Abstract: A display substrate, a display device and a fabrication method are disclosed. The display substrate includes: a base substrate, having a first light-emitting region, a second light-emitting region and a transparent region, where an orthographic projection of the transparent region on the base substrate does not overlap an orthographic projection of the first light-emitting region on the base substrate and an orthographic projection of the second light-emitting region on the base substrate; and a light-emitting member, located on a side of the base substrate and including a bottom-emitting light-emitting unit located in the first light-emitting region and a top-emitting light-emitting unit located in the second light-emitting region.

Abstract: This application relates to an electrode active composition, a preparation method thereof, an electrode, a battery, and an apparatus. The electrode active composition includes: a first component, the first component being lithium cobalt oxide particles; and a second component, the second component being ternary material particles. The first component includes lithium cobalt oxide particles with a particle size greater than 11 ?m and lithium cobalt oxide particles with a particle size less than 6 ?m, and a ratio in number of the lithium cobalt oxide particles with a particle size greater than 11 ?m to the lithium cobalt oxide particles with a particle size less than 6 ?m is 0.2-4.8, and in some embodiments, 0.2-2.8.

Abstract: This disclosure relates to the electrochemical field, and in particular, to a positive electrode material and a preparation method and usage thereof. The positive electrode material of this disclosure includes a substrate, where a general formula of the substrate is LixNiyCozMkMepOrAm, where 0.95?x?1.05, 0.5?y?1, 0?z?1, 0?k?1, 0?p?0.1, 1?r?5.2, 0?m?2, m+r?2, M is selected from one or more of Mn and Al, Me is selected from one or more of Zr, Zn, Cu, Cr, Mg, Fe, V, Ti, Sr, Sb, Y, W, and Nb, and A is selected from one or more of N, F, S, and Cl; and an oxygen defect level of the positive electrode material satisfies at least one of condition (1) or condition (2): (1) 1.77?OD1?1.90; or (2) 0.69?OD2?0.74.

Abstract: An image processing method and apparatus using a neural network are provided. The image processing method includes generating a plurality of augmented features by augmenting an input feature, and generating a prediction result based on the plurality of augmented features.

Abstract: This application provides a positive active material, a positive electrode plate, an electrochemical energy storage apparatus, and an apparatus. The positive active material is LixNiyCozMkMepOrAm or LixNiyCozMkMepOrAm whose surface is provided with a coating layer. The positive active material is secondary particles, and a particle size Dn10 of the positive active material satisfies: 0.5 ?m?Dn10?3 ?m. In this application, particle morphology of the positive active material and the amount of micro powder in the positive active material are properly controlled, to effectively reduce side reactions between the positive active material and an electrolyte, decrease gas production of the electrochemical energy storage apparatus, and improve storage performance of the electrochemical energy storage apparatus without deteriorating energy density, cycle performance and rate performance of the electrochemical energy storage apparatus.

Abstract: The present invention relates to an electrode active material, a preparation method thereof, an electrode, a battery, and an apparatus. The electrode active material includes: a core and a coating layer, where the core includes a ternary material, the coating layer coats the core, the coating layer includes a reaction product of a sulfur-containing compound and a lithium-containing compound, and the reaction product includes element Li, element S, and element O.

Abstract: This application relates to an electrode active composition, a preparation method thereof, an electrode, a battery, and an apparatus. The electrode active composition includes: a first component, the first component being lithium cobalt oxide particles; and a second component, the second component being ternary material particles. The first component includes lithium cobalt oxide particles with a particle size greater than 11 ?m and lithium cobalt oxide particles with a particle size less than 6 ?m, and a ratio in number of the lithium cobalt oxide particles with a particle size greater than 11 ?m to the lithium cobalt oxide particles with a particle size less than 6 ?m is 0.2-4.8, and in some embodiments, 0.2-2.8. A summed number of the lithium cobalt oxide particles with a particle size greater than 11 ?m and the lithium cobalt oxide particles with a particle size less than 6 ?m accounts for above 90% of a total number of particles in the first component.

