Sun Yat-sen University

The present invention discloses a skeleton sequence recognition method based on a masked graph autoencoder, including the following steps: building a skeleton action recognition model, using the skeleton action recognition model to recognize a skeleton sequence, and implementing prediction of an action category, where said skeleton action recognition model includes a spatio-temporal representation learning model at a M layer and a classifier at one layer; and said spatio-temporal representation learning model includes two masked graph autoencoders connected in parallel, and an output end of the masked graph autoencoder is residually connected to an input end thereof through 1×1 convolution.

A data processing method and apparatus, an electronic device, and a storage medium are disclosed. The method may include determining a prediction table corresponding to attribute information of a point cloud; determining, a residual according to the prediction table; and encoding the residual and the index of the predicted value to form a code stream for transmission or storage.

Provided is a three-dimensional object detection framework based on multi-source data knowledge transfer. By outputting an image feature extracted by an image feature extraction unit, an interested target selection unit outputs point cloud data of an interested target to a point cloud feature extraction unit according to the image feature; the point cloud feature extraction unit extracts a point cloud feature from the point cloud data; in a knowledge transfer unit, enable the image feature to learn the point cloud feature and update parameters of the image feature extraction unit, while a three-dimensional target parameter prediction unit updates parameters of the image feature and point cloud feature extraction units according to the image feature and the point cloud feature. Finally, the updated image feature extraction unit re-extracts the image feature to the three-dimensional target parameter prediction unit, which reckons and inputs three-dimensional parameters according to the image feature.

The present application provides methods and compositions for treating diseases or disorders related to hematopoietic dysfunctions and/or injuries, or for rejuvenating HSPCs.

A method for simulating polyurethane permeation grouting diffusion includes constructing a geometric model of permeation grouting diffusion of polyurethane in a porous medium to be injected based on physical property data of the porous medium to be injected; establishing a physical field of the geometric model using a Richards equation and a dilute species transport equation for a porous medium, and adjusting the geometric model based on a material property parameter of the geometric model obtained based on the physical field; setting a boundary condition and an initial value for an adjusted geometric model, and performing mesh division on the adjusted geometric model based on a local refinement method to obtain a simulation model for permeation grouting diffusion; and solving the simulation model for permeation grouting diffusion using a transient solver to complete the simulation of permeation grouting diffusion of the polyurethane in the porous medium to be injected.

An isotope analysis system includes: a first liquid channel, second liquid channels, third liquid channels, fourth liquid channels connected with a heating reactor, a diverter, and a selector valve. The diverter is configured to divert liquid from the first liquid channel to the third liquid channels. The selector valve comprises a first liquid outlet and a plurality of first liquid inlets. A third liquid channel and a fourth liquid channel are assigned to each of the plurality of second liquid channels; an end of the fourth liquid channel is connected to both an end of the second liquid channel and an end of the third liquid channel; and a first liquid inlet is assigned to each of the plurality of fourth liquid channels, and another end of the fourth liquid channel is connected to the first liquid inlet.

A disaster smoke detection method includes: performing a first convolution operation on an input image to extract features to generate a primary feature map; performing enhancement processing on the primary feature map to obtain an enhanced feature map; performing multi-scale fusion on the enhanced feature map according to a second convolution operation to obtain a plurality of feature maps of different scales as high-level feature maps; respectively performing top-down feature fusion and bottom-up feature fusion on each high-level feature map at each scale according to a third convolution operation to correspondingly obtain a plurality of top-down fused feature maps and a plurality of bottom-up fused feature maps; fusing the top-down fused feature maps and the bottom-up fused feature maps to obtain a plurality of bidirectional cross-fused feature maps; and performing disaster and smoke detection on each of the bidirectional cross-fused feature maps.

A method for preparing a diester by oxidative carbonylation of an olefin and carbon monoxide, which comprises the following steps: carrying out an oxidative carbonylation reaction on olefin and carbon monoxide in an oxygen-containing atmosphere and in the presence of a catalyst to obtain a 1,4-diester-based compound; the catalyst comprises a procatalyst, a pro-oxidant, an acid, and a dehydrating agent; and the procatalyst is a substance comprising the element Pd; the pro-oxidant comprises one or more among copper salt, iron salt, and iron powder; the acid comprises Lewis acid and/or protonic acid; and the dehydrating agent comprises one or more among a ketal, an acetal, orthoformate, and silicate. The present method has high catalytic efficiency, high selectivity, and a high conversion rate; oxygen or air is used as an oxidizing agent; the catalyst is a green, low-carbon, environment-friendly catalytic system that can be reused, is low-cost, and produces essentially no waste in the production process; and the oxidative carbonylation reaction of the catalyzed olefin and CO prepares the 1,4-diester compound.

A bionic event imaging system, which includes: a lens or lens group for collecting the light from the external environment; a controllable blink module comprising a photomask and a control unit for the closing-opening operation of the photomask; and a dynamic vision sensor for detecting the brightness change of the optical signal incident through the controllable blink module, and triggering an event when the brightness change exceeds a preset threshold. The controllable blink module is used to control blocking or allowing the light of the external environment to enter. The photomask correspondingly covers all or part of the light detection units in the dynamic vision sensor at the maximum closed state. The event processing unit, for decoding the event stream generated by the dynamic vision sensor, and reconstructing the absolute light intensity images of static scenes and dynamic scenes in the external environment.

A Weibull function is used to randomly assign the linear elastic limit bond stretch and tensile limit bond stretch of each material point of a material to be analyzed after a quantitative discrete processing is performed on the material to be analyzed; based on the discrete processing result, relative position vector, relative displacement vector, bond stiffness, and a bond stretch of any two material points in a group are sequentially calculated, and a bilinear damage function and a bond-based peridynamics constitutive equation are constructed; based on the constitutive equation, the coordinate information of each material point and the bond stretch are cyclically updated time step by time step bond stretch and a value of the bilinear damage function is obtained, and the group information is updated; a local damage value of each material point is calculated to analyze the fracture situation and obtain the damage determination result.