Abstract: A mobile device includes a primary battery and a secondary battery, and the mobile device further includes: a power supply control module and a main control module connected to each other, where the power supply control module is respectively connected to the primary battery and the secondary battery; and the main control module is configured to control the primary battery to supply power to the mobile device when it is determined that the primary battery and the mobile device are in the power-on state; and control a power supply of the mobile device to be switched from the primary battery to the secondary battery when it is determined that the primary battery and the mobile device are in the power-off state.

Abstract: A decoding method, a data processing method, an information generation method, a mobile terminal, a control terminal, an electronic system, and a non-transitory computer-readable storage medium are provided. The decoding method includes: parsing combined data that is received, the combined data being data obtained by combining image data captured by a mobile terminal and mobile terminal information corresponding to the mobile terminal; and in response to obtaining, by the parsing, an extended data bit string corresponding to the mobile terminal information, parsing extended data encoding information corresponding to the mobile terminal information from the combined data, and decoding the extended data encoding information to obtain the mobile terminal information.

Abstract: The present disclosure provides crystalline forms of 2-methyl-N-[2-oxo-2-(2,2,2-trifluoroethylamino)ethyl]-4-[(5S)-5-[3-chloro-2-fluoro-5-(trifluoromethyl)phenyl]-5-(trifluoromethyl)-4H-isoxazol-3-yl]benzamide, methods of preparing the same, and pharmaceutical compositions comprising the same.

Abstract: The present application provides a method and system for defect detection. The method includes: acquiring a two-dimensional (2D) picture of an object to be detected; inputting the acquired 2D picture to a trained defect segmentation model to obtain a segmented 2D defect mask, where the defect segmentation model is trained based on a multi-level feature extraction instance segmentation network with intersection over union (IoU) thresholds being increased level by level, and the 2D defect mask includes information about a defect type, a defect size, and a defect location of a segmented defect region; and determining the segmented 2D defect mask based on a predefined defect rule to output a defect detection result.

Abstract: An image processing method includes obtaining two-dimensional and three-dimensional images of an object, extracting luminance and depth information from the three-dimensional image to generate luminance and depth image for the object, graying the two-dimensional image to obtain a single-channel grayscale image, selecting at least three same-location points from each of the grayscale and luminance image, calculating a coordinate transformation matrix between the grayscale and luminance images based on coordinates of the at least three same-location points in each of the grayscale and luminance images, and aligning the two-dimensional image with the luminance and depth images based on the coordinate transformation matrix to obtain fused image data. The fused image data includes color information of the two-dimensional image and the luminance and depth information of the three-dimensional image.

Abstract: The present application provides a method and system for defect detection. The method includes: acquiring a two-dimensional (2D) picture of an object to be detected; inputting the acquired 2D picture to a trained defect segmentation model to obtain a segmented 2D defect mask, where the defect segmentation model is trained based on a multi-level feature extraction instance segmentation network with intersection over union (IoU) thresholds being increased level by level, and the 2D defect mask includes information about a defect type, a defect size, and a defect location of a segmented defect region; and determining the segmented 2D defect mask based on a predefined defect rule to output a defect detection result.

Abstract: An image processing method includes obtaining two-dimensional and three-dimensional images of an object, extracting luminance and depth information from the three-dimensional image to generate luminance and depth image for the object, graying the two-dimensional image to obtain a single-channel grayscale image, selecting at least three same-location points from each of the grayscale and luminance image, calculating a coordinate transformation matrix between the grayscale and luminance images based on coordinates of the at least three same-location points in each of the grayscale and luminance images, and aligning the two-dimensional image with the luminance and depth images based on the coordinate transformation matrix to obtain fused image data. The fused image data includes color information of the two-dimensional image and the luminance and depth information of the three-dimensional image.

Abstract: The present invention provides a preparation method for a nitrogen-doped carbon-loaded metal monatomic catalyst, including: mixing a soluble metallic salt, a hydroxylamine hydrochloride, a soluble carbon source, water, and ethanol, to obtain a mixed solution, then performing drying and precipitation, to obtain a catalyst precursor, and finally performing calcination, to obtain a nitrogen-doped carbon-loaded metal monatomic catalyst. In the present invention, the metallic salt, the hydroxylamine hydrochloride, and the carbon source are fully mixed in the solution, and after being dried, are calcined, to carbonize the carbon source, so that ammonium ions are decomposed into nitrogen-doped carbon, and meanwhile, metal atoms are loaded onto the nitrogen-doped carbon. The method is simple, and costs are low.