Abstract: The invention provides systems and methods for a vehicle-based cloud computing system (VCCS) for autonomous driving. This VCCS builds world models based on a series of complex scenario data to optimize sensing, prediction, planning, decision making, and control for autonomous driving. The VCCS can execute vehicle control algorithms, train general AI models, and make inferences to optimize autonomous driving. Specifically, it dynamically adjusts driving strategies based on long tail scenarios including but not limited to weather, work zone information, and traffic status, ensuring safe and efficient vehicle operation. Additionally, the VCCS can gather supplementary data from (a) a roadside unit (RSU) network, (b) another OBU, (c) a cloud platform, (d) a traffic control center/traffic control unit (TCC/TCU), and (e) a traffic operations center (TOC), thereby further improving control and efficiency in complex driving environments.

Abstract: An array substrate includes a base substrate, a first conductive layer, a first electrode, an organic planarization layer and an organic active layer. The first conductive layer is provided on a side of the base substrate. The first electrode is provided on a side of the first conductive layer away from the base substrate, an orthographic projection of the first electrode on the base substrate overlapping an orthographic projection of the drain electrode on the base substrate. The organic planarization layer is provided on a side of the first electrode away from the base substrate, first via holes being provided in the organic planarization layer. The organic active layer is provided on a side of the organic planarization layer away from the base substrate, the organic active layer being connected to the source electrode by a first via hole and connected to the drain electrode by a first via hole.

Abstract: This technology provides systems and methods for a vehicle computing system (VCS) for autonomous driving. This VCS furnishes End-to-End models that provide sensing, prediction, planning, decision-making, and control functions. The VCS executes vehicle control algorithms, trains general AI models, and makes inferences from those AI models. Specifically, a computing subsystem of the VCS performs computation methods that train a tensor-centered model and/or make inferences from a tensor-centered model. Additionally, the VCS gathers data from a roadside unit network, an onboard unit, a cloud platform, a traffic control center/traffic control unit, and a traffic operations center (TOC), thereby enhancing the safety and efficiency of autonomous driving.

Abstract: The present disclosure provides a display panel and a display device. The display panel includes a plurality of pixel units distributed in an array. The pixel unit includes: a pixel driver circuit configured to provide a driving current, a plurality of sub-pixels configured to emit light under an action of the driving current, and a switching circuit including a plurality of switching units arranged in correspondence with the plurality of sub-pixels. The switching unit is connected in series between the pixel driver circuit and a corresponding sub-pixel, a control end of the switching unit is configured to receive a switching signal, a first end of the switching unit is connected to the pixel driver circuit, a second end of the switching unit is connected to the corresponding sub-pixel, and the switching unit conducts a communication path between the sub-pixel and the pixel driver circuit in response to the switching signal.

Abstract: A method includes modeling a reservoir using a lab scale set of models and a field scale set of models. The reservoir is modeled using the lab scale set of models by scanning a sample of the reservoir into the lab scale set of models to create modeled fractures, estimating hydraulic properties of the modeled fractures, estimating multi-phase dynamic properties of the modeled fractures, and determining characteristics of a flow regime of a fluid flowing through the modeled fractures. The reservoir is modeled using the field scale set of models by modeling a discrete fracture network of the reservoir, upscaling the discrete fracture network, and calibrating the discrete fracture network. An enhanced oil recovery operation is designed and performed on the reservoir using the calibrated discrete fracture network.

Abstract: The present invention provides a virtual subscriber identity module (vSIM) for network connection. The vSIM includes a memory and at least one processor. The memory is configured to store a remote SIM (rSIM) implemented as a software card. The at least one processor is coupled to the memory and configured to: register to a first network and download a vSIM profile from a vSIM server via the rSIM; and complete a registration to a second network using the vSIM profile for activating a vSIM service to connect to the second network. The present invention further provides an apparatus including the vSIM, a vSIM server for communicating with the apparatus, and a method performed by the apparatus.

