Abstract: A liquid crystal projection layer for use in a glass, the glass including a first glass which includes a first surface and a second surface opposite to each other, the liquid crystal projection layer includes a transparent projection layer disposed on a side of the first glass close to the second surface and configured to display a projected image received from a projector; and a liquid crystal module disposed between the first glass and the transparent projection layer and configured to be switchable between a transparent mode and a privacy mode, wherein in the transparent mode, the liquid crystal module allows the projected image displayed on the transparent projection layer to be transmitted towards the first glass, and in the privacy mode, the liquid crystal module prevents the projected image displayed on the transparent projection layer from being transmitted towards the first glass.

Abstract: A light guide layer for vehicle glass, a vehicle glass and a vehicle interior lighting system are provided. The light guide layer or vehicle glass includes a transparent body or a glass body including a first surface and a second surface arranged opposite to each other, and the transparent body being adapted to be couple to vehicle glass, so as to receive light-source light emitted from a light source arranged at a predetermined position of a vehicle and allow the light-source light to propagate within the transparent body; and a light diffusion part formed in the transparent body or the glass body or on at least one of the first surface and the second surface and configured to diffusely reflect, scatter and/or refract the light-source light propagating to the light diffusion part to a predetermined area of at least one of the first surface and the second surface, so as to emit the light-source light out from the predetermined area.

Abstract: A method for detecting and tracking target object in a captured video using convolutional neural network (CNN) is provided. The method includes: inputting image data into a detecting model to generate detection results, wherein the detecting model is constructed by the CNN; inputting the image data into tracking models to generate tracking results; performing detection score enhancement operation according to the detection results and the tracking results to obtain enhanced detection results; matching the enhanced detection results and the tracking results by a matching operation; processing matched results and unmatched target detection results and unmatched target tracking results; and selectively updating the tracking models using tracking reliability estimation according to the matched results.

Abstract: A control method for an electronic device and an electronic device are provided. The electronic device includes an infrared emitter, an infrared sensor, and a visible light sensor. The control method includes: acquiring an original pixel position of a zero-level region on the infrared sensor; acquiring a human eye pixel position of a human eye region on the visible light sensor; determining whether a human eye enters the zero-level region according to the original pixel position and the human eye pixel position; and triggering a protection mechanism of the infrared emitter when the human eye enters the zero-level region.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of storing, for each respective customer of one or more customers, respective customer information in a customer database; predicting, using a machine learning lifetime value (LTV) update model, a respective LTV for each respective customer of the one or more customers; determining an online advertisement for each respective customer of the one or more customers using the respective LTV, as predicted, for each respective customer of the one or more customers; and coordinating displaying the online advertisement for at least a portion of the one or more customers. Other embodiments are disclosed herein.

Abstract: A braking method for a vehicle is provided. The method includes the following steps: obtaining a first state information of the vehicle, where the first state information includes a vehicle mass and a deceleration required by braking; calculating a braking torque required by the vehicle according to the first state information, and controlling an output of an electric braking torque according to the braking torque required by the vehicle; obtaining a current gradient and a current vehicle speed of the vehicle; and determining whether to control the vehicle to unload the electric braking torque, and whether to control the vehicle to apply a mechanical braking torque according to the current vehicle speed, the braking torque required by the vehicle, the deceleration required by braking, and the current gradient. A braking device for a vehicle and a vehicle are further provided.

Abstract: In one aspect, the disclosure relates to a synthetic modified mRNA (modRNA) and a novel gene therapy approach using the same that offers efficient, transient, safe, nonimmunogenic, and controlled mRNA delivery to the heart tissue without any risk of genomic integration. In a further aspect, the disclosure relates to methods of using the modRNA to achieve transient and exclusive overexpression of CCND2 only in cardiomyocytes, increasing cell cycle markers, enhancing cardiac function, and promoting myocardial repair. This abstract is intended as a scanning tool for purposes of searching in the particular art and is not intended to be limiting of the present disclosure.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations including: reducing, using a multilayer perceptron, a dimension of feature embeddings for an item to generate a representation vector; extracting, using a recurrent neural network, sequential data from traffic features for the item; inputting the representation vector and the sequential data into a multilayer neural network, wherein the first scoring layer outputs one or more first performance metrics based on offline learning; and re-purposing the output of the second ReLU activation function of the multilayer neural network by feeding the output of the second ReLU activation function into a second scoring layer to output one or more second performance metrics based on online learning. Other embodiments are disclosed.

Abstract: A point cloud encoding and decoding method and a point cloud decoder are provided in the disclosure. The point cloud encoding includes the following. Geometry information and attribute information of points in a point cloud are obtained. Prediction values of the attribute information of the points in the point cloud are determined according to the geometry information of the points in the point cloud. Residual values of the attribute information of the points in the point cloud are determined according to the prediction values of the attribute information of the points in the point cloud. The residual values of the attribute information of the points in the point cloud are processed with a first encoding process, where lossless encoding is performed on a residual value of attribute information of at least one point in the point cloud in the first encoding process.

Abstract: A multi-functional, computer-aided gastroscopy system optimized with integrated AI solutions is disclosed. The system makes use of multiple deep-learning neural models to achieve low latency and high-performance requirements for multiple tasks. The optimization is made at three levels: architectural, modular and functional level. At architectural level, the models are designed in such a way that it is able to accomplish HP infection classification and detection of some lesions for one inference in order to reduce computation costs. At modular level, as a sub-model of HP infection classification, the site recognition model is optimized with temporal information. It not only improves the performance of HP infection classification, but also plays important roles for lesion detection and procedure status determination. At functional level, the inference latency is minimized by configuration and resource aware optimization.

