Zhejiang Lab

Zhejiang University

Alibaba Group Holding Limited

Advanced New Technologies Co., Ltd.

Fmr Corp.

Other

Huawei Technologies Co., Limited

Venus Medtech (hangzhou) Inc.

Chengdu Monolithic Power Systems Co., Ltd.

Zhejiang Academy of Agricultural Sciences

Handa Oncology, LLC

Eco-environmental Science Research & Design Institute of Zhejiang Province

Yu Zhang

Nan Wang

Zhichao Wang

Zhijun Du

Chaoliang Sun

Huan Zhang

Haotian Qian

Tianzi Jiang

Yong Cai

Shuo Liu

Zhiyong Sun

Pu Li

Wanglin Lin

Zhijian Yang

Kaiyou Jiang

Fan Ding

Shanmin Zhou

Jingsong Li

Xianbin Wang

Jin Zhao

Wei Ding

Zhaoyang Zhang

Qiang He

Hua Hao

Jianan Wang

Dong Han

Jiajie Ma

Jingyang Li

Ting Jiang

Linlin Hou

Ting Yu

Kewei Gu

Junyang Zhang

Yan Chen

Wei Song

Wei Wang

Yiqun Wu

Qian Ouyang

Ying Zhang

Yang Shi

Hou-Sen Lim

Xiaokang Wu

Jun Li

Li Fu

Xue Li

Bo Zhang

Zhenjun Zi

Hao Wang

Zhifei Zhang

Fang-Yu Liu

Lei Chen

Di Xu

Ji Zhang

Kaiqian Wang

Hongyu Fan

Zhengxian Liu

Xiao Zhang

Junjie Zhang

Liang Chen

Yingyu Tan

Xiaoyan Mao

Lei Qin

Xiaoqin Wu

Kc Sung

Dong Li

Xiangyu Shao

Junhong Wang

Frank Min Zeng

Zuoyi Zhu

Wenyuan Qiu

Jiahong Zhu

Fei Huang

Xiaogang Wei

Zenghui Xu

Renwu Jiang

Hao Qi

Yu Xin

Jiwei Tian

Jianhua Sun

Xingwei Xiang

Genyi Zhang

Liang Zhang

Shang Wei Qin

Dingding Luo

George Kraft

Yi Dong

John Duan

Zhaoxiang Wang

Ruonan Zheng

Chen Wang

Kai Qiao

Weichen Dai

Chuanlu Yu

Jiajun Jiang

Lan Wang

Disclosed are a disease prediction method, system and apparatus based on a multi-relation functional connectivity matrix. A Pearson correlation coefficient matrix and a DTW distance matrix are respectively calculated according to resting state functional magnetic resonance time series extracted from a brain atlas, the DTW distance matrix is converted in combination with the Pearson correlation coefficient matrix into a DTW' matrix which includes correlation degree and correlation direction information and whose numerical range is equivalent to the value range of a Pearson coefficient, and a functional connectivity matrix is obtained after weighted combination. The present disclosure combines DTW distance information to weaken the dynamic change of functional connectivity and the influence of asynchrony of functional signals in different brain regions on the functional connectivity matrix, so that the calculated functional connectivity matrix can better reflect the correlation between the functional signals in different brain regions.

Disease prediction system and apparatus based on multi-relation functional connectivity matrix

An information recommendation method, an apparatus, a device, and a medium based on embedding table compression are provided. The method includes: determining, based on a preset compression ratio, to-be-compressed features and non-compressed features in a to-be-compressed embedding table of a recommendation model, generating a similarity index matrix based on a similarity between the to-be-compressed features and the uncompressed features; generating an index dictionary based on the similarity index matrix; substituting a first feature mapping dictionary based on the index dictionary to generate a second feature mapping dictionary, wherein the first feature mapping dictionary is generated based on a data set; and acquiring to-be-recommended data, replacing features in the to-be-recommended data according to the second feature mapping dictionary, inputting replaced features into the recommendation model, and outputting a prediction result.

Information recommendation method, apparatus, device, and medium based on embedding table compression

The present invention relates to oral compositions comprising cabozantinib salts and at least one pharmaceutically acceptable excipient and methods of using the oral compositions to increase the oral bioavailability of the cabozantinib and reduce the adverse events associate with the oral administration of cabozantinib. The invention also relates to methods for preparing cabozantinib lauryl sulfate salts.

