Abstract: An array substrate (100) and a display device. The array substrate (100) includes a bonding area (102). The array substrate (100) includes a substrate (10), a first conductive layer (20) on the substrate (10), a first insulating layer (30) on one side of the first conductive layer (20) away from the substrate (10), and a second conductive layer (40) on one side of the first insulating layer (30) away from the substrate (10). The bonding area (102) is provided with bonding pins (201), and the bonding pin (201) includes a first conductive portion (21) and a second conductive portion (41) located on the side of the first conductive portion (21) away from the substrate (10), the first conductive portion (21) is located in the first conductive layer (20), the second conductive portion (41) is located in the second conductive layer (40), and the first conductive portion (21) is in direct contact with the second conductive portion (41).

Abstract: Disclosed herein is a method of stripping a strong reflection layer based on deep learning. The method establishes a direct mapping relationship between a strong reflection signal and seismic data of a target work area through a nonlinear mapping function of the deep neural network, and strips a strong reflection layer after the strong layer is accurately predicted. A mapping relationship between the seismic data containing the strong reflection layer and an event of the strong reflection layer is directedly found through training parameters. In addition, this method does not require an empirical parameter adjustment, and only needs to prepare a training sample that meets the actual conditions of the target work area according to the described rules.

Abstract: Disclosed herein is a method of stripping a strong reflection layer based on deep learning. The method establishes a direct mapping relationship between a strong reflection signal and seismic data of a target work area through a nonlinear mapping function of the deep neural network, and strips a strong reflection layer after the strong layer is accurately predicted. A mapping relationship between the seismic data containing the strong reflection layer and an event of the strong reflection layer is directedly found through training parameters. In addition, this method does not require an empirical parameter adjustment, and only needs to prepare a training sample that meets the actual conditions of the target work area according to the described rules.

Abstract: The present disclosure relates to the field of carbon materials, in particular to an amorphous carbon material and a preparation method and an application thereof. The amorphous carbon material has the following characteristics: (1) a true density ? of the amorphous carbon material and a interlayer spacing d002 obtained by powder X-Ray Diffraction (XRD) spectrum analysis satisfy the following relational formula: 100×?×d002?70; (2) the interlayer spacing d002, La and Lc of the amorphous carbon material obtained by powder XRD spectrum analysis satisfy the following relational formula: Lc×d002?0.58, and 100×(Lc/La2)×d0023?0.425, wherein ? is denoted by the unit of g/cm3, each of d002, Lc and La is denoted by the unit of nm. The amorphous carbon material prepared by the present disclosure has desirable heat transfer performance and can provide high battery capacity.

Abstract: The present disclosure relates to the field of carbon materials, in particular to an amorphous carbon material and a preparation method and an use thereof. The amorphous carbon material has the following characteristics: (1) the true density ? of the amorphous carbon material and the interlayer spacing d002 obtained by powder XRD spectrum analysis satisfy the relational formula: 100×?×d002?70; (2) the interlayer spacing d002, La and Lc satisfy the following relational formula: Lc×d002?0.58; and 100×(Lc/La2)×d0023?0.425; (3) the amorphous carbon material contains 0.001-2% of a silicon component and 0.001-2% of an aluminum component, based on the total mass of the amorphous carbon material. The amorphous carbon material prepared by the present disclosure has desirable heat transfer performance and can provide high battery capacity.