Abstract: Provided are a method for preparing a curved piezoelectric single crystal composite material, and the application thereof. The preparation method includes: step 1, designing a curved-surface 3D printed mesh mold and forming the curved-surface 3D printed mesh mold by printing; step 2, cutting a blocky piezoelectric phase into a plurality of small piezoelectric columns; step 3, inserting the small piezoelectric columns into empty cells of the 3D printed mold; step 4, filling gaps between the piezoelectric columns and the 3D printed mold with a non-piezoelectric phase such as an epoxy resin, and curing and forming the non-piezoelectric phase; and step 5, grinding, polishing, and ultrasonically cleaning a prepared sample, and then performing an electrode coating operation on the sample to obtain a curved-surface piezoelectric composite material.

Abstract: The disclosed embodiments provide a highly accurate, low-latency pre-processing pipeline hardware architecture for RADAR images. In an embodiment, a method comprises: receiving a time-domain representation of a radar image of a scene, the representation including at least one object; determining a range to the at least one target based on a range frequency spectrum computed from the time-domain representation; determining a radial velocity of the at least one object based on a Doppler frequency spectrum computed from the time-domain representation; determining an azimuth angle of the at least one object based on the Doppler frequency spectrum; generating a data structure containing the range, radial velocity and azimuth angle; performing at least one machine learning process on contents of the data structure; and generating at least one control signal for controlling a vehicle based at least in part on a result of performing the machine learning process.

Abstract: A distributed vibration sensing (DVS) system and method provide unified measurement sensitivity along a multi-segment optical fiber route. The system employs a hybrid gain control architecture utilizing both optical and digital gain controls to normalize signal amplitude. An optical gain controller, such as a high-speed variable optical attenuator (VOA) driven by a ramp signal, applies a time-varying attenuation profile to backscattered light. This optical control compensates for continuous fiber attenuation, preventing near-end detector saturation while amplifying far-end signals. A digital signal processor applies localized digital gain adjustments to the digitized backscattered signal to compensate for discrete step losses at connection points between different fiber segments. The combined approach enables uniform visualization of vibration events across the entire route on a fixed-scale waterfall plot.

Abstract: A system, method, and non-transitory computer-readable medium for end-to-end distributed fiber optic sensing are disclosed. The system bypasses traditional digital signal processing (DSP) modules by learning directly from raw 4-channel analog-to-digital converter (ADC) signals. The processing architecture includes a patch tokenizer configured to segment raw time-series signals into discrete patches and a channel encoder to identify signal origins. A Transformer module utilizing multi-head attention performs feature learning directly from the raw data, thereby eliminating fixed gauge length constraints and enabling variable gauge length learning. The end-to-end model achieves high recognition accuracy across complex environmental audio categories and is configured for downstream applications including acoustic recognition, anomaly detection, and infrastructure monitoring.

Abstract: Embodiments of this application provide data transmission methods and apparatuses. In an implementation, a method includes: determining information about a first modulation constellation diagram and communicating with a first device based on the first modulation constellation diagram, wherein the first modulation constellation diagram comprises M constellation points, and wherein the information about the first modulation constellation diagram comprises one of: a value range of M1 constellation points in the first modulation constellation diagram, wherein M1 is an integer greater than or equal to 1 and less than or equal to M; offsets of M1 constellation points in the first modulation constellation diagram relative to M1 constellation points in a reference modulation constellation diagram, wherein M1 is an integer greater than or equal to 1 and less than or equal to M; or a rotation phase of the first modulation constellation diagram relative to a reference modulation constellation diagram.

Abstract: Embodiments of this specification provide acquiring apparatuses, methods, and computer program product. An acquiring apparatus includes a controller, a first near field communication (NFC) module, and a second NFC module. The first NFC module and the second NFC module work under control of the controller. The first NFC module is configured to work in a card reader mode, and in the card reader mode, the first NFC module is configured to transmit a first radio frequency signal, detect first response information, and obtain customer information based on the first response information. The second NFC module is configured to work in a card emulation mode, and in the card emulation mode, the second NFC module is configured to send second response information comprising merchant acquiring information in response to sensing a second radio frequency signal.

