Abstract: A logic cell structure includes a first portion, a second portion and a third portion. The first portion, arranged to be a first layout of a first semiconductor element, is placed in a first cell row of a substrate area extending in a first direction. The second portion, arranged to be a second layout of a second semiconductor element, is placed in a second cell row of the substrate area. The third portion is arranged to be a third layout of an interconnecting path used for coupling the first semiconductor element and the second semiconductor element. The first, second and third portions are bounded by a bounding box with a height in a second direction and a width in the first direction. Respective centers of the first portion and the second portion are arranged in a third direction different from each of the first direction and the second direction.

Abstract: The method for manufacturing the semiconductor structure includes: providing a substrate, and forming contact holes in the substrate; depositing a metal at a bottom of each contact hole, and performing a reverse sputtering treatment to form a metal layer; in the reverse sputtering treatment, metal atoms or metal ions are sputtered onto at least a part of a side wall of each contact hole; performing a annealing treatment, to cause the substrate reacts with the metal layer to form a metal silicide layer.

Abstract: Provided are a complex of an anti-IL-4R antibody or an antigen-binding fragment thereof, and a medical use thereof. Specifically, provided are a complex of an antibody that specifically binds to IL-4R or an antigen-binding fragment thereof covalently linked to a toxin, a pharmaceutical composition comprising the complex, and a use thereof in the preparation of a drug for treating IL-4R-mediated diseases or disorders, especially a use in the preparation of an anti-cancer drug.

Abstract: A gain control method for a signal amplifier includes obtaining, by the signal amplifier, target information; determining, by the signal amplifier, a power adjustment parameter of the signal amplifier according to the target information, where the power adjustment parameter includes any one of the following: an amplification multiple-related parameter and a transmit power-related parameter; and adjusting, by the signal amplifier, a power parameter of the signal amplifier according to the power adjustment parameter, where the power parameter includes any one of the following: an amplification multiple and transmit power.

Abstract: A user equipment includes a control unit that controls transmission or reception of a sidelink signal in which a first resource and a second resource are multiplexed in a same slot, wherein at least one of SLSS (Sidelink synchronization signal) or PSBCH (Physical Sidelink Broadcast Channel) is allocated in the first resource, and at least one of PSCCH (Physical Sidelink Control Channel), PSSCH (Physical Sidelink Shared Channel), and PSDCH (Physical Sidelink Discovery Channel) is allocated in the second resource; a reception unit that monitors the first resource, the second resource, or the first resource and the second resource; and a transmission unit that performs transmission using any one of the first resource, the second resource, and the first resource and the second resource.

Abstract: Embodiments described herein provide systems and methods for training a sequential recommendation model. Methods include determining a difficulty and quality (DQ) score associated with user behavior sequences from a training dataset. User behavior sequences are sampled during training based on their DQ scores. A meta-extrapolator may also be trained based on user behavior sequences sampled according to DQ score. The meta-extrapolator may be trained with high quality low difficulty sequences. The meta-extrapolator may then be used with an input of high quality high difficulty sequences to generate synthetic user behavior sequences. The synthetic user behavior sequences may be used to augment the training dataset to fine-tune the sequential recommendation model, while continuing to sample user behavior sequences based on DQ score. As the DQ score is based on current model predictions, DQ scores iteratively update during the training process.

Abstract: Described herein, a transparent soap bar for cleaning the skin including a soap surfactant, a synthetic surfactant, a fragrance component, an amine component, an antioxidant salt, wherein the transparent soap bar has a percent transmittance (% T) value of greater than 40% as measured using the method of Measurement of % Transmittance.

Abstract: An object drag method includes a first terminal that displays an object on a display of the first terminal. The first terminal receives a drag operation from a user. The drag operation initiates a drag for the object. The first terminal displays, on the display of the first terminal in response to the drag operation, an animation in which the object moves with the drag operation. The first terminal sends drag data to a second terminal after determining that a drag intent of the user is a cross-device drag. The drag data enables the second terminal to display the object on a display of the second terminal.

Abstract: A conversation engine performs conversations with users using chatbots customized for performing a set of tasks that can be performed using an online system. The conversation engine loads a chatbot configuration that specifies the behavior of a chatbot including the tasks that can be performed by the chatbot, the types of entities relevant to each task, and so on. The conversation may be voice based and use natural language. The conversation engine may load different chatbot configurations to implement different chatbots. The conversation engine receives a conversation engine configuration that specifies the behavior of the conversation engine across chatbots. The system may be a multi-tenant system that allows customization of the chatbots for each tenant.

Abstract: A user equipment includes a receiving unit configured to receive a physical control channel and a physical shared channel from another user equipment; a control unit configured to calculate a distance that is an estimated distance between the another user equipment and the user equipment, based on information acquired via the physical control channel; and a transmitting unit configured to determine whether to transmit, via a channel used for transmitting and receiving a response relating to retransmission control, the response relating to the retransmission control of the physical shared channel transmitted from the another user equipment, based on the calculated distance.

