Abstract: A method of wireless communications by a user equipment (UE) includes communicating with a network based on a machine learning model for wireless communication. The method also includes monitoring a status of the machine learning model for wireless communication. The method further includes reporting the status of the machine learning model for wireless communication using a predetermined resource according to a predetermined format. The method also includes falling back to communicating with a fallback procedure, instead of the machine learning model for wireless communication, to maintain wireless communication with the network in response to the status of the machine learning model indicating a model failure.

Abstract: Methods, systems, and devices for power backoff techniques for modulation schemes are described. A user equipment (UE) may receive an indication of a constellation distribution parameter and a modulation scheme to be used by the UE for an uplink message on an uplink channel. The UE may determine an uplink transmission power based at least in part on the indicated constellation distribution parameter and the indicated modulation scheme. The UE may transmit the uplink message using the indicated modulation scheme according to the determined uplink transmission power. In some examples, the UE may transmit a report indicating a power headroom parameter and an output power parameter based at least in part on the constellation distribution parameter.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a base station, a beam failure detection (BED) reference signal set in one or more slots in a full-duplex mode and in one or more slots in a half-duplex mode. The UE may detect beam failure due to self-interference based at least in part on a comparison of measurements of the BFD reference signal set in the full-duplex mode and half-duplex mode. The UE may switch from the full-duplex mode to the half-duplex mode for slots configured for the full-duplex mode based at least in part on detecting beam failure due to self-interference. Numerous other aspects are described.

Abstract: Methods, systems, and devices for wireless communications are described. In some systems, devices use machine learning (ML) models to support wireless communications. For example, a user equipment (UE) may download ML model information from a network to determine an ML model. The network may additionally configure a status reporting procedure, a fallback procedure, or both for the ML model. In some examples, based on a configuration, the UE may transmit a status report to a base station according to a reporting periodicity, a UE-based trigger, a network-based trigger, or some combination thereof. Additionally or alternatively, the UE may determine to fallback from operating using the ML model to operating in a second mode based on a fallback trigger. In some examples, to restore operating using a downloaded ML model, the UE may download an updated ML model or receive iterative updates to a previously downloaded ML model.

Abstract: Methods, systems, and devices for wireless communications are described. In some systems, a wireless device may In use non-uniformly distributed bits for amplitude mapping and uniformly distributed bits for sign mapping to support probabilistic constellation shaping (PCS) for transmission of a message. To provide a coding gain with one or more retransmissions of the message, the device may configure redundancy versions based on the non-uniform distribution of one or more symbols. In some examples, the device may include the same set of non-uniformly distributed systematic bits or at least a portion of non-uniformly distributed systematic bits in each redundancy version of the message. Additionally or alternatively, the device may use multiple modulation and coding scheme (MCS) values to modulate one or more of the redundancy versions, where a first MCS value is used to modulate non-uniformly distributed symbols and a second MCS value is used to modulate uniformly distributed symbols.

Abstract: A configuration for reporting OOD samples for neural network optimization. The apparatus receives, from a base station, a configuration to report an OOD dataset for a machine learning model. The apparatus detects an occurrence of one or more OOD events. The apparatus reports the OOD dataset comprising the one or more OOD events based on the configuration to report OOD dataset. The apparatus receives, from the base station, an update to the machine learning model. The OOD dataset may comprise raw data related to the one or more OOD events, or may comprise extracted latent data corresponding to features of raw data related to the one or more OOD events.

Abstract: Apparatus, methods, and computer-readable media for network coding for handover are disclosed herein. A base station (BS) transmits a first group of encoded packets to a first road side unit (RSU) over a first radio access network (RAN) interface. The BS initiates a handover procedure between the first RSU and a second RSU. The BS receives, from the first RSU, a release acknowledgment associated with the handover procedure and feedback associated with the first group of encoded packets. The BS transmits network coding level information to the second RSU over a second RAN interface based on the feedback. The network coding level information indicates a number of missing encoded packets within the first group of encoded packets for the second RSU to transmit to the UE. The BS transmits, to the UE, a second group of encoded packets associated with the number of missing encoded packets at the second RSU.

Abstract: The present invention provides N6-substituted adenosine derivatives and N6-substituted adenine derivatives, manufacturing methods thereof, a pharmaceutical composition comprising the said compounds above, and uses of these compounds in manufacturing medicaments and health-care products for treating insomnia, convulsion, epilepsy, and Parkinson's diseases, and preventing and treating dementia.

Abstract: The present invention discloses an Albizzia chinensis extract used in the preparation of a drug for the treatment of gastric ulcers. Specifically, it discloses an Albizzia chinensis (Osbeck) Merr extract and its preparation method including the stems bark of Albizzia chinensis was successively grounded, extracted, concentrated and purificated, as well as a pharmaceutical composition comprising the Albizzia chinensis extract. Through pharmacological test, it has been demonstrated that, the Albizzia chinensis extract showed strong inhibition activity against proton pumps, and it can be used for the treatment of gastric ulcers, chronic gastritis and other acid-related diseases, and its anti-ulcer effect is significant, quick, safe and reliable.

Abstract: The present invention discloses an Albizzia chinensis extract used in the preparation of a drug for the treatment of gastric ulcers. Specifically, it discloses an Albizzia chinensis (Osbeck) Merr extract and its preparation method including the stems bark of Albizzia chinensis was successively grounded, extracted, concentrated and purificated, as well as a pharmaceutical composition comprising the Albizzia chinensis extract. Through pharmacological test, it has been demonstrated that, the Albizzia chinensis extract showed strong inhibition activity against proton pumps, and it can be used for the treatment of gastric ulcers, chronic gastritis and other acid-related diseases, and its anti-ulcer effect is significant, quick, safe and reliable.

Abstract: The present invention provides N6-substituted adenosine derivatives and N6-substituted adenine derivatives, manufacturing methods thereof, a pharmaceutical composition comprising the said compounds above, and uses of these compounds in manufacturing medicaments and health-care products for treating insomnia, convulsion, epilepsy, and Parkinson's diseases, and preventing and treating dementia.