Abstract: A method for determining a regulation range of pumping power of a three-machine pumped storage unit is provided. The method includes: obtaining a first parameter set of pumping measurement parameters for characterizing the three-machine pumped storage unit and determining a pumping process efficiency; determining a first relational expression based on the pumping process efficiency and a design efficiency of a pumped storage power station and establishing a second relational expression; and determining a third relational expression based on power absorbed by a power grid and the second relational expression and determining a fourth relational expression, where the fourth relational expression reflects the regulation range of the pumping power of the three-machine pumped storage unit. The method for determining the regulation range of the pumping power of the three-machine pumped storage unit is proposed according to unit characteristics and operating economy of the power station.

Abstract: Provided herein are novel compounds, for example, compounds having a Formula (I), or a pharmaceutically acceptable N salt thereof. Also provided herein are methods of preparing the compounds and methods of using the compounds, for example, in inhibiting TYK2, and/or function of IL-12, IL-23 and/or INF-alpha, and/or in treating various associated diseases or disorders.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via multi-layered scene completion techniques facilitated by artificial intelligence. For instance, in some embodiments, the disclosed systems receive a digital image portraying a first object and a second object against a background, where the first object occludes a portion of the second object. Additionally, the disclosed systems pre-process the digital image to generate a first content fill for the portion of the second object occluded by the first object and a second content fill for a portion of the background occluded by the second object. After pre-processing, the disclosed systems detect one or more user interactions to move or delete the first object from the digital image. The disclosed systems further modify the digital image by moving or deleting the first object and exposing the first content fill for the portion of the second object.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: The disclosure relates to the field of electronic materials, and in particular to a composite film of fluorinated polybenzoxazole (6FPBO) and triple-shelled mesoporous silica hollow spheres, and to its preparation and use. The composite film comprises fluorinated polybenzoxazole as a matrix and amino-functionalized triple-shelled mesoporous silica hollow spheres which are dispersed in the fluorinated polybenzoxazole matrix. A mass ratio of (amino-functionalized triple-shelled mesoporous silica hollow spheres)/(fluorinated polybenzoxazole) is 1/100 to 5/100. The composite film has excellent thermal stability and a lower dielectric constant.

Abstract: A battery includes positive and negative current collectors and a plurality of bipolar electrodes arranged in a stack between the positive and negative current collectors. The positive and negative current collectors and the stack of the plurality of bipolar electrodes are folded in an S-shape.

Abstract: Apparatus, systems, articles of manufacture, and methods for robot movement are disclosed. An example robot movement apparatus includes a sequence generator to generate a sequence of context variable vectors and policy variable vectors. The context variable vectors are related to a movement target, and the policy variable vectors are related to a movement trajectory. The example apparatus includes a calculator to calculate an upper policy and a loss function based on the sequence. The upper policy is indicative of a robot movement, and the loss function is indicative of a degree to which a movement target is met. The example apparatus also includes a comparator to determine if the loss function satisfies a threshold and an actuator to cause the robot to perform the robot movement of the upper policy when the loss function satisfies the threshold.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for panoptically guiding digital image inpainting utilizing a panoptic inpainting neural network. In some embodiments, the disclosed systems utilize a panoptic inpainting neural network to generate an inpainted digital image according to panoptic segmentation map that defines pixel regions corresponding to different panoptic labels. In some cases, the disclosed systems train a neural network utilizing a semantic discriminator that facilitates generation of digital images that are realistic while also conforming to a semantic segmentation. The disclosed systems generate and provide a panoptic inpainting interface to facilitate user interaction for inpainting digital images. In certain embodiments, the disclosed systems iteratively update an inpainted digital image based on changes to a panoptic segmentation map.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for panoptically guiding digital image inpainting utilizing a panoptic inpainting neural network. In some embodiments, the disclosed systems utilize a panoptic inpainting neural network to generate an inpainted digital image according to panoptic segmentation map that defines pixel regions corresponding to different panoptic labels. In some cases, the disclosed systems train a neural network utilizing a semantic discriminator that facilitates generation of digital images that are realistic while also conforming to a semantic segmentation. The disclosed systems generate and provide a panoptic inpainting interface to facilitate user interaction for inpainting digital images. In certain embodiments, the disclosed systems iteratively update an inpainted digital image based on changes to a panoptic segmentation map.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for panoptically guiding digital image inpainting utilizing a panoptic inpainting neural network. In some embodiments, the disclosed systems utilize a panoptic inpainting neural network to generate an inpainted digital image according to panoptic segmentation map that defines pixel regions corresponding to different panoptic labels. In some cases, the disclosed systems train a neural network utilizing a semantic discriminator that facilitates generation of digital images that are realistic while also conforming to a semantic segmentation. The disclosed systems generate and provide a panoptic inpainting interface to facilitate user interaction for inpainting digital images. In certain embodiments, the disclosed systems iteratively update an inpainted digital image based on changes to a panoptic segmentation map.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for panoptically guiding digital image inpainting utilizing a panoptic inpainting neural network. In some embodiments, the disclosed systems utilize a panoptic inpainting neural network to generate an inpainted digital image according to panoptic segmentation map that defines pixel regions corresponding to different panoptic labels. In some cases, the disclosed systems train a neural network utilizing a semantic discriminator that facilitates generation of digital images that are realistic while also conforming to a semantic segmentation. The disclosed systems generate and provide a panoptic inpainting interface to facilitate user interaction for inpainting digital images. In certain embodiments, the disclosed systems iteratively update an inpainted digital image based on changes to a panoptic segmentation map.