Abstract: This application provides a touch sensor, a touch display, and an electronic device. The touch sensor includes a substrate, a bridge electrode line, and an electrode layer. The electrode layer includes at least a first electrode pattern, the first electrode pattern includes a plurality of first conductive units spaced from each other, a boundary line of the first conductive unit includes a curved connecting segment, the connecting segment includes at least one first concave and convex portion, and first concave and convex portions are sequentially connected to form a smooth curve. The bridge electrode line extends in a curve, and two ends respectively cross connecting segments of two adjacent first conductive units, and electrically connect the two first conductive units. The touch sensor provided in the embodiments of this application improves bending resistance performance of a touch electrode.

Abstract: This application discloses a transmission parameter management method and apparatus, and an electronic device. The transmission parameter management method is executed by a first integrated access backhaul IAB node and includes: obtaining assistance information related to a transmission parameter of a second IAB node and/or assistance information related to a measurement parameter; and determining a transmission parameter based on the assistance information.

Abstract: One or more fields can be divided into portions, and different sets of interventions can be performed during the course of planting and growing a crop in each field portion. The effect of each set of interventions on the crop outcome of the corresponding field portion can be determined using a best performing model of a set of predictive models applied to the set of interventions. The selected model can be used to determine an effect of each intervention on crop outcome of a field portion by estimating a portion of the crop outcome attributable to the intervention. A machine-learned model can be trained based on the effect each intervention has on crop outcome determined by the selected model, and the machine-learned model can be applied to subsequent fields and crops to predict effects that various interventions can have on subsequent crop outcomes.

Abstract: Embodiments described herein provide a universal item learning framework that generates universal item embeddings for zero-shot items. Specifically, the universal item learning framework performs generic features extraction of items and product knowledge characterization based on a product knowledge graph (PKG) to generate embeddings of input items. A pretrained language model (PLM) may be adopted to extract features from generic item side information, such as titles, descriptions, etc., of an item. A PKG may be constructed to represent recommendation-oriented knowledge, which comprise a plurality of nodes representing items and a plurality of edges connecting nodes represent different relations between items. As those relations in PKG are usually retrieved from user-item interactions, the PKG adapts the universal representation for recommendation with knowledge of user-item interactions.

Abstract: Disclosed herein are a method and a device for remotely diagnosing vehicle faults, a vehicle and a computer storage medium. The method includes monitoring vehicle data uploaded by the vehicle in real time via a cloud platform, and determining whether to identify a preset fault abnormal signal identification from target data of the vehicle data. The method also includes, in response to the fault abnormal signal identification being identified from the target data, sending a fault diagnosis task to the vehicle according to the target data, and receiving diagnosis result data returned by the vehicle after the fault diagnosis task is executed locally by the vehicle. The method further includes generating a remote fault diagnosis result of the vehicle according to the vehicle data and the diagnosis result data.

Abstract: Disclosed herein are a vehicle thermal runaway warning method, device, electronic equipment and readable storage medium. The method of vehicle thermal runaway warning includes obtaining operating data of a vehicle, the operating data including a plurality of cell voltage data of a battery pack in the vehicle, and dividing time windows for the plurality of cell voltage data according to a collection timing of the operating data. The method also includes extracting cell voltage characteristics from a partial cell voltage data corresponding to each of the divided time windows. The method further includes, in response to each cell voltage characteristic meeting a preset voltage warning condition, determining that the vehicle has a risk of thermal runaway, and controlling the vehicle to output thermal runaway warning information.

Abstract: A method for determining a sidelink feedback resource includes determining, by a first UE, a first resource, where the first resource is one or more resources used by the first UE to perform a channel access procedure.

Abstract: A conversation engine performs conversations with users using chatbots customized for performing a set of tasks that can be performed using an online system. The conversation engine loads a chatbot configuration that specifies the behavior of a chatbot including the tasks that can be performed by the chatbot, the types of entities relevant to each task, and so on. The conversation may be voice based and use natural language. The conversation engine may load different chatbot configurations to implement different chatbots. The conversation engine receives a conversation engine configuration that specifies the behavior of the conversation engine across chatbots. The system may be a multi-tenant system that allows customization of the chatbots for each tenant.

Abstract: A sidelink resource recommendation method and apparatus, a device, and a readable storage medium are provided. The sidelink resource recommendation method according to embodiments of this disclosure includes: selecting, by a first terminal, a sidelink resource. The sidelink resource includes one or more of the following: a first resource and a second resource. The second resource is used for the first terminal to transmit first information to the second terminal. The first information is used for the first terminal to recommend the first resource to the second terminal.