Abstract: The present application relates to the electrochemical field, and in particular, to a positive electrode material, and an electrochemical energy storage apparatus having thereof. The present application provides a positive electrode material, including a substrate. The substrate includes secondary particles containing primary particles. A surface of the substrate is coated with an oxide coating layer. The oxide coating layer comprises a coating element, and the coating element is selected from one or more of Al, Ba, Zn, Ti, Zr, Mg, W, Y, Si, Sn, B, Co, or P. The electrochemical energy storage apparatus comprises the foregoing positive electrode material.

Abstract: This specification provides a training method of a hybrid graph neural network model. The hybrid graph neural network model includes an encoding function and a decoding function. The method includes the following: using instances corresponding to all targets in training samples and several nearest neighbors of the instances as nodes in a graph, a graph representation vector of each instance is generated by using the encoding function based on graph data of all the instances. t rounds of training are performed on a decoding parameter; and in each round, bs targets are extracted from training samples, a predicted quantity of each target is generated by using the decoding function based on the graph representation vector of the instance corresponding to each target and non-graph data corresponding to each target, and the decoding parameter is optimized based on a loss quantity of the current round that is determined by the predicted quantities and label quantities of the bs targets in the current round.

Abstract: This disclosure relates to the electrochemical field, and in particular, to a positive electrode material and a preparation method and usage thereof. The positive electrode material of this disclosure includes a substrate, where a general formula of the substrate is LixNiyCozMkMepOrAm, where 0.95?x?1.05, 0.5?y?1, 0?z?1, 0?k?1, 0?p?0.1, 1?r?5.2, 0?m?2, m+r?2, M is selected from one or more of Mn and Al, Me is selected from one or more of Zr, Zn, Cu, Cr, Mg, Fe, V, Ti, Sr, Sb, Y, W, and Nb, and A is selected from one or more of N, F, S, and Cl; and an oxygen defect level of the positive electrode material satisfies at least one of condition (1) or condition (2): (1) 1.77?OD1?1.90; or (2) 0.69?OD2?0.74.

Abstract: This application provides a positive active material, a positive electrode plate, an electrochemical energy storage apparatus, and an apparatus. The positive active material is LixNiyCozMkMepOrAm or LixNiyCozMkMepOrAm whose surface is provided with a coating layer. The positive active material is secondary particles, and a particle size Dn10 of the positive active material satisfies: 0.5 ?m?Dn10?3 ?m. In this application, particle morphology of the positive active material and the amount of micro powder in the positive active material are properly controlled, to effectively reduce side reactions between the positive active material and an electrolyte, decrease gas production of the electrochemical energy storage apparatus, and improve storage performance of the electrochemical energy storage apparatus without deteriorating energy density, cycle performance and rate performance of the electrochemical energy storage apparatus.

Abstract: The present invention relates to an electrode active material, a preparation method thereof, an electrode, a battery, and an apparatus. The electrode active material includes: a core and a coating layer, where the core includes a ternary material, the coating layer coats the core, the coating layer includes a reaction product of a sulfur-containing compound and a lithium-containing compound, and the reaction product includes element Li, element S, and element O.

Abstract: The present application relates to the electrochemical field, and in particular, to a positive electrode material, and an electrochemical energy storage apparatus having thereof. The present application provides a positive electrode material, including a substrate. The substrate includes secondary particles containing primary particles. A surface of the substrate is coated with an oxide coating layer. The oxide coating layer comprises a coating element, and the coating element is selected from one or more of Al, Ba, Zn, Ti, Zr, Mg, W, Y, Si, Sn, B, Co, or P. The electrochemical energy storage apparatus comprises the foregoing positive electrode material.

