Phase-based fringe projection metrology systems have been widely used to obtain the shape of 3D objects. One vital step is calibration, which defines the relationship between the phase and depth data. Existing calibration methods are complicated because of the dependence of the relationship on the pixel position. In this Letter, a simple calibration procedure is introduced based on an uneven fringe projection technique, in which the relationship between phase and depth becomes independent of the pixel position and can be represented by a single polynomial function for all pixels. Therefore, given a set of discrete points with a known phase and depth in the measuring volume, the coefficient set of the polynomial function can be determined. A white plate having discrete markers with known separation is used to calibrate the 3D imaging system. Experimental results demonstrate that the proposed calibration method is simple to apply and can build up an accurate relationship between phase and depth data.

One important step of phase-based three-dimensional imaging system is calibration, which defines the relationship between phase and depth data. Existing calibration methods are complicated and hard to carry out because of using a translation stage or gauge block in a laboratory environment. This Letter introduces a new simple, flexible calibration method by using a checkerboard and a white plate having discrete markers with known separation. The checkerboard determines the internal parameters of a CCD camera. The plate gives phase and depth data of each pixel to establish their relationship. Experimental results and performance evaluation show that the proposed calibration method can reliably build up the accurate relationship between phase map and depth data in a simple, flexible way.

Huanglongbing (HLB) has turned into a devastating botanical pandemic of citrus crops, caused by Candidatus Liberibacter asiaticus (CLas). However, until now the disease has remained incurable with very limited control strategies available. Restoration of the affected microbiomes in the diseased host through the introduction of an indigenous endophyte Bacillus subtilis L1-21 isolated from healthy citrus may provide an innovative approach for disease management. A novel half-leaf method was developed in vitro to test the efficacy of the endophyte L1-21 against CLas. Application of B. subtilis L1-21 at 104 colony forming unit (cfu ml−1) resulted in a 1,000-fold reduction in the CLas copies per gram of leaf midrib (107 to 104) in 4 days. In HLB-affected citrus orchards over a period of 2 years, the CLas incidence was reduced to < 3%, and CLas copies declined from 109 to 104 g−1 of diseased leaf midribs in the endophyte L1-21 treated trees. Reduction in disease incidence may corroborate a direct or an indirect biocontrol effect of the endophytes as red fluorescent protein-labeled B. subtilis L1-21 colonized and shared niche (phloem) with CLas. This is the first large-scale study for establishing a sustainable HLB control strategy through citrus endophytic microbiome restructuring using an indigenous endophyte.

A highly efficient atom‐economic method for the preparation of chiral 3,3′‐bis(indolyl)methanes (3,3′‐BIMs) was developed. A chiral phosphoric acid (1 mol %) was found to promote the formation of structurally divers BIMs with quaternary stereogenic carbon centers in excellent yields with excellent enantioselectivities. Control experiments indicated that the simultaneous formation of two hydrogen bonds between the catalyst and the substrate was the key factor to obtain a good stereoselective outcome.

Friction is a crucial factor affecting air accident occurrence on landing or taking off. Tire–runway friction directly contributes to aircraft stability on land. Therefore, an accurate friction estimation is a rising issue for all stakeholders. This paper summarizes the existing measurement methods, and a multi-sensor information fusion scheme is proposed to estimate the friction coefficient between the tire and the runway. Acoustic sensors, optical sensors, tread sensors, and other physical sensors form a sensor system that is used to measure friction-related parameters and fuse them through a neural network. So far, many attempts have been made to link the ground friction coefficient with the aircraft braking friction coefficient. The models that have been developed include the International Runway Friction Index (IRFI), Canada Runway Friction Index (CRFI), and other fitting models. Additionally, this paper attempts to correlate the output of the neural network (estimated friction coefficient) with the correlation model to predict the friction coefficient between the tire and the runway when the aircraft brakes. The sensor system proposed in this paper can be regarded as a mobile weather–runway–tire system, which can estimate the friction coefficient by integrating the runway surface conditions and the tire conditions, and fully consider their common effects. The role of the correlation model is to convert the ground friction coefficient to the grade of the aircraft braking friction coefficient and the information is finally reported to the pilots so that they can make better decisions.