Abstract: Disclosed are vehicle-infrastructure interaction systems and methods employing a distributed fiber optic sensing (DFOS) system operating with pre-deployed fiber-optic telecommunication cables buried alongside/proximate to highways/roadways which provide 24/7 continuous information stream of vehicle traffic at multiple sites; only require a single optical sensor cable that senses/monitors multiple locations of interest and multiple lanes of traffic; the single optical sensor cable measures multiple related information (multi-parameters) about a vehicle, including driving speed, wheelbase, number of axles, tire pressure, and others, that can be used to derive secondary information such as weight-in-motion; and overall information about a fleet of vehicles, such as traffic congestion or traffic-cargo volume. Different from merely traffic counts, our approach can provide the count grouped by vehicle-types and cargo weights.

Abstract: A terminal device detects a synchronization signal; the terminal device determines an operating mode of a cell based on the synchronization signal, where the cell supports at least two operating modes with different energy consumption, and the operating mode of the cell has a mapping relationship with at least one of the following: raster information of the synchronization signal and a type of the synchronization signal; and the terminal device accesses a network based on the operating mode of the cell. According to this method, the terminal device can quickly obtain an operating mode of a current cell after being powered on, and further access a network based on the operating mode of the cell.

Abstract: A high-sensitivity forward-transmission vibration sensing system and method for urban fiber infrastructure. The system utilizes adaptive time-frequency (T-F) masking to identify weak vibration events by suppressing common laser phase noise in the time-frequency domain. Accurate localization is achieved through in-band laser phase noise suppression using a detuning matrix to balance correlation terms. The invention enables detection and localization of real-world events, such as footsteps and construction activity, in noisy metropolitan environments where conventional filtering fails.

Abstract: A high-definition distributed fiber optic sensing (HD-DFOS) system and method for traffic monitoring and road condition diagnostics. The system utilizes optical fibers deployed along roadsides to capture high-temporal-resolution vibrational signals, capturing thousands of frames per second to clearly identify ground vibration wavefronts. A high-performance, multi-process computational platform utilizing shared memory converts 16-bit multi-channel transient traces into pseudo-color RGB images.

Abstract: Various embodiments of the teachings herein include workflow execution methods. An example includes: obtaining a workflow and configuration information, wherein the workflow is generated based on a behavior tree construction operation performed by a user on a graphical user interface; configuring an auxiliary process adapted to provide a resource for the workflow based on the configuration information, wherein the auxiliary process is adapted to host a long connection with the resource; and generating a function block process adapted to execute a function block in the workflow, wherein the function block process is adapted to host a first idempotent short connection with the auxiliary process and/or a second idempotent short connection with the resource, and the auxiliary process is decoupled from the function block process.

Abstract: Distributed fiber optic sensing (DFOS) and artificial intelligence (AI) systems and methods for performing utility pole hazardous event localization that advantageously identify a utility pole that has undergone a hazardous event such as being struck by an automobile or other detectable impact. Systems and methods according to aspects of the present disclosure employ machine learning methodologies to uniquely identify an affected utility pole from a plurality of poles. Our systems and methods collect data using DFOS techniques in telecommunication fiber optic cable and use an AI engine to analyze the data collected for the event identification. The AI engine recognizes different vibration patterns when an event happens and advantageously localizes the event to a specific pole and location on the pole with high accuracy. The AI engine enables analyses of events in real-time with greater than 90% accuracy.

Abstract: Provided is the use of a piperidene alkene compound in the preparation of a drug for treating cancer. Specifically, the use of 1?-((7-ethyl-6-carbonyl-5,6-dihydro-1,5-naphthyridin-3-yl)methyl)-N-methyl-1?,2?,3?,6?-tetrahydro-[3,4?-bipyridine]-6-carboxamide or a pharmaceutically acceptable salt thereof in the preparation of a drug for treating cancer. 1?-((7-ethyl-6-carbonyl-5,6-dihydro-1,5-naphthyridin-3-yl)methyl)-N-methyl-1?,2?,3?,6?-tetrahydro-[3,4?-bipyridine]-6-carboxamide or a pharmaceutically acceptable salt thereof has a good inhibitory effect on each cancer cell, and can be used for treating related cancers.

