Abstract: Provided are a preparation and applications of a six-membered fused with six-membered heterocyclic compound, specifically, provided in the present invention is a compound as represented by formula I as follows, where the definitions of the groups are as described in the description. The compound has TRK kinase inhibiting activity and can serve as a pharmaceutical composition for treating TRK dysfunction-related diseases.

Abstract: An object detection model training method, object detection method and related apparatus, relate to the field of artificial intelligence technologies such as computer vision, deep learning. An implementation includes: obtaining training sample data including a first remote sensing image and position annotation information of an anchor box of a subject to be detected in the first remote sensing image, where the position annotation information includes angle information of the anchor box relative to a preset direction; obtaining an object feature map of the first remote sensing image based on an object detection model, performing object detection on the subject to be detected based on the object feature map to obtain an object bounding box, and determining loss information between the anchor box and the object bounding box based on the angle information; updating a parameter of the object detection model based on the loss information.

Abstract: A positioning method includes clustering points in a first point cloud through multi-clustering to obtain a target point cloud, where the target point cloud represents a feature of a target object, and the first point cloud includes the target point cloud and a point cloud that represents a feature of an interfering object; and determining a position of the target object based on the target point cloud.

Abstract: A method for forming a porous copper composite is provided. At least two carbon nanostructure reinforced copper composite substrates are provided. The at least two carbon nanostructure reinforced copper composite substrates are stacked to form a composite substrate. An active metal layer is disposed on a surface of the composite substrate to form a first a composite structure. The first composite structure is pressed to form a second composite structure. The second composite structure is annealed to form a third composite structure. The third composite structure is de-alloyed to form a porous copper composite.

Abstract: An electronic device includes: a flexible substrate including a through hole; a connecting element disposed in the through hole; a semiconductor disposed on the flexible substrate; and a first conductive element disposed under the flexible substrate, wherein the first conductive element electrically connects to the semiconductor through the connecting element, wherein a distance between the semiconductor and the connecting element ranges from 5 ?m to 500 ?m

Abstract: A 1,2,3,4-tetrahydroquinoxaline derivative having a structure as represented by formula (I), preparation method therefor and application thereof. These compounds can be widely applied to preparation of drugs for treating one or more tumors, cancers, metabolic diseases, autoimmune diseases or disorders, and a new generation of ROR?t agonist drugs is expected to be developed.

Abstract: A sensor pattern and a capacitive touch screen are provided. The sensor pattern comprises: a plurality of unit blocks, and a first unit block of the unit blocks comprises: a first 1st-type sensor element, a first 2nd-type sensor element, and a second 2nd-type sensor element. The first 1st-type sensor element is disposed on a first patterned layer, having a border trace, two parallel main traces, a bridge, a first cell, and a second cell, wherein the first and second cells are not aligned. The first 2nd-type sensor element is disposed on a second patterned layer, having a main trace and a sub-trace, wherein the main trace surrounds the first cell of the first 1st-type sensor element. The second 2nd-type sensor element is disposed on the second patterned layer, having a main trace and a sub-trace, wherein the main trace surrounds the second cell of the first 1st-type sensor element.

Abstract: The present disclosure provides a resource indication method and a communication device. The resource indication method includes indicating feedback resources used by a receiving end in unicasting and/or multicasting transmission to the receiving end, the feedback resources at least including an HARQ ACK feedback resource or an HARQ NACK feedback resource for the receiving end.

Abstract: A method for making a fiber containing active ingredients from a Chinese herb. The method includes subjecting a fiber material, which is to be combined with active ingredients from the Chinese herb, to be swelled with a solvent of cellulose and then to be impregnated in a solution of an extract of the Chinese herb. The fiber material is a cellulose fiber or a spunlaced nonwoven fabric made thereof. The method requires no use of adhesives. With the method, the fiber material does not need to be subjected to acidic or basic solutions or high temperature, which would cause the active ingredients to be decomposed. The method can provide a cellulose fiber or a nonwoven fabric made thereof, both of which have a higher content of active ingredients from a Chinese herb and higher durability. Furthermore, the method is simple and is easy to control, and thus, suitable for mass production.

Abstract: A power conversion system includes an uninterruptible power apparatus, a generator module, and a control unit. The uninterruptible power apparatus includes a conversion module and a DC-to-AC conversion unit. The control unit controls the conversion module and the generator module according a power command so that a first average power provided from a DC power source coupled to the conversion module is slowly increased or decreased, and the control unit controls the conversion module according to a bus voltage so that a second average power provided from a mains is slowly decreased or increased corresponding to the first average power.