Abstract: According to an aspect, there is provided a computer-implemented method (300; FIG. 3) for interacting with a user of a personal care device (FIG. 1; 102). The method (300; FIG. 3) comprises receiving (302, FIG. 3) device usage data indicative of a manner in which the personal care device is used by the user during a usage instance of the personal care device, the device usage data relating to one or more of a defined set of device usage parameters; receiving (304) performance data indicative of an outcome of the usage instance, the performance data relating to one or more of a defined set of performance parameters; and responsive to a determination that one or more of the received device usage data and the received performance data differ from stored reference device usage data and stored reference performance data, respectively, by more than a defined threshold amount, generating (306) a user input request to be presented to the user. An apparatus, a system and a computer program product are also provided.

Abstract: Provided are a point cloud encoding method and decoding method, and an encoder and a decoder. The encoding method comprises: processing attribute information of a target point in a point cloud, so as to obtain a predicted residual of the attribute information of the target point; quantizing the predicted residual on the basis of a quantized weight of the target point and a quantized stride of the target point, so as to obtain a quantized residual of the attribute information of the target point, wherein the quantized weight of the target point is the weight used when weighting the quantized stride of the target point; and encoding the quantized residual, so as to obtain a code stream.

Abstract: The present disclosure provides a display panel comprising a bottom emitting type array substrate and a wavelength converting unit, wherein the wavelength converting unit is in contact with a transparent substrate layer of the array substrate, and the transparent substrate layer has a thickness of 5 ?m or less. The present disclosure also provides a method for manufacturing the display panel by using a subtractive manufacture process.

Abstract: A method includes a server computer receiving a dataset comprising data associated with a plurality of service providers. The server computer can extract a plurality of features from the dataset. The features include user intent features, off-platform features, and on-platform features. The server computer can train a machine learning model using training data based on the plurality of features of at least some of the service providers. For one or more candidate service providers of the plurality of service providers, the server computer can determine a predicted rank and a predicted value for each of the one or more candidate service providers using the trained machine learning model.

Abstract: A point cloud decoding method, a point cloud encoding method, and a decoder are provided in implementation of the disclosure. The decoding method includes the following. A bitstream of a point cloud is parsed to obtain an initial reconstructed value of attribute information of a target point in the point cloud. The initial reconstructed value is converted into an initial luma value and an initial chroma value. A final chroma value is obtained by filtering the initial chroma value with a Kalman filtering algorithm. A final reconstructed value of the attribute information of the target point is obtained based on the final chroma value and the initial luma value. A decoded point cloud is obtained according to the final reconstructed value of the attribute information of the target point.

Abstract: A method for blocking mine water inrush includes: grouting first slurry into an interface between the quaternary aquifer and the weathered bedrock aquifer in a fracture grouting manner until a first preset condition is met; forming a first water-resisting cushion after the first slurry is solidified; drilling a curve branch drill hole in the surface horizon downward; grouting second slurry into the curve branch drill hole in a downward grouting manner until a second preset condition is met; forming a second water-resisting cushion after the second slurry is solidified; grouting third slurry onto a top of the first water-resisting cushion in an upward grouting manner until a third preset condition is met; forming a third water-resisting cushion after the third slurry is solidified; wherein the third water-resisting cushion is located on the top of the first water-resisting cushion.

Abstract: Devices and techniques for continuously monitoring pressure and simultaneously monitoring changes in blood flow, vascular resistance, and/or vascular behavior are provided. The techniques are employed in measuring intracranial pressure (ICP), while simultaneously measuring cerebral blood flow and/or cerebrovascular resistance or behavior. A sensor device includes an optical and piezoelectric sensing assembly integrated into a deployable ICP monitoring device.

Abstract: The present disclosure is related to a display substrate. The display substrate may include a base substrate, a display structure on a display area of the base substrate, at least one blocking structure on a peripheral area around the display area of the base substrate, and a first water-blocking layer on the substrate. The first water-blocking layer may cover the display structure and the at least one blocking structure. The blocking structure may be configured to block cracks generated on the first water-blocking layer at a side of the blocking structure opposite from the display area from propagating to the display area.

Abstract: Disclosed in embodiments of the present application are a point cloud encoding method, a point cloud decoding method, an encoder, a decoder, and a computer storage medium. The point cloud encoding method comprises: an encoder determining n target neighbouring points of a current point; determining a target prediction mode from k prediction modes on the basis of geometric information of the n target neighbouring points; determining a prediction value of attribute information of the current point according to the target prediction mode and attribute information of the n target neighbouring points; and encoding the current point according to the prediction value.

Abstract: A gelable system is formed by mixing lithium salts and small-molecule ether compounds such as cyclic ether compounds or straight-chain ether compounds, optionally added with inorganic nanoparticles, additives, other solvents and/or electrolytes; a gel system or solid system is formed by interaction between them (such as the formation of new complexes or self-assembly, etc.), and by ring-opening polymerization or polycondensation of the small-molecule cyclic ether compounds, or by addition-fragmentation chain transfer polymerization of the small-molecule straight-chain ether compounds, etc. The gel system or solid system not only has better safety in use than common gel systems or solid systems, but also better adjustability of strength. The strength of the formed gel can be improved from the source by changing composition and type of raw materials. The improvement in the strength enables the gel system to be expanded into the solid system, thereby further extending the application range of the gel system.