Abstract: Provided in the present invention are a method performed by user equipment and user equipment. The method performed by user equipment includes: receiving a coordination request in a first resource pool, determining a coordination resource set in a second resource pool, and transmitting, in a third resource pool, a coordination message as a response to the coordination request, wherein the coordination message includes an indication for the coordination resource set, and the first resource pool, the second resource pool, and the third resource pool are the same resource pool.

Abstract: The present disclosure relates to a class-agnostic object segmentation system that automatically detects, segments, and selects objects within digital images irrespective of object semantic classifications. For example, the object segmentation system utilizes a class-agnostic object segmentation neural network to segment each pixel in a digital image into an object mask. Further, in response to detecting a selection request of a target object, the object segmentation system utilizes a corresponding object mask to automatically select the target object within the digital image. In some implementations, the object segmentation system utilizes a class-agnostic object segmentation neural network to detect and automatically select a partial object in the digital image in response to a target object selection request.

Abstract: Provided in the present invention are a method performed by user equipment, and user equipment. The method includes: receiving a PSCCH and a corresponding PSSCH of the PSCCH transmitted by another sidelink user equipment; and determining a sidelink phase-tracking reference signal (PT-RS) sequence.

Abstract: Disclosed herein is a drug delivery vehicle. The drug delivery vehicle includes a lipid nanoparticle core for enclosing a primary drug and a protective shell surrounding the lipid nanoparticle. Also disclosed herein is a drug delivery system including the drug delivery vehicle carrying the primary drug, a method of preparing the drug delivery system and a method of using the drug delivery system.

Abstract: According to the present invention, provided are a method performed by user equipment and user equipment. The method includes: acquiring configuration information related to a hybrid automatic repeat request acknowledgement (HARQ-ACK) codebook, the configuration information including a first HARQ-ACK codebook parameter, a second HARQ-ACK codebook parameter, and a third HARQ-ACK codebook parameter; and determining, according to the configuration information related to the HARQ-ACK codebook, a HARQ-ACK codebook type related to sidelink (SL) transmission, wherein if the second HARQ-ACK codebook parameter has been configured, the first HARQ-ACK codebook parameter is applied and the second HARQ-ACK codebook parameter is ignored, and if the third HARQ-ACK codebook parameter has been configured, the first HARQ-ACK codebook parameter is applied and the third HARQ-ACK codebook parameter is ignored.

Abstract: Provided in the present invention are a method performed by user equipment and user equipment. The method includes: a MAC entity of user equipment receiving configuration information from upper layers, wherein the MAC entity is configured by the upper layers to perform sensing-based sidelink transmission; the user equipment selecting time domain and frequency domain resources for a first transmission opportunity; and the user equipment selecting time domain and frequency domain resources for a second transmission opportunity.

Abstract: Provided in the present invention are a method performed by user equipment and user equipment. The method comprises: determining sidelink resource pool configuration information; receiving a PSCCH and a corresponding PSSCH transmitted by another user equipment; and determining an initialization sequence parameter cinit of a cyclic shift ?1 of a sequence for a physical sidelink feedback channel (PSFCH).

Abstract: According to the present invention, provided is a method performed by user equipment, characterized by comprising: setting content of a message of 12 bits in a PSBCH of an S-SS/PSBCH block; and transmitting the S-SS/PSBCH block. One bit of the 12 bits is used to indicate whether pattern 1 is used or both of pattern 1 and pattern 2 are used for TDD configuration, and for FDD, or for a spectrum supporting only a PC5 interface and not provided with the TDD configuration, the 12 bits are all set to ‘1’.

Abstract: A method performed by a sidelink transmitting user equipment (SL TX UE) for sidelink (SL) vehicle to everything (V2X) unicast transmission to a sidelink receiving user equipment (SL RX UE). The method includes: receiving, a Radio Resource Control (RRC) configuration from a base station, the RRC configuration includes at least information for enabling SL Channel State Information (CSI) reporting and first Modulation and Coding Scheme (MCS) information for SL transmission by the SL TX UE; transmitting, a CSI-Reference Signal (CSI-RS) measurement resource configuration to the SL RX UE for deriving an SL CSI report; transmitting, an aperiodic CSI report trigger to the SL RX UE for triggering the SL CSI report in a sidelink control information (SCI); and receiving, the SL CSI report from the SL RX UE in a Physical Sidelink Shared Channel (PSSCH).

Abstract: Provided in the present invention are a method performed by user equipment, and user equipment. The method includes: receiving sidelink scheduling information transmitted by a base station; determining time domain resource interval indication information T1 and/or T2; and determining a value TRIV? of a time domain resource indication field in sidelink control information (SCI) format 0-1.