Abstract: A memory device includes a substrate. A first dielectric layer is disposed over the substrate. A plurality of conductive layers and a plurality of dielectric layers are alternately and horizontally disposed on the substrate. A channel column structure is disposed on the substrate and in the conductive layers and the dielectric layers. A side wall of the channel column structure is in contact with the plurality of conductive layers. A second dielectric layer covers the first dielectric layer. A conductive column structure is in the first and second dielectric layers, adjacent to the channel column structure, and in contact with one of the plurality of conductive layers. The conductive column structure includes a liner insulating layer as a shell layer.

Abstract: An object area measurement method and an apparatus are provided, relating to the computer vision and deep learning technology. The method includes acquiring an original image with a spatial resolution, the original image including a target object; acquiring an object identification model including at least two sets of classification models; generating one or more original image blocks based on the original image; performing operations on each original image block: scaling each original image block at at least two scaling levels to obtain scaled image blocks with at least two sizes, the scaled image blocks respectively corresponding to the at least two sets of classification models, and inputting the scaled image blocks into the object identification model to obtain an identification result of the target object; and determining an area of the target object based on the respective identification results of the one or more original image blocks and the spatial resolution.

Abstract: A method for detecting a surface defect, a method for training model, an apparatus, a device, and a medium, are provided. The method includes: inputting a surface image of the article for detection into a defect detection model to perform a defect detection, and acquiring a defect detection result output by the defect detection model; inputting a surface image of a defective article determined to be defective into an image discrimination model based on the defect detection result to determine whether the surface image of the defective article is defective, wherein the image discrimination model is a trained generative adversarial networks model, and the generative adversarial networks model is obtained by training using a surface image of a defect-free good article; and adjusting the defect detection result of the surface image of the defective article according to a determination result of the image discrimination model.

Abstract: A data transmission method of Internet of vehicles, a sending terminal and a network device are provided. The method includes: receiving a retransmission configuration sent by a network-side device, where the retransmission configuration is configured to indicate a pre-allocated retransmission resource; and performing a HARQ retransmission corresponding to an initial transmission, on the pre-allocated retransmission resource.

Abstract: The present disclosure discloses a method and apparatus for generating an image, a device, a storage medium and a program product, relates to the field of artificial intelligence, and particularly to computer vision and deep learning technologies, and may be applied in smart cloud and power grid inspection scenarios. A particular implementation of the method comprises: acquiring an original insulator image; performing an image transformation on the original insulator image to obtain a composite insulator image; and inputting the original insulator image and the composite insulator image into a pre-trained generative adversarial network to generate a target insulator image. According to the implementation, the image transformation is performed on the original insulator image, and then, massive target insulator images are generated through the generative adversarial network.

Abstract: An anode of the lithium ion battery is provided. The anode of the lithium ion battery comprises a nanoporous copper substrate and a copper oxide nanosheet array. The copper oxide nanosheet array is disposed on one surface of the nanoporous copper substrate, and the nanoporous copper substrate is chemically bonded to the copper oxide nanosheet array.

Abstract: A semiconductor device package comprises a semiconductor device, a first encapsulant surrounding the semiconductor device, a second encapsulant covering the semiconductor device and the first encapsulant, and a redistribution layer extending through the second encapsulant and electrically connected to the semiconductor device.

Abstract: The present disclosure discloses a method and apparatus for training a model, a method and apparatus for predicting a mineral, a device and a storage medium, and relates to the fields of computer vision and deep learning technologies. An implementation of the method may include: acquiring a target hyperspectral image of a target area, the target hyperspectral image including at least one pixel point annotated with a mineral category; determining a mask image corresponding to the target hyperspectral image; determining a sample hyperspectral image according to the target hyperspectral image and the mask image; determining an annotation vector of each pixel point according to the at least one pixel point annotated with the mineral category; and training a model according to the sample hyperspectral image and the annotation vector of the each pixel point.

Abstract: The present disclosure provides a sidelink communication method, a terminal and network equipment.

Abstract: Provided are a method and apparatus for evaluating image relative definition, a device and a medium, relating to technologies such as computer vision, deep learning and intelligent medical. A specific implementation solution is: extracting a multi-scale feature of each image in an image set, where the multi-scale feature is used for representing definition features of objects having different sizes in an image; and scoring relative definition of each image in the image set according to the multi-scale feature by using a relative definition scoring model pre-trained, where the purpose for training the relative definition scoring model is to learn a feature related to image definition in the multi-scale feature.