Abstract: A tumor radiotherapy planning design method and apparatus, an electronic device, and a computer storage medium are provided, including: obtaining a current optimization parameter vector set, and calculating a current cost function value; randomly correcting the current optimization parameter vector set to generate alternative optimization parameter vector sets; then performing planning parameter optimization, and calculating corresponding total cost function values; determining current optimal or suboptimal alternative optimization parameter vector sets according to the total cost function values, sampling to update the current optimization parameter vector set and the current cost function value according to the total cost function values of the current alternative optimization parameter vector sets, and then performing an iteration repeatedly until a convergence condition is satisfied; and outputting an optimal optimization parameter vector set after the iteration, determining planning parameters, and calcu

Abstract: Implementations of the disclosure provide video processing systems and methods. The video processing method may include receiving, by one or more processors, a video frame of a video for in-loop filtering. For a target pixel of the video frame, the video processing method may further include selecting, by the one or more processors, a bilateral filtering window to perform the in-loop filtering on the target pixel from a group of candidate filtering windows. The group of candidate filtering windows include a plurality of side filtering windows and a full filtering window. The video processing method may also include filtering, by the one or more processors, the target pixel of the video frame using the selected bilateral filtering window.

Abstract: A computer system acquires a video bitstream. The video bitstream includes data associated with multiple encoded pictures. Each encoded picture includes one or more coding units (CUs). While decoding a current CU of a picture in the video bitstream, the current CU having a plurality of reference subblocks located in one or more reference pictures, in accordance with a determination that the plurality of reference subblocks satisfy a first set of predefined conditions for enabling a subblock-based temporal motion vector prediction (SbTMVP) mode, the computer system retrieves, from the video bitstream, syntax elements associated with the SbTMVP mode. The computer system then decodes the current CU using the retrieved syntax elements associated with the SbTMVP mode.

Abstract: An electronic apparatus performs a method of decoding video data. The method includes: receiving, from the video data, an Adaptation Parameter Set (APS) identifier associated with a number of previously used Cross-Component Sample Adaptive Offset (CCSAO) filter offset sets stored in APS; receiving, from the video data, a syntax in Picture Header (PH) or Slice Header (SH) that indicates the APS identifier used for a current picture or slice; decoding, for the current coding tree unit (CTU), a filter set index that indicates a particular previously used CCSAO filter offset set of the number of offset sets in the APS associated with the APS identifier; and applying the particular previously used CCSAO filter offset set to the current CTU of the video data.

Abstract: Methods and devices are provided for decoding a video block in GPM. The method includes: partitioning the video block into a first geometric partition and a second geometric partition; receiving a first template matching (TM) enable flag for the first geometric partition a second TM enable flag for the second geometric partition, the first TM enable flag indicating whether a uni-directional motion of the first geometric partition is refined by TM, and the second TM enable flag indicating whether a uni-directional motion of the second partition is refined by the TM; receiving a first merge GPM index for the first geometric partition and a second merge GPM index for the second geometric partition; constructing a uni-directional motion victor (MV) candidate list of the GPM; and generating a first uni-directional MV for the first geometric partition and a second uni-directional MV for the second geometric partition.

Abstract: Methods and devices for video decoding are provided. The method may include obtaining a plurality of coding blocks within a video frame, where the plurality of coding blocks may include at least one chroma coding block and a plurality of luma coding blocks. Further, the method may include determining whether to apply OBMC to the at least one chroma coding block and the plurality of luma coding blocks to generate prediction samples for the video frame in response to determining that a local chroma tree partition is applied to the plurality of coding blocks.

Abstract: Provided are a sequencing library and applications thereof. The provided sequencing library includes a first nucleic acid molecule and a second nucleic acid molecule. The first nucleic acid molecule carries a cell index sequence and a droplet index sequence. The second nucleic acid molecule carries an insert fragment and a cell index sequence.

Abstract: The present disclosure describes a system, method and software applications for predicting the KAM of a subject for a plurality of gait cycles of a subject. At least one sensor attachable adjacent to the ankle of at least one leg of the subject provides accelerometer and gyroscopic data for the plurality of gait cycles. A processing means receives subject parameters and accelerometer and gyroscopic data from the at least one sensor for evaluation by a neural network of predicted KAM values for the plurality of gait cycles of the subject. The neural network is configured via determining KAM values for each of the plurality of subjects from measurements during a plurality of gait cycles and other parameters.

Abstract: The present disclosure describes a system, method and software applications for predicting the KAM of a subject for a plurality of gait cycles of a subject. At least one sensor attachable adjacent to the ankle of at least one leg of the subject provides accelerometer and gyroscopic data for the plurality of gait cycles. A processing means receives subject parameters and accelerometer and gyroscopic data from the at least one sensor for evaluation by a neural network of predicted KAM values for the plurality of gait cycles of the subject. The neural network is configured via determining KAM values for each of the plurality of subjects from measurements during a plurality of gait cycles and other parameters.