Abstract: Provided herein is a technology for an Autonomous Vehicle Cloud System (AVCS). This AVCS provides sensing, data fusion, prediction, decision-making, and/or control instructions for specific vehicles at a microscopic level based on data from one or more of other vehicles, roadside unit (RSU), cloud-based platform, and traffic control center/traffic control unit (TCC/TCU). Specifically, the AVs can be effectively and efficiently operated and controlled by the AVCS. The AVCS provides individual vehicles with detailed time-sensitive control instructions for fulfilling driving tasks, including car following, lane changing, route guidance, and other related information. The AVCS is configured to predict individual vehicle behavior and provide planning and decision-making at a microscopic level. In addition, the AVCS is configured to provide one or more of virtual traffic light management, travel demand assignment, traffic state estimation, and platoon control.

Abstract: A touch substrate and a display panel are provided by this disclosure. The touch substrate includes a plurality of touch units, each touch unit has a first electrode and a second electrode. The first electrode includes a first trunk electrode and a plurality of first branch electrodes. The first trunk electrode is parallel to a first direction. The first branch electrodes are disposed on two sides of the first trunk electrode. The first branch electrodes extend outwardly with the first trunk electrode as a center to form a radial structure. The second electrode includes a second trunk electrode and a plurality of second branch electrodes. The second trunk electrode is parallel to a second direction. The second branch electrodes are disposed on two sides of the second trunk electrode. The first branch electrodes and the second branch electrodes are alternately disposed to form an occlusal structure.

Abstract: The present disclosure discloses a preparation method and application of decellularized extracellular matrix tissue paper, and belongs to the technical field of regenerative medicine. The preparation method includes the following steps: (1) preparing decellularized extracellular matrix materials; (2) preparing tissue paper: homogenizing and stirring the prepared decellularized extracellular matrix materials, then, placing the obtained homogenates on a flat-bottom filter screen to filter out water, standing and air-drying the filtered homogenates, and freeze-drying the homogenates to obtain the tissue paper; (3) cross-linking the tissue paper: cross-linking the tissue paper in a cross-linking solution; and (4) freeze-drying or stacking and compacting the cross-linked tissue paper. According to the present disclosure, the decellularized extracellular matrix tissue paper with tissue specificity is prepared by a traditional paper-making technology combined with a freeze-drying technology.

Abstract: Provided herein is a technology for an Autonomous Vehicle Intelligent System (AVIS), which facilitates vehicle operations and control for autonomous driving. The AVIS and related methods provide vehicles with vehicle-specific information for a vehicle to perform driving tasks such as car following, lane changing, and route guidance. The AVIS comprises an onboard unit (OBU), wherein the OBU comprises a communication module communicating with one or more of other autonomous vehicles (AV), a roadside unit (RSU), a cloud platform, and a traffic control center/traffic control unit (TCC/TCU). The AVIS implements one or more of the following functions: sensing, prediction, decision-making, and vehicle control using onboard information and vehicle-specific information received from other AVs, the RSU, the cloud platform, and/or the TCC/TCU.

Abstract: The present invention discloses a green knowledge recommendation method based on characteristic similarity and user demands, an electronic device and a computer readable storage medium thereof. The method includes: obtaining a current-search text e and a historical-search-texts set Eu both from a user; constructing a topics dictionary and a subtopics dictionary according to a green knowledge base, and decomposing the e and the Eu on the basis of semantic decomposition; picking words in a text-vector set and a valid-text set that about two dictionaries; finding the corresponding knowledge according to user satisfaction. The invention enables users to quickly find the required content through templating, thus avoiding users' meaningless search, improving search efficiency, and reducing the loss of useless time.

Abstract: The invention provides systems and methods for a computing power allocation system for autonomous driving (CPAS-AD), which is a component of an Intelligent Road Infrastructure System (IRIS). The CPAS-AD incorporates advanced computing capabilities that effectively allocate computational power for sensing, prediction, planning, decision-making, and control functions to enable end-to-end driving functions. In addition to the vehicle, the CPAS-AD can acquire additional computation resources from one or more of: (a) a roadside unit (RSU) network, (b) a cloud platform, (c) a traffic control center/traffic control unit (TCC/TCU), and (d) a traffic operations center (TOC). Additionally, tailored to different traffic scenarios, the CPAS-AD can allocate data and computation resources (including but not limited to CPU and GPU) for vehicle sensing, prediction, planning, decision-making, and control functions, thereby enabling safe and efficient autonomous driving.