Abstract: A rapid demagnetization method based on characteristics of magnetic media. In the method, basic information is obtained by a recognition module of magnetic media by means of multi-source sensing collaboration. The magnetic medium is identified by using a data processing technology and a magnetic medium identification algorithm, and then the characteristic information is extracted. Optimized set values of demagnetization parameters are obtained by a demagnetization parameter optimizing and setting module based on a demagnetization optimizing model. Demagnetization parameter set values are tracked by a closed-loop control module of a demagnetization magnetic field in combination with domain expert knowledge by using a closed-loop control mechanism integrated with a magnetic field control algorithm, a charging-discharging device, a magnetic field generating device, a magnetic field sensor and an environmental sensor, completing the rapid demagnetization of the magnetic medium.

Abstract: Embodiments of the present invention relate to the field of communications methods and technologies, and in particular, to a transmission method and apparatus. The transmission method includes: generating, by a first device, a sequence based on one or more transmission parameters, where the one or more transmission parameters include at least one of the following: a time domain resource type, transmission waveform indication information, subcarrier spacing indication information, device type information, service type indication information, multiple-input multiple-output MIMO parameter information, duplex mode indication information, control channel format indication information, and transmission carrier indication information; generating to-be-transmitted information by using the sequence; and sending the to-be-transmitted information. According to the transmission method and apparatus in the embodiments of the present invention, a new transmission error check mechanism is provided.

Abstract: A method for encoding a three-dimensional audio signal is provided. The method includes: An encoder obtains a current frame of a three-dimensional audio signal; obtains coding efficiency of an initial virtual speaker for the current frame based on the current frame of the three-dimensional audio signal; and when the coding efficiency of the initial virtual speaker for the current frame meets a preset condition, determines an updated virtual speaker for the current frame from a set of candidate virtual speakers; encodes the current frame based on the updated virtual speaker for the current frame, to obtain a first bitstream; or when the coding efficiency of the initial virtual speaker for the current frame does not meet the preset condition, encodes the current frame based on the initial virtual speaker for the current frame, to obtain a second bitstream.

Abstract: Disclosed is a cartridge-type rivet feeding mechanism of a flow drill screwing device including a rivet box, a magazine for storing rivets from the rivet box, a rivet pulling mechanism including a rivet pulling block, a rivet pulling block guide housing and a linear driving unit connected with the rivet pulling block, a blowing mechanism including a curved connecting tube and a third air inlet, the rivet pulling block is defined with a T-shaped through hole capable of accommodating a rivet and configured for transferring the rivet from the first connecting tube to the second connecting tube. The first air inlet and the second air inlet are both configured for introducing compressed air to push the rivet to move towards the riveter head.

Abstract: Embodiments of this application disclose a three-dimensional audio signal processing method and apparatus, to implement bit allocation of a signal. The method includes: performing spatial coding on a to-be-coded three-dimensional audio signal, to obtain a transmission channel signal and transmission channel attribute information, where the transmission channel signal includes at least one virtual speaker signal group and at least one residual signal group; and determining a bit allocation ratio of the virtual speaker signal group and a bit allocation ratio of the residual signal group based on the transmission channel attribute information.

Abstract: A present invention embodiment requests resources for a set of tasks from different resource providers. The set of tasks includes first tasks and second tasks of longer duration than the first tasks. The resources are revocable by the different resource providers based on processing demand. Performance of the first tasks is initiated on the resources, and stable resources are identified based on revocation of the resources during performance of the first tasks. Performance of the second tasks are initiated on the identified stable resources. Requests for the resources to the different resource providers are adjusted based on resource provider information collected in response to completion of the set of tasks.