Abstract: Methods, systems, and devices for wireless communication at a user equipment (UE) are described. A user equipment (UE) may receive a configuration indicating a mapping between a set of multiple subband indices and a set of multiple encoding parameter sets. The UE may apply, at a first distribution matcher, a first encoding parameter set to a first subset of a bit stream. The UE may also apply, at a second distribution matcher, a second encoding parameter set to a second subset of the bit stream. The a first encoding parameter set may be associated with a first subband index and the second encoding parameter set may be associated with a second subband index. The UE may then transmit a first modulated bit stream on a first subband, and a second modulated bit stream on a second subband.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a transmitter of orbital angular momentum (OAM) multiplexing based communication may transmit, to a receiver of the OAM multiplexing based communication, a configuration message that indicates a configured set of transmitter circles. The transmitter may transmit, to the receiver, at least one data stream using the configured set of transmitter circles. Numerous other aspects are provided.

Abstract: Methods, systems, and devices for wireless communications are described that support signaling of compressed gradient vectors in a machine learning system that utilizes federated learning. The compressed gradient vectors may be used to report stochastic gradients from multiple edge devices (e.g., multiple user equipment (UE) devices) that are combined into a global model at an edge server (e.g., a base station). A base station may configure a UE with one or more parameters for quantizing a local stochastic gradient, and for reporting the quantized local stochastic gradient in a set of compressed gradient vectors. Each vector of the compressed gradient vectors may be associated with a different stage of a multi-stage compression procedure for reporting the local stochastic gradient, and multiple reports from multiple UEs may be aggregated in a federated learning procedure associated with a machine learning algorithm.

Abstract: Methods, systems, and devices for wireless communications at a are described. A first device (e.g., a transmitting device) may receive, from a second device (e.g., a receiving device), an indication of one or more parameters associated with communications between the second device and the first device. The first device may determine a transmitter circle of a set of transmitter circles for an orbital angular momentum (OAM) mode of a set of OAM modes for communications with the second device based on the one or more parameters. The first device may transmit a message to the second device using the transmitter circle according to the orbital angular momentum mode based the determining.

Abstract: Methods, systems, and devices for wireless communications are described. A rateless code may be used to generate n encoded packets based on a set of source packets. A modulation technique may be used to generate first symbol packets from the encoded packets. And a layered modulation technique may be used to generate coded symbol packets from the first symbol packets. The layered modulation technique may include generating a coded symbol packet from a group of first symbol packets. Different weights may be applied to the different first symbol packets included in the group of first symbol packets before the first symbol packets in the group are combined together. A receiving device may demodulate the transmitted coded symbol packets to reconstruct the group of first symbol packets, use the reconstructed group of first symbol packets to recover the encoded packets, and use the encoded packets to reconstruct the source packets.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive an indication of one or more of an input size or an input structure for a transmitting-side neural network, wherein the input structure indicates one or more of non-zero values or locations for the non-zero values within an input, having the input size, to the transmitting-side neural network. The UE may communicate with a base station based at least in part on the indication of the one or more of the input size or the input structure of the transmitting-side neural network. Numerous other aspects are provided.

Abstract: Disclosed are a control method and a control device for an auxiliary pipeline of an excavator, a working machine and an electronic apparatus. The control method for the auxiliary pipeline of the excavator includes: acquiring a pressure difference between an input end and an output end of the auxiliary pipeline of the excavator; obtaining an output flow of the auxiliary pipeline based on the pressure difference; and controlling the output flow of the auxiliary pipeline to adjust to be within a target flow range when the output flow of the auxiliary pipeline is beyond the target flow range. The control method for the auxiliary pipeline of the excavator according to the present application can solve the defect of relatively large pressure and flow distortion of the auxiliary pipeline in the related art, and realize an accurate control to the input and output of the flow of the auxiliary pipeline.

Abstract: Disclosed are a protective starch-based film and its preparation method and application, belonging to the field of food packaging. According to the method for preparing the protective starch-based film, surfaces of zinc oxide nanoparticles are enabled to adsorb tannic acid and iron ions under the action of metal coordination by controlling the pH to obtain metallic polyphenol network coated zinc oxide nanoparticles, dispersion of the obtained nanoparticles is added to a starch gelatinization solution, and a melanin-like precursor is simultaneously added to form mixed liquid; and by controlling the pH of the mixed solution, ?-? stacking, self-polymerization and metal coordination are induced, so that a stable protective starch-based film with a nano-reinforced interpenetrating network structure is formed.

Abstract: Techniques are provided for positioning a user equipment (UE). An example method of positioning includes receiving a positioning reference signal resource set associated with a base station, receiving an indication of a subset of the positioning reference signal resource set, and obtaining measurements from positioning reference signals associated with the subset of the positioning reference signal resource set.

Abstract: A UE may indicate, to a wireless network, a capability to support one or more versions of an ML processing model, and a wireless network entity of the wireless network may configure the UE to apply a version of the ML processing model that is supported by the UE. The indication from the UE may indicate the capability to support one or more of a first version of the ML processing model that is common across multiple wireless networks and at least one alternate version of the ML processing model, such as a version that is specific to a network. The wireless network entity may configure at least one of a network specific algorithm structure or one or more weights for an network specific machine learning model that is supported by the UE.

