Abstract: The present application provides a gate driving circuit and a display panel. The gate driving circuit includes a plurality of cascaded gate driving units, where each of the plurality of cascaded gate driving units includes a pull-up control module, an inversion module and a feedback module. The potential of the pull-up node is stepwise increased by the pull-up control module, so that the feedback module can be controlled to be turned off by the inversion module when the potential of the pull-up node is lower, thereby improving a phenomenon of leakage of the pull-up node through the feedback module.

Abstract: A gate driving circuit and a display panel are provided. The gate driving circuit includes a plurality of gate driving units, and each of the gate driving units includes a first transistor and a second transistor. By setting a second size of the second transistor to be greater than a first size of the first transistor, not only the working stability of the second transistor is improved, but also the coupling of a potential of an output terminal of the first transistor to a potential of an output terminal of the second transistor can be reduced or avoided.

Abstract: The present application provides a gate driving circuit and a display panel. The gate driving circuit includes a plurality of cascaded gate driving units, where each of the plurality of cascaded gate driving units includes a pull-up control module, an inversion module and a feedback module. The potential of the pull-up node is stepwise increased by the pull-up control module, so that the feedback module can be controlled to be turned off by the inversion module when the potential of the pull-up node is lower, thereby improving a phenomenon of leakage of the pull-up node through the feedback module.

Abstract: Method and apparatus configured to receive a plurality of power flow data from at least a grid monitoring device connected to a grid network including a plurality of nodes, generate a power flow allocation for at least a node in the network as a function of the at least a power consumption datum and the at least a generation datum, determine a carbon flow as a function of the power flow allocation and a first set of stored relational rules, generate an objective function of a carbon flow and a second set of stored relational rules, minimize the objective function of a carbon flow as a function of the carbon optimization model and an optimization algorithm, generate a grid modification as a function of the minimization; and modify a grid parameter of the grid network as a function of the grid modification.

Abstract: A method for calculating consumption-based carbon emissions in power grids is disclosed. The method includes receiving, from a first grid monitoring device monitoring a first grid, a plurality of first power output quantities from a plurality of power generators in the first grid; receiving, from a second grid monitoring device monitoring a second grid, a plurality of second power output quantities from a plurality of power generators in the second grid, wherein the first grid is connected to the second grid and can send and/or receive power to and/or from the second grid; computing and solving a linear system of equations based on variables representative of each the first grid and the second grid; and displaying, on a user interface, a consumption-based carbon emissions calculation describing carbon emissions consumed per megawatt-hours (MWh) produced by the first grid and the second grid based on solving the linear system of equations.

Abstract: The present disclosure provides a display panel including a display GOA unit and a dummy GOA unit connected to the display GOA unit, a pull-down module of the display GOA unit receives a frame start signal and a pull-down module of the dummy GOA unit receives a control signal; within a frame duration, the frame start signal comprises one frame start pulse, and the control signal comprises a first pulse and a second pulse sequentially generated at intervals; a first pulse of a previous frame is generated between a last clock pulse of a previous frame and a frame start pulse of a next frame; a second pulse of the previous frame is generated between the last clock pulse of the previous frame and the frame start pulse of the next frame or in synchronization with the frame start pulse of the next frame.

Abstract: An electronic device includes an integrally formed metal casing including a first part and a second part that are intersecting with each other. An outer surface of the first part is a first surface presenting a first visual effect. An outer surface of the second part is a second surface presenting a second visual effect. The second visual effect is different from the first visual effect, and the second visual effect is a mirror effect. A boundary line between the second visual effect and the first visual effect is used to distinguish the first surface and the second surface.

Abstract: A method for generating an image of a scene with a corresponding depth map is disclosed herein. The method comprises collecting a plurality of copies of a two-dimensional image of the scene, generating an intermediate image by concatenating the plurality of copies of the two-dimensional image along a first direction, generating an intermediate depth map corresponding to the intermediate image by applying a neural network to the intermediate image, and generating, from the intermediate image and the intermediate depth map, the image of the scene with the corresponding depth map.

Abstract: Method and apparatus configured to receive a plurality of power flow data from at least a grid monitoring device connected to a grid network including a plurality of nodes, generate a power flow allocation for at least a node in the network as a function of the at least a power consumption datum and the at least a generation datum, determine a carbon flow as a function of the power flow allocation and a first set of stored relational rules, generate an objective function of a carbon flow and a second set of stored relational rules, minimize the objective function of a carbon flow as a function of the carbon optimization model and an optimization algorithm, generate a grid modification as a function of the minimization; and modify a grid parameter of the grid network as a function of the grid modification.