Abstract: A present invention embodiment provides trace-base analysis and memory migration. A trace is performed on a process that is executing one or more preconfigured tasks to collect trace data comprising memory access addresses of the process and function calls of the process. The trace data is analyzed to identify one or more metadata memory regions based on frequent memory accesses and a content memory region based on infrequent memory accesses during the trace. It is determined that a portion of content addresses of the content memory region can be migrated to a remote memory without disrupting execution of the process. The portion of content addresses is migrated to the remote memory. The process is patched to insert remote logic that redirects access operations to the portion of the content addresses to the migrated portion of content addresses in the remote memory. The process is executed.

Abstract: A system and method for distributed fiber-optic sensing (DFOS) event classification utilizing an energy-based generative artificial intelligence model. The method leverages a joint energy-based model (JEM) to ingest both human-annotated labeled sensing data and abundant unlabeled ambient sensing data collected from a DFOS interrogator. The joint energy-based model models the data distribution of high-dimensional spatial-temporal sensing signals, enabling semi-supervised classification that improves generalization, provides calibrated uncertainty estimates, and avoids domain-specific data augmentation constraints. The system further provides a test-time refinement mechanism utilizing Stochastic Gradient Langevin Dynamics (SGLD) updates in the input data space to remove the effects of sensor noise and recover discriminative classification accuracy upon deployment in pre-existing telecom cable networks.

Abstract: A communication method and apparatus. First-stage control information is sent, where the first-stage control information includes scheduling information of second-stage control information. The scheduling information of the second-stage control information includes scheduling information of first data. The second-stage control information is sent, where the second-stage control information is determined based on a first joint encoding result of the first data and first information. The first information is second control information of second data.

Abstract: Systems, methods, and structures providing dynamic line rating (DLR) for overhead transmission lines based on distributed fiber optic sensing (DFOS)/distributed temperature sensing (DTS) to determine temperature of the electrical conductors. Environmental conditions such as wind speed, wind direction, and solar radiation data, are collected from environmental sensors and an acoustic modem that convert the digital data collected from the environmental sensors into generated vibration patterns that are subsequently used to vibrationally excite a DFOS optical sensor fiber. The DFOS system monitors the optical sensor fiber and detects, measures, and decodes the vibrational excitations. An Artificial Neural Network (ANN) determines a heat transfer correlation between the temperature of the optical sensor fiber and electrical conductor(s) (core temperature).

Abstract: The technology of this application relates to a method for determining a feature of a terminal and a communication apparatus. A mandatory feature set in a feature set of a terminal determined by the terminal or a network device is related to a type of the terminal. In this way, a mandatory feature set may be separately defined for different types of terminals. This customizes features of the terminals, helps minimize the features of the terminals, meets feature requirements of the different types of terminals, reduces chip costs and terminal implementation processing complexity, and implements terminal energy saving.

Abstract: In various examples, a multi-sensor fusion machine learning model—such as a deep neural network (DNN)—may be deployed to fuse data from a plurality of individual machine learning models. As such, the multi-sensor fusion network may use outputs from a plurality of machine learning models as input to generate a fused output that represents data from fields of view or sensory fields of each of the sensors supplying the machine learning models, while accounting for learned associations between boundary or overlap regions of the various fields of view of the source sensors. In this way, the fused output may be less likely to include duplicate, inaccurate, or noisy data with respect to objects or features in the environment, as the fusion network may be trained to account for multiple instances of a same object appearing in different input representations.

Abstract: The present disclosure provides methods and compositions for preparing DNA molecules useful for determining a methylation status of selected regions of the DNA molecules. The methods utilize methylation sensitive restriction enzymes, and typically include one or more amplifications or a selective enrichment of target regions.