Abstract: The present application discloses a high-barrier polyolefin composite film, including, from the outside to the inside, an outer PE film, a water-barrier layer, a high-barrier PVA coating layer, an adhesive layer, and an inner PE film, wherein the inner PE film comprises the following raw materials in percentage by weight: 10-20% of HDPE, 30-50% of MDPE, 20-26% of LLDPE, 10-20% of LDPE, 8-12% of a water- and oxygen-barrier masterbatch, and 1-3% of an auxiliary agent; the water- and oxygen-barrier masterbatch includes the following raw materials in parts by weight: 10-20 parts of polycarbonate, 0.1-0.3 parts of a compatibilizer, 10-20 parts of an ethylene-vinyl acetate copolymer (EVA), 1-2 parts of single-layer graphene, and 1-2 parts of polyhedral oligomeric silsesquioxane.

Abstract: A method for acquiring point of interest (POI) representation information, includes: acquiring a POI relationship graph, and acquiring a node relationship set of each node on the POI relationship graph based on the POI relationship graph, in which the POI relationship graph includes edges representing relationships between nodes of POIs, and the node relationship set includes relationship paths where the node reaches all second-order neighbor nodes via any one first-order neighbor node; acquiring a spatial distance matrix between the node and corresponding second-order neighbor nodes; and determining first POI representation information of the node based on the node relationship set of the node and the spatial distance matrix.

Abstract: A method for determining a competitive relation of Points of Interest (POI), and a device are provided in the present disclosure. The specific implementation includes: determining POI representation data between two target POIs based on service-related data of the target POIs; and determining a competitive relation between the target POIs based on the POI representation data.

Abstract: The present disclosure discloses an information processing method and device, and relates to the field of artificial intelligence, in particular, to a graph neural network in the field of deep learning. A specific implementation solution according to an embodiment includes determining initial representation of edges connected between a plurality of atoms in a molecule based on three-dimensional structure information of the molecule; determining first representation of a neighbor edge of each of the atoms based on the initial representation of the edges, the neighbor edge of each of the atoms indicating at least one edge connected with each of the atoms; determining first representation of each of the atoms based on the first representation of the neighbor edge of each of the atoms; determining feature representation for characterizing the molecule based on the first representation of each of the atoms.

Abstract: A method of training a prediction model for determining molecular binding force is provided, which relates to the field of artificial intelligence, in particular to a graph neural network in the field of deep learning. The method includes: constructing a virtual complex molecule based on a three-dimensional structure information of a first molecule and a second molecule; determining a predicted binding force and a predicted interaction matrix between the first molecule and the second molecule based on the virtual complex molecule by using the prediction model, the predicted interaction matrix indicating an element-type-based and distance-based interaction between an atom in the first molecule and an atom in the second molecule; and training the prediction model by minimizing a target loss function based on a difference between the predicted binding force and a real binding force and a difference between the predicted interaction matrix and a real interaction matrix.

Abstract: A method for determining correlation between a drug and a target, and an electronic device are provided. The method includes: establishing a spatial molecular graph of a candidate drug and the target, the spatial molecular graph including an atomic node set and an edge set, the atomic node set including atoms in the candidate drug and atoms in the target, the edge set including at least one atom connection edge; inputting a first atom feature of the atomic node set and the spatial molecular graph into a first GAT for prediction, to obtain a second atom feature of the atomic node set; and determining a parameter value of the correlation between the candidate drug and the target in accordance with the second atom feature of the atomic node set.

Abstract: A method for determining a competitive relation of Points of Interest (POI), and a device are provided in the present disclosure. The specific implementation includes: determining POI representation data between two target POIs based on service-related data of the target POIs; and determining a competitive relation between the target POIs based on the POI representation data.