Cabozantinib compositions and methods of use

Disclosed in the present invention are a dynamic maximal clique enumeration device and method based on an FPGA with an HBM, the method including: the HBM stores a dynamic edge flow, a complete graph adjacency matrix, and candidate cliques; a matrix computing unit updates the complete graph adjacency matrix based on the dynamic edge flow, transmits the updated complete graph adjacency matrix to the HBM for storage, and determines header nodes, of which the corresponding candidate clique needs to be updated; a sequence computing unit constructs, according to the updated complete graph adjacency matrix and each header node to be updated, the sorted data set for reconstructing candidate cliques by data block sequencing; and an update computing unit executes, in parallel, an update task of the candidate clique corresponding to each header node to be updated based on the sorted data set, transmits the updated candidate cliques to the HBM for storage, and transmits the updated candidate cliques to the PC host to extract maximal cliques by means of a filtering operation. The present invention supports the computation of pipelined-type incremental maximal clique, thereby improving the overall computing efficiency of the task.

Dynamic maximal clique enumeration device and method based on FPGA with HBM

A system for classifying working memory task magnetoencephalography based on machine learning, including: the magnetoencephalography data acquisition module configured to acquire magnetoencephalography data of a subject in different working memory task states; the magnetoencephalography data preprocessing module configured to control the quality of magnetoencephalography data in different working memory tasks and separate noises and artifacts; the magnetoencephalography source reconstruction module configured for sensor signal analysis and source reconstruction analysis for the data processed by the magnetoencephalography data preprocessing module; and the machine learning classification module is configured to classify the working memory tasks to which the subjects belong by taking power time series as features. The present disclosure integrates the complete analysis pipeline from preprocessing to source reconstruction of the working memory magnetoencephalography data, classifies the working memory task magnetoencephalography data, and is of great significance to the study of working memory decoding and brain memory related mechanisms.

System for classifying working memory task magnetoencephalography based on machine learning

A method and a system for simulating magnetic resonance echo-planar imaging artifacts. Firstly, for K-space artifacts, K-space data are restored through normal magnetic resonance images, and the K-space data are modified pertinently, and then images with artifacts are reconstructed; for susceptibility artifacts, a susceptibility model is constructed through normal magnetic resonance images, and the magnetic field distribution is reconstructed, and then the images with distortion artifacts are reconstructed. According to the present disclosure, a large number of artifact data sets with different artifact types and artifact degrees can be quickly created through a small number of normal images, thus laying a foundation for the research of identifying artifacts, eliminating or weakening artifacts. A simulation algorithm is designed according to the principle of generation of EPI sequence artifacts, and the obtained images such as stripe artifacts, Moer artifacts, Nyquist artifacts, susceptibility artifacts and the like have good scientificity, accuracy and interpretability.

Method and system for simulating magnetic resonance echo-planar imaging artifact

A system for precisely locating abnormal areas of brain fiber bundles. The system extracts fiber connections of the whole brain from diffusion magnetic resonance data, and fiber bundle pathways extracts through self-defined fiber bundle pathways or based on brain fiber bundle templates. A selected fiber bundle pathway is projected on a fiber connection result of the whole brain and finely segmented. The imaging indexes such as fractional anisotropy, mean diffusivity, intra-neurite volume fraction and orientation dispersion index are calculated from diffusion magnetic resonance data, so as to obtain the imaging index of each node of each fiber bundle pathway. These imaging indexes are configured to classify the disease group and the healthy group by a machine learning method, and which nodes on which fiber bundle pathways have abnormal changes with different diseases can be precisely located.

System for precisely locating abnormal area of brain fiber bundle

Provided are a directionally assembled flexible MOF hydrogel, a preparation method and a proton conduction application thereof. The prepared method includes: mixing a transition metal salt and L-Glu to prepare a mixed aqueous solution; putting the mixed aqueous solution into a reaction kettle to react at a constant reaction temperature in a range from 80° C. to 200° C. for a reaction period of 1-5 hours, to thereby obtain a reacted aqueous solution; cooling the reacted aqueous solution to room temperature; and washing the reacted aqueous solution after the cooling with deionized water and absolute ethanol, to thereby obtain the directionally assembled flexible MOF hydrogel, L-Glu-M (M═Zr, Fe, or Co), for sealing and storing. The preparation method is simpler and easier to operate, and the directionally assembled flexible MOF hydrogel has great prospects in the field of proton conducting technologies.