Abstract: The present disclosure relates to a class-agnostic object segmentation system that automatically detects, segments, and selects objects within digital images irrespective of object semantic classifications. For example, the object segmentation system utilizes a class-agnostic object segmentation neural network to segment each pixel in a digital image into an object mask. Further, in response to detecting a selection request of a target object, the object segmentation system utilizes a corresponding object mask to automatically select the target object within the digital image. In some implementations, the object segmentation system utilizes a class-agnostic object segmentation neural network to detect and automatically select a partial object in the digital image in response to a target object selection request.

Abstract: According to the present invention, a method performed by user equipment and user equipment are provided. The method performed by the user equipment is characterized by including: acquiring resource pool-related information; and determining a slot set in a resource pool. The resource pool-related information includes an SL subcarrier spacing configuration, a duplex mode, TDD configuration information, a time-domain resource period, a time-domain resource indication, and S-SSB-related information.

Abstract: Fill techniques as implemented by a computing device are described to perform hole filling of a digital image. In one example, deeply learned features of a digital image using machine learning are used by a computing device as a basis to search a digital image repository to locate the guidance digital image. Once located, machine learning techniques are then used to align the guidance digital image with the hole to be filled in the digital image. Once aligned, the guidance digital image is then used to guide generation of fill for the hole in the digital image. Machine learning techniques are used to determine which parts of the guidance digital image are to be blended to fill the hole in the digital image and which parts of the hole are to receive new content that is synthesized by the computing device.

Abstract: Provided in the present invention are a method performed by user equipment, and user equipment. The method includes: determining the maximum number Nmax of sidelink resources reserved for one sidelink transmission; receiving sidelink scheduling information transmitted by a base station; determining an index or number f2 of a lowest sub-channel of a second sidelink resource, and the number m of sub-channels in a sidelink frequency domain resource assignment, and/or an index f3 of a lowest sub-channel of a third sidelink resource; and determining a value r? of a frequency domain resource indication field in a sidelink control information (SCI) format 0-1.

Abstract: According to the present invention, a method performed by user equipment and user equipment are provided. The method performed by user equipment is characterized by including: determining a size of one or more DCI formats in a set S of DCI formats; and receiving DCI, wherein the set S of DCI formats includes at least one of DCI format 3_0 and DCI format 3_1, and the UE is configured with at least one of an SL-RNTI, an SL-CS-RNTI, an SL-L-CS-RNTI, and an SL SPS V-RNTI.

Abstract: According to the present invention, a method performed by user equipment is provided. The method is characterized by including: determining N PSFCHs, and performing one or more PSFCH-related operations, wherein N is an integer greater than or equal to 2, each of the N PSFCHs is for transmission or reception and overlapped in time, and destination layer-1 identifiers in SCI for scheduling data transmission triggering the N PSFCHs are different from each other.

Abstract: The present disclosure relates to a class-agnostic object segmentation system that automatically detects, segments, and selects objects within digital images irrespective of object semantic classifications. For example, the object segmentation system utilizes a class-agnostic object segmentation neural network to segment each pixel in a digital image into an object mask. Further, in response to detecting a selection request of a target object, the object segmentation system utilizes a corresponding object mask to automatically select the target object within the digital image. In some implementations, the object segmentation system utilizes a class-agnostic object segmentation neural network to detect and automatically select a partial object in the digital image in response to a target object selection request.

Abstract: The present invention provides a method performed by user equipment, and user equipment. The method includes: determining sidelink resource pool configuration information; and determining the number Q?SCI2 of coded modulation symbols of second stage SCI. The second stage SCI is second stage sidelink control information carried by a physical sidelink shared channel (PSSCH).

Abstract: According to the present invention, provided is a method performed by user equipment, and the method is characterized by including: obtaining indication information related to resource allocation; and determining Nindicatedres time/frequency resources according to the indication information, wherein Nindicatedres is a positive integer greater than or equal to 1, the indication information related to resource allocation includes information indicated in sidelink control information (SCI), and the information indicated in the SCI includes a time resource allocation indication value TRIV and/or a frequency resource allocation indication value FRIV.

Abstract: Provided in the present invention are a method performed by user equipment, and user equipment. The method comprises: determining sidelink resource pool configuration information to be first configuration information (S101); receiving, from another user equipment, sidelink control information (SCI) and a corresponding or associated physical sidelink shared channel (PSSCH) (S102); and determining a cyclic shift of a physical sidelink feedback channel (PSFCH) corresponding to the PSSCH.