Abstract: The present disclosure relates to uplink control information (UCI) multiplexing for multi-slot physical uplink shared channel (PUSCH) with transport block size (TBS) scaling. Specifically, a user equipment (UE) may determine to transmit UCI on a multi-slot PUSCH transmission. The UE may further identify a number of UCI resource elements (REs) in at least one slot of the PUSCH transmission based at least on a scaling rate. The UE may further perform the PUSCH transmission including the UCI REs.

Abstract: Disclosed is a computer implemented method for malware detection that analyses a file on a per packet basis. The method receives a packet of one or more packets associated a file, and converting a binary content associated with the packet into a digital representation and tokenizing plain text content associated with the packet. The method extracts one or more n-gram features, an entropy feature, and a domain feature from the converted content of the packet and applies a trained machine learning model to the one or more features extracted from the packet. The output of the machine learning method is a probability of maliciousness associated with the received packet. If the probability of maliciousness is above a threshold value, the method determines that the file associated with the received packet is malicious.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment may receive a signaling communication that includes information specifying whether a channel state information reference signal (CSI-RS) precoding resource block group includes a same quantity of resource blocks (RBs) that is included in a CSI reporting subband configured for the UE. The CSI-RS precoding resource block group may enable the UE to perform a channel estimation based at least in part on a CSI-RS transmitted by a base station. The UE may perform the channel estimation based at least in part on the CSI-RS transmitted by the base station. The channel estimation may be based at least in part on whether the CSI-RS precoding resource block group includes the same quantity of RBs that is included in the CSI reporting subband configured for the UE. Numerous other aspects are provided.

Abstract: Methods, systems, and devices for wireless communication are described that provide for reduced timing between certain downlink communications and responsive uplink communications relative to certain legacy systems (e.g., legacy LTE systems). A user equipment (UE) or base station may be capable of operating using two or more timing configurations that each include an associated time period between receipt of a downlink communication (e.g., a grant of uplink resources or shared channel data) and a responsive uplink communication (e.g., an uplink transmission using the granted uplink resources or feedback of successful reception of the shared channel data). In cases where a UE or base station are capable of two or more timing configurations, a timing configuration for a transmission may be determined and the responsive uplink communication transmitted according to the determined timing configuration.

Abstract: A method of desulfurizing a sulfur-containing hydrocarbon feedstock includes introducing the sulfur-containing hydrocarbon feedstock within a reactor in the presence of a gas atmosphere and a catalyst structure, where the catalyst structure comprises a zeolite porous support structure including gallium (Ga) and molybdenum (Mo) loaded in the zeolite porous support structure. The gas atmosphere can include methane. At least 50% of sulfur content can be removed from the feedstock as a result of the desulfurizing method.

Abstract: Aspects of the present disclosure provide techniques for channel state information (CSI) reporting in multiple transmitter receiver point (mTRP) scenarios.

Abstract: Wireless communications systems and methods related to determining and transmitting delay measurements, such as propagation delay, between a base station (BS) and a user equipment (UE) are provided. In some aspects, a UE may receive, from a BS, a positioning reference signal (PRS). The UE may further transmit, in response to and at a predetermined time after the receiving the PRS, a sounding reference signal (SRS) to the BS. Further, the UE may receive, from the BS, a delay measurement corresponding to the PRS.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive, from a base station, a sensing configuration associated with a sensing mode, the sensing configuration indicating one or more parameter values that the UE is to use to perform sensing of objects within a detectable range of the UE, and the sensing configurating further indicating a format for providing a sensing report according to the sensing mode. The UE may receive one or more sensing waveforms based at least in part on the sensing configuration. The UE may transmit, to the base station according to the sensing mode, a sensing report indicating information associated with the one or more sensing waveforms.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive, from a base station, a channel state information (CSI) configuration indicating a first feedback reporting periodicity for a dominant, or strong, spatial layer and a second feedback reporting periodicity for a non-dominant, or weak, spatial layer. The UE may transmit a first CSI report for at least the dominant spatial layer according to the first feedback reporting periodicity. The UE may transmit a second CSI report for the non-dominant spatial layer according to the second feedback reporting periodicity. In some cases, for aperiodic reporting, the UE may be triggered by downlink control information to report CSI for the dominant spatial layer. In some cases, the CSI configuration may indicate different codebooks for the dominant and non-dominant spatial layers.

Abstract: The present disclosure provides a transmission line defect identification method based on a saliency map and a semantic-embedded feature pyramid, including the following steps: step 1: cleaning and classifying a dataset; step 2: generating a super-resolution image for a small target of a transmission line by using an Electric Line-Enhanced Super-Resolution Generative Adversarial Network (EL-ESRGAN) model; step 3: performing image saliency detection on the dataset by constructing a U2-Net; step 4: performing data augmentation on the dataset by using GridMask and random cutout algorithms based on a saliency map, and generating a classified dataset; and step 5: performing image classification on a normal set and a defect set by using a ResNet34 classification algorithm and a deep semantic embedding (DSE)-based feature pyramid classification network.