Abstract: A system for machine-learning for prediction grid carbon emissions includes a computing device configured to receive, from a first local grid monitoring device monitoring a first local grid, a plurality of first power output quantities of a plurality of power generators in the first local grid, train an emission projection machine-learning process, wherein training further includes compiling a plurality of training data entries, each training data entry correlating a plurality of past power output quantities with at least a reported carbon emission datum and training the emission projection machine-learning process using the plurality of training data entries, and generate, using the emission projection machine-learning process, a projected carbon emission rate as a function of the plurality of power output quantities.

Abstract: Method and apparatus configured to receive a plurality of power flow data from at least a grid monitoring device connected to a grid network including a plurality of nodes, generate a power flow allocation for at least a node in the network as a function of the at least a power consumption datum and the at least a generation datum, determine a carbon flow as a function of the power flow allocation and a first set of stored relational rules, generate an objective function of a carbon flow and a second set of stored relational rules, minimize the objective function of a carbon flow as a function of the carbon optimization model and an optimization algorithm, generate a grid modification as a function of the minimization; and modify a grid parameter of the grid network as a function of the grid modification.

Abstract: A system for machine-learning for prediction grid carbon emissions includes a computing device configured to receive, from a first local grid monitoring device monitoring a first local grid, a plurality of first power output quantities of a plurality of power generators in the first local grid, train an emission projection machine-learning process, wherein training further includes compiling a plurality of training data entries, each training data entry correlating a plurality of past power output quantities with at least a reported carbon emission datum and training the emission projection machine-learning process using the plurality of training data entries, and generate, using the emission projection machine-learning process, a projected carbon emission rate as a function of the plurality of power output quantities.

Abstract: A system for machine-learning for prediction grid carbon emissions includes a computing device configured to receive, from a first local grid monitoring device monitoring a first local grid, a plurality of first power output quantities of a plurality of power generators in the first local grid, train an emission projection machine-learning process, wherein training further includes compiling a plurality of training data entries, each training data entry correlating a plurality of past power output quantities with at least a reported carbon emission datum and training the emission projection machine-learning process using the plurality of training data entries, and generate, using the emission projection machine-learning process, a projected carbon emission rate as a function of the plurality of power output quantities.

Abstract: An electronic device includes an input assembly and an output assembly, to be respectively used for data input and data output, a support assembly, to at least support the input assembly or the output assembly and to enable either of the input assembly or the output assembly to stand on a base, and a connector mechanism, to connect the input assembly and/or the output assembly to the support assembly, and to enable the input assembly and/or the output assembly to rotate relative the support assembly in various dimensions. The electronic device according to embodiments of the present disclosure is rotatable in multiple dimensions to meet user's needs in variable position adjustments.

Abstract: A method for generating an image of a scene with a corresponding depth map is disclosed herein. The method comprises collecting a plurality of copies of a two-dimensional image of the scene, generating an intermediate image by concatenating the plurality of copies of the two-dimensional image along a first direction, generating an intermediate depth map corresponding to the intermediate image by applying a neural network to the intermediate image, and generating, from the intermediate image and the intermediate depth map, the image of the scene with the corresponding depth map.

Abstract: A method for generating an image of a scene with a corresponding depth map is disclosed herein. The method comprises collecting a plurality of copies of a two-dimensional image of the scene, generating an intermediate image by concatenating the plurality of copies of the two-dimensional image along a first direction, generating an intermediate depth map corresponding to the intermediate image by applying a neural network to the intermediate image, and generating, from the intermediate image and the intermediate depth map, the image of the scene with the corresponding depth map.

Abstract: A method for generating an image of a scene with a corresponding depth map is disclosed herein. The method comprises collecting a plurality of copies of a two-dimensional image of the scene, generating an intermediate image by concatenating the plurality of copies of the two-dimensional image along a first direction, generating an intermediate depth map corresponding to the intermediate image by applying a neural network to the intermediate image, and generating, from the intermediate image and the intermediate depth map, the image of the scene with the corresponding depth map.

Abstract: An electronic device includes an input assembly and an output assembly, to be respectively used for data input and data output, a support assembly, to at least support the input assembly or the output assembly and to enable either of the input assembly or the output assembly to stand on a base, and a connector mechanism, to connect the input assembly and/or the output assembly to the support assembly, and to enable the input assembly and/or the output assembly to rotate relative the support assembly in various dimensions. The electronic device according to embodiments of the present disclosure is rotatable in multiple dimensions to meet user's needs in variable position adjustments.