Abstract: An array substrate, a method for manufacturing an array substrate, a liquid crystal cell and a display apparatus are provided. The array substrate includes: a first base substrate; thin film transistors; a first planarization layer; a common electrode on a side of the first planarization layer away from the thin film transistors; a first dielectric layer on a side of the common electrode away from the first planarization layer; first pixel electrodes on a side of the first dielectric layer away from the common electrode; the first pixel electrodes are electrically connected to the thin film transistors in a one-to-one correspondence through first vias extending through the first dielectric layer and the first planarization layer; a surface of each first pixel electrode away from the first base substrate is provided with a first groove at least corresponding to a corresponding first via.

Abstract: Methods, systems, and computer-readable storage media for receiving metric data of a cloud system periodically; transforming the metric data of each type into a byte array using mapping tables, wherein the byte array is an encoded format of the metric data, where each field of the metric data is encoded as a field ID and a field type ID that are short integer variables; merging and storing the byte arrays of multiple metric data into a binary file, wherein the binary file comprises multiple blocks with each block comprising multiple byte arrays; generating indexes for common fields of different metric data in the binary file; receiving a retrieval request requesting metric records including a common field of a particular value; determining storage locations of one or more metric records satisfying the retrieval request; and obtaining the one or more metric records from the binary file using the corresponding storage locations.

Abstract: The invention provides systems and methods for a function-based computing power allocation system (FCPAS), which is a component of an Intelligent Road Infrastructure System (IRIS). The FCPAS incorporates advanced computing capabilities that effectively allocate computational power for prediction, planning, and decision making functions. Specifically, through the FCPAS, an AV can acquire additional computational resources for vehicle prediction, planning, and decision-making functions, thereby enabling safe and efficient autonomous driving. Additionally, tailored to different traffic scenarios, the FCPAS can allocate data and computational resources (including but not limited to CPU and GPU) for vehicle automation.

Abstract: The present application provides an instruction encoding-based data processing method and apparatus, and a device. N-path error correction encoding is performed on an instruction in information to be processed to obtain N encoded instructions, the encoded instructions and encoded meta channel programs obtained by the error correction encoding are used to perform redundant processing on data to be processed to obtain N pieces of response data, and then error correction decoding is performed on the N pieces of response data to obtain processing result information of the information to be processed. Because the N encoded instructions are heterogeneous and the encoded meta channel programs used in the N-path processing are heterogeneous, the randomness of the processing process can be improved, generalized disturbance in the data processing process can be corrected in combination with the error correction encoding and decoding methods, and thus the security of data processing is improved.

Abstract: An xenon lamp power supply, a purification device, and a refrigeration device are provided. The xenon lamp power supply comprises: an input circuit, a coupling assembly, an output circuit, and a control circuit. The input circuit comprises an alternating-current input end and a direct-current output end, and the input circuit is used for converting alternating current input by the alternating-current input end into direct current output by the direct-current output end. A first end of the coupling assembly is connected to the direct-current output end. The output circuit comprises a xenon lamp power supply circuit, and the xenon lamp power supply circuit is connected to a second end of the coupling assembly, so as to convert electric energy from the second end into direct-current power, and then supply power to a xenon lamp.

Abstract: The present application provides a biological active peptide from seawater pearl, the sequence of which is Ile-Pro-Ser-Thr-Thr-Pro-Phe-Pro-Ser-Thr-Thr-Val-Ala-Thr-Thr-Thr-Met, and the name of which is SCOL polypeptide. The biological active peptide can improve an ACE2 enzyme activity to 3.76 times, and can be applied in preparation of a drug improving an ACE2 activity, treating hypertension, anti-heart failure, anti-tissue fibrosis, anti-inflammation, and type 2 diabetes mellitus and the complication thereof, and relieving neuropathic pain. The biological active peptide can be specifically bound to the ACE2, effectively inhibits the 65% binding between novel coronavirus S protein and the ACE2, can be applied in preparation of an anti-coronavirus infection drug as an inhibitor, and specifically applied in preparation of anti-novel coronavirus drug.

Abstract: The technology provided herein relates to a roadside infrastructure sensing system for Intelligent Road Infrastructure Systems (IRIS) and, in particular, to devices, systems, and methods for data fusion and communication that provide proactive sensing support to connected and automated vehicle highway (CAVH) systems.