Abstract: This application provides a composite positive-electrode material and a preparation method thereof, a positive-electrode plate, a secondary battery, and a battery module, a battery pack, and an apparatus containing such secondary battery. The composite positive-electrode material includes a core and a coating layer covering at least part of a surface of the core, where the core includes a positive-electrode pre-lithiation material, the positive-electrode pre-lithiation material includes a lithium-rich metal oxide, and the coating layer includes a positive-electrode active material.

Abstract: A cleaning robot for swimming pools includes a charging assembly, a floating assembly, a power assembly and a cleaning assembly. The charging assembly includes a charging mount provided with a first charging induction portion and a first magnet set. The floating assembly includes a floating body, and a second charging induction portion and a second magnet set are disposed on a lateral portion of the floating body. The floating assembly is attracted with the first magnet set of the charging assembly through the second magnet set, and the first charging induction portion and the second charging induction portion are arranged to charge the power assembly after being turned on. The floating assembly and the cleaning assembly are provided with a first and a second travel module for driving the floating assembly and the cleaning assembly respectively. The floating assembly is connected to the cleaning assembly through a power supply cable.

Abstract: A video data obtaining method comprises: deploying at least two simulators, each of the at least two simulators being used to simulate operation of one mobile terminal; sending video access requests to a server respectively by means of the at least two simulators; and respectively receiving, by means of the at least two simulators, video data returned by the server according to the corresponding video access requests. During the respectively receiving, by means of the at least two simulators, video data returned by the server according to the corresponding video access requests, the obtaining method further comprises: intercepting the video data returned by the server according to the corresponding video access requests, and storing the intercepted video data in a set database.

Abstract: Implementations of the present specification provide a model-based prediction method and apparatus. The method includes: a model running environment receives an input tensor of a machine learning model; the model running environment sends a table query request to an embedding running environment, the table query request including the input tensor, to request low-dimensional conversion of the input tensor; the model running environment receives a table query result returned by the embedding running environment, the table query result being obtained by the embedding running environment by performing embedding query and processing based on the input tensor; and the model running environment inputs the table query result into the machine learning model, and runs the machine learning model to complete model-based prediction.

Abstract: This application provides a positive active material, a positive electrode plate, an electrochemical energy storage apparatus, and an apparatus. The positive active material is LixNiyCozMkMepOrAm, or LixNiyCozMkMepOrAm with a coating layer on its surface; and the positive active material is single crystal or quasi-single crystal particles, and a particle size Dn10 of the positive active material satisfies: 0.3 ?m?Dn10?2 ?m. In this application, particle morphology of the positive active material and an amount of micro powder in the positive active material are properly controlled, to effectively reduce side reactions between the positive active material and an electrolyte solution, decrease gas production of the electrochemical energy storage apparatus, and improve storage performance of the electrochemical energy storage apparatus without deteriorating an energy density, cycle performance, and rate performance of the electrochemical energy storage apparatus.

Abstract: This application provides a composite positive-electrode material and a preparation method thereof, a positive-electrode plate, a secondary battery, and a battery module, a battery pack, and an apparatus containing such secondary battery. The composite positive-electrode material includes a core and a coating layer covering at least part of a surface of the core, where the core includes a positive-electrode pre-lithiation material, the positive-electrode pre-lithiation material includes a lithium-rich metal oxide, and the coating layer includes a positive-electrode active material.

Abstract: A positive electrode plate for secondary battery, a secondary battery, a battery module, a battery pack, and an apparatus are provided. Some embodiments provide a positive electrode plate for secondary battery, where the positive electrode plate includes a positive electrode current collector and a positive electrode active substance layer located on a surface of the positive electrode current collector, the positive electrode active substance layer includes a positive electrode active substance, the positive electrode active substance contains a first lithium-nickel transition metal oxide and a second lithium-nickel transition metal oxide, the first lithium-nickel transition metal oxide contains a first matrix and a first coating layer located on a surface of the first matrix, the first matrix is secondary particles, and the second lithium-nickel transition metal oxide is single crystal particles or particles with quasi-single crystal morphology.