Chinese Academy of Sciences

China Institute of Atomic Energy

Other

Yangtze River Delta (jiaxing) Nano Applied Technology Research Institute

East Rock Union Limited

Guangzhou Institute of Blue Energy

Institute of Laboratory Animal Sciences, Cams & Pumc

Jue Wang

Wen Wen Yang

Yangang Wang

Ningming Nie

Jian Zhang

Yue Wu

Ling Zhang

Chuan Qin

Yue Gao

Xiaoguang Wang

Qi Kong

Tingting Feng

Yitong Li

Fuhai Gao

Yongjiang Zong

Xinfu He

Zhikuang Xin

Lixia Jia

Xia Cao

Yankun Dou

Zhongxiao Cao

Yangde Feng

Tiancai Liu

Provided is a method and system for recommendation and comparative analysis of an animal model of neurological diseases, and relates to the field of data analysis technology. The method includes obtaining a plurality of pieces of related literature on animal models of neurological diseases; extracting, for each piece of related literature on animal models of neurological diseases, information from the related literature on animal models of neurological diseases to obtain literature information of the related literature on animal models of neurological diseases; preprocessing the literature information to obtain phenotypes and application data corresponding to the related literature on animal models of neurological diseases, constructing an animal model database based on application data corresponding to all the related literature on animal models of neurological diseases, and developing a comparative analysis function; and determining a recommended model based on a user input instruction and the animal model database.

Method and system for recommendation and comparative analysis of animal model of neurological diseases

The disclosure relates to a method and a system for predicting the operation time of sparse matrix vector multiplication. The method comprises constructing a convolutional neural network comprising an input layer, a feature processing layer, a data splicing layer and an output layer for outputting prediction results. The method further comprises acquiring a plurality of groups of sparse matrices with known sparse matrix vector multiplication operation time as sample data, inputting the sample data into the convolutional neural network to train the convolutional neural network, and inputting the sparse matrix to be classified into the trained convolutional neural network to realize the prediction of the operation time of sparse matrix vector multiplication.

Method and system for predicting operation time of sparse matrix vector multiplication

A self-generating power supply apparatus includes a power generating body, an energy harvester, and a power consumer. The power generating body generates an electromagnetic field when a force is applied, an energy of the electromagnetic field is received by the energy harvester and subsequently transferred to the power consumer; or alternatively, the energy harvester is not provided and the energy of the electromagnetic field is directly received and used by the power consumer. The energy of the electromagnetic field is harvested by the energy harvester contacting or not contacting the power generating body, and then is converted into electrical energy, which is transferred out in a wired or wireless manner to enable self-generating power supply for the apparatus. The self-generating power supply apparatus has an immeasurable impact on the development in the fields such as wearable devices, small mobile communication devices, Internet of Things, new energy etc.

Self-generating power supply apparatus

A method and device for simulating microstructure evolution of a material based on solution in an exponential time-difference format. The method includes: establishing a reaction rate theory model for substance defects, wherein the model is expressed with equations that comprise linear terms having coefficients characterized with matrixes; and iteratively solving the equations by using an exponential time-difference format, wherein during the iterative solving, the linear terms with exponential powers of the matrixes as the coefficients are integrated. Since a rate theory is not limited by spatial-temporal scales, the advantages of the rate theory can be significantly reflected when the microstructure evolution is simulated under a high damage dose condition; and then, the equations are solved by using the exponential time-difference format, with a solved result better in accuracy and higher in precision.

Simulation of microstructure evolution of material as solved based on exponential time-difference format

The present invention provides a transfer molding mold for a vulcanized rubber boot, comprising: a combined tube mold, having an inner cavity corresponding to a tube of the rubber boot a last mold with partition elements, having a main body substantially corresponding to the tube of the rubber boot in shape, and two or more partition elements disposed on the main body, wherein the last mold is suitable for installation into the inner cavity of the tube mold to form a transfer molding cavity between the wall of the inner cavity of the tube mold and the outer surface of the last mold, and the transfer molding cavity is partitioned into two or more parts by the last mold and the tube mold; and a rubber injection guide plate suitable for installation to the top of the tube mold to guide injection of unvulcanized mixed rubber, comprising a plate body, wherein the plate body is provided with: a rubber injection port to be connected with an external injection head to inject the unvulcanized mixed rubber; and an annular rubber injection channel for introducing the externally injected unvulcanized mixed rubber into the transfer molding cavity in an annular distribution manner.

Vulcanized rubber boot and transfer molding mold, manufacturing equipment and manufacturing method thereof

Growing community of inventors

Beijing, China

Jue Wang