Directionally assembled flexible MOF hydrogel, and preparation method and proton conduction application thereof

A system for predicting disease with graph convolutional neural network based on multimodal magnetic resonance imaging, which extracts the radiomics information of multiple brain regions across modals as the features of nodes from multimodal magnetic resonance data, and extracts the connectomics information between brain regions to form an adjacency matrix. T1-weighted structural images extract cortical information through cortical reconstruction, and resting-state magnetic resonance data are used to calculate amplitude of low frequency fluctuations, regional homogeneity and functional connectivity. Through multimodal data preprocessing, image index extraction and structured data integration, multimodal unstructured magnetic resonance image data are integrated into unified graph-structured data, and the disease is predicted by a graph convolutional neural network method. The system can better integrate the cross-modal physiological indexes of multiple brain regions and the correlation between brain regions and improve prediction ability of the model and generalization ability of the model with different diseases.

System for predicting disease with graph convolutional neural network based on multimodal magnetic resonance imaging

The present disclosure discloses a brain atlas individualization method and system based on magnetic resonance and a twin graph neural network. Firstly, a feature is extracted from resting-state functional magnetic resonance imaging (rs-fMRI) by utilizing functional connectivity based on a region-of-interest, and at the same time, Fisher transformation and exponential transformation are performed on the feature; secondly, a corresponding adjacent matrix is extracted from T1-weighted magnetic resonance data in a data set; and then the twin graph neural network is designed for training and testing with the transformed feature and the adjacent matrix as inputs and a group atlas label and a sampling mask as outputs.

Brain atlas individualization method and system based on magnetic resonance and twin graph neural network

A large-flux in-situ filtration device for marine microorganism based on a multi-channel circulation distributor is provided, comprising an energy and control module, a circulation distribution module, a filtration module, a pump module, a filtration volume measurement module, a pipeline connection, and a main body support frame. The circulation distribution module may include a multi-channel circulation distributor, a deep-sea servo motor, etc. The filtration module may include a plurality of filter film holders. The pump module may include a stainless steel gear pump, a deep-sea drive motor, etc. The filtration volume measurement module may include a water meter, a camera, and an LED light.

Large-flux in-situ filtration devices for marine microorganism based on multi-channel circulation distributors

A data classification method and apparatus, a device and a storage medium. A structural feature of the respective node in graph data may be determined according to a neighbor node of the respective node in the graph data through a deviation between the decoded feature obtained by decoding the embedded coding feature of the respective node in the graph data and the initial feature of the respective node, and then the embedded coding feature corresponding to the respective node is adjusted according to the decoded feature of the respective node and the structural feature of the respective node in the graph data to obtain the adjusted feature corresponding to the respective node, so that accuracy of an obtained feature of the respective node is improved, and thus accuracy of data classification may be improved.

Data classification method and apparatus, device and storage medium

The present invention discloses a core assembly, a sheath assembly, a sheath, a sheath processing method and an interventional instrument delivery system and method. A core assembly for delivering an interventional instrument according to the present invention comprises a core tube, a locking member fixed at a distal end of the core tube for connecting the interventional instrument, and a bendable adjustable tube mounted around an outer periphery of the core tube, wherein the distal ends of the bendable adjustable tube and the core tube are fixedly connected to each other, and the proximal ends can slide relative to each other.

Sheath for delivering interventional instrument and sheath assembly

The present disclosure involves a calculation method and device for intelligent cutting squid white slices, the calculation method being implemented on the device for intelligent cutting squid white slices. The calculation method may be implemented on a calculation device, the calculation device may have at least one processor and at least one storage medium including an instruction set used for intelligent cutting the squid white slices, the calculation method including: reading a laser point cloud data of a three-dimensional (3D) topography of the squid white slices; optimizing the laser point cloud data; extracting an effective area of the squid white slices; determining a cutting zero point; determining a cutting process area; and determining optimization of a cutting point position and a cutting angle. The one or more embodiments provided by the present disclosure may satisfy the needs of large-scale continuous production in factories, reduce labor costs, and improve production efficiency.

Methods and systems for intelligent processing of aquatic products

A distal end structure of a sheath for delivering an interventional instrument includes a tubular body section which has opposite distal and proximal sides. A plurality of elastic expansion pieces is arranged circumferentially at the distal side of the body section at intervals. Each expansion piece assumes a converged configuration extending in an axial direction of the body section and a flared configuration away from each other. A connecting strip is provided between two adjacent expansion pieces, and two ends of the connecting strip are respectively connected to expansion pieces at respective sides at connection positions adjacent to distal ends of the expansion pieces. In the converged configuration of each expansion piece, a middle portion of the connecting strip is folded and received in a region between two adjacent expansion pieces; and in the flared configuration of each expansion piece, the middle portion of the connecting strip is unfolded.

Distal end structure of sheath for delivering interventional instrument and sheath

Growing community of inventors

Hangzhou, China

Yu Zhang