This study aimed to identify suitable reference genes under three chemical inducers, methyl jasmonate (MeJA), salicylic acid (SA) and hydrogen peroxide (HO) in Ganoderma lucidum. In this study, expression stabilities of 14 candidate reference genes had been validated. Four algorithms were used: geNorm, NormFinder, BestKeeper, and RefFinder. Our results showed that, in short time, UCE2 (ubiquitin conjugating enzyme) was the most stable gene both in MeJA and HO treatments, ACTIN (beta-actin) was the most suitable reference gene for SA treatment. ACTIN/UCE2 were considered the most suitable genes to normalize in MeJA, SA and HO conditions. In long time, PP2A (protein phosphatase 2A regulatory subunit) was the most stable gene in MeJA and SA treatments, UCE2 was the most suitable reference gene for HO treatment. PP2A/UBQ1 (polyubiquitin 1) were considered the most suitable genes to normalize in MeJA, SA and HO conditions. Furthermore, target gene, oxidosqualene cyclase (osc), was selected to validate the most and least stable reference genes under different treatments. Our work provided a better support to study the regulatory mechanism of MeJA, SA and HO on biological functions.

Precision spherical joint is a spherical motion pair that can realize rotation with three degrees of freedom. This joint is widely used in robots, parallel mechanisms, and high-end medical equipment, as well as in aerospace and other fields. However, the rotation orientation and angle cannot be determined when the joint is in passive motion. The real-time determination of the rotation orientation and angle is crucial to the improvement of the motion control accuracy of the equipment where the joint is installed in. In this study, a new measurement method that utilizes eddy current sensors is proposed to identify the special features of the joint ball and realize angle measurements indirectly. The basic idea is to manufacture the specific shape features on the ball without affecting its movement accuracy and mechanical performance. An eddy current sensor array is distributed in the ball socket. When the ball head rotates, the features on the ball opposite to the sensor, as well as the output signal of every eddy current sensor, change. The measurement model that establishes the relationship between the output signal of the eddy current sensor array and the rotation direction and angle of the ball head is constructed by learning and training an artificial neural network. A prototype is developed using the proposed scheme, and the model simulation and feasibility experiment are subsequently performed. Results show that the root mean square angular error of a single axis within a range of ±14° is approximately 20 min, which suggests the feasibility of the proposed method.

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