Abstract: Provided herein are KRN2 gene controlling kernel row number in plant, molecular markers closely linked to KRN2 and their application in molecular breeding.

Abstract: Disclosed is an air microorganism enrichment device in farms, and relates to the technical field of air microorganism collection.

Abstract: An aerial vehicle dispatching method includes obtaining an aerial vehicle use request, determining a flight task according to the aerial vehicle use request, the flight task including a target flight area, in response to the flight task, determining a target aerial vehicle from a plurality of aerial vehicles, controlling the target aerial vehicle to perform the flight task in the target flight area, controlling the target aerial vehicle to obtain sensing data in the target flight area while performing the flight task, and sending the sensing data to a terminal device.

Abstract: A sensor, a movable platform, and a microwave radar sensor are provided. The sensor may include a motor, a rotating body, and a grating sensor. The motor may include a stator and a rotor rotatably connected to the stator, and the stator may have a mounting end face in an extension direction of a rotation center line of the rotor. The rotating body may be fixedly connected to the rotor. The grating sensor may include a grating code disc and a reading head assembly matched with the grating code disc. The grating code disc may be disposed on the mounting end face. The reading head assembly may be connected to the rotating body, and its position is opposite the position of the grating code disc. The reading head assembly may cooperate with the grating code disc to sense a rotation angle of the rotating body.

Abstract: A radar device includes a radar base and a radar module. The radar module is mounted at the radar base and configured to rotate relative to the radar base around a rotation axis. The radar module includes an antenna assembly, a signal processing circuit board, and a rotation installation base. The antenna assembly and the signal processing circuit board are arranged oppositely at an interval and jointly enclose to form an accommodation space. The rotation installation base is connected to the antenna assembly and the signal processing circuit board and is located in the accommodation space. The radar base is at least partially located in the accommodation space and arranged opposite to the rotation installation base.

Abstract: A sensor includes a rotation system and a sensing member. The rotation system includes a rotation assembly, an electromagnetic induction power supply assembly, and a wireless communication assembly. The rotation assembly includes a fixing member and a rotation member. The electromagnetic induction power supply assembly includes a power transmission assembly mounted at the rotation member, and a power reception assembly mounted at the fixing member and configured to transmit power to the power reception assembly. The wireless communication assembly includes first and second signal assemblies mounted at the fixing member and the rotation member, respectively. The sensing member is mounted at the rotation member and is electrically coupled to the power reception assembly and the second signal assembly, and is configured to be powered by the power reception assembly and transmit sensing data through the first and second signal assemblies.

Abstract: The present disclosure provides a system and a method for automatic secure delivery of a model, and belongs to the field of delivery technologies of artificial intelligence models. The system includes: a model warehouse, including at least one machine learning model; a prediction warehouse, including at least one prediction module matching metadata of the machine learning model in the model warehouse; and a processing engine, configured to have a function of assembling the machine learning model in the model warehouse and the prediction module in the prediction warehouse; in which the prediction module is configured to have an authentication function and an anti-debugging function, and the processing engine is configured to assemble the machine learning model in the model warehouse and the prediction module in the prediction warehouse which have a metadata matching relationship, and to generate a prediction service after the assembly is completed.