oceanography-Earth System Model version 2.0 (FIO-ESM v2.0), a global climate model coupled with an ocean wave model, was carried out the Coupled Model Intercomparison Project phase 6 (CMIP6) experiments. Here, we present the global monthly-mean and 3-hourly instantaneous wave parameter dataset from the FIO-ESM v2.0 CMIP6 experiments, including 700-year piControl, 165-year historical, three 86-year future scenarios (ssp125, ssp245, and ssp585, respectively), and two 150-year climate sensitive experiments (1pctCO2 and abrupt-4xCO2) simulations. Historical results show that the model can capture the basic wave climate features under climate change. These unique centuries of global wave data are from a fully coupled system and can provide the community with a vital long-term data source for scientific and engineering applications, such as wave climate research, wave-related process studies and parameterizations, as well as coastal and near-shore industry designs. Measurement(s) spectrum peak wave period • zero-crossing wave period • wave • height • direction Technology Type(s) computational modeling technique Factor Type(s) time-variant • geographic location Sample Characteristic - Environment climate system • ocean Sample Characteristic - Location Earth (planet) Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12479582 [ABSTRACT FROM AUTHOR]