Abstract: An example system includes first memory, second memory having a greater areal density than the first memory, and a logic circuit configured to move some test data from the second memory to the first memory while at least one of (i) reading other test data from the first memory or (ii) processing the other test data. The logic circuit is configured to process the other test data prior to output along a test channel. The test channel leads to a device under test (DUT) to be tested.

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 instance, in one or more embodiments, the disclosed systems receive a digital image from a client device. The disclosed systems detect, utilizing a shadow detection neural network, an object portrayed in the digital image. The disclosed systems detect, utilizing the shadow detection neural network, a shadow portrayed in the digital image. The disclosed systems generate, utilizing the shadow detection neural network, an object-shadow pair prediction that associates the shadow with the object.

Abstract: A medical system includes a head having an end arranged to face a reference plane and a multistage slide mechanism coupled with the head. The multistage slide mechanism includes a coarse-float mechanism configured to enable movement of the head relative to the reference plane, and a fine-float mechanism configured to limit a force applied through the head to an initial force, and to reduce the force applied through the head to a reduced force less than the initial force in response to a presence of a first triggering event. The first triggering event may correspond to a valid coupling between a cone attachment of the head and a patient interface coupled to an anatomical site at the reference plane.

Abstract: A medical system includes a head having an end arranged to face a reference plane and a multistage slide mechanism coupled with the head. The multistage slide mechanism includes a coarse-float mechanism configured to enable movement of the head relative to the reference plane, and to prevent movement of the head toward the reference plane while allowing movement of the head away from the reference plane. A one-way brake associated with the coarse-float mechanism is configured to transition between a locked state and an unlocked state in response to a presence of or an absence of a first triggering event. In the locked state, the one-way brake prevents movement of the head toward the reference plane and simultaneously allows movement of the head away from the reference plane. In the unlocked state, the one-way brake allows movement of the head toward the reference plane and movement of the head away from the reference plane.

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 instance, in one or more embodiments, the disclosed systems detect a selection of an object portrayed in a digital image displayed within a graphical user interface of a client device. The disclosed systems provide, for display within the graphical user interface in response to detecting the selection of the object, an interactive window displaying one or more attributes of the object. The disclosed systems receive, via the interactive window, a user interaction to change an attribute from the one or more attributes. The disclosed systems modify the digital image by changing the attribute of the object in accordance with the user interaction.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that provides a graphical user interface experience to move objects and generate new shadows within a digital image scene. For instance, in one or more embodiments, the disclosed systems receive a digital image depicting a scene. The disclosed systems receive a selection to position an object in a first location within the scene. Further, the disclosed systems composite an image by placing the object at the first location within the scene of the digital image. Moreover, the disclosed systems generate a modified digital image having a shadow of the object where the shadow is consistent with the scene and provides the modified digital image to the client device.

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 instance, in one or more embodiments, the disclosed systems generate, utilizing a segmentation neural network and without user input, object masks for objects in a digital image. The disclosed systems determine foreground and background abutting an object mask. The disclosed systems generate an expanded object mask by expanding the object mask into the foreground abutting the object mask by a first amount and expanding the object mask into the background abutting the object mask by a second amount that differs from the first amount. The disclosed systems inpaint a hole corresponding to the expanded object mask utilizing an inpainting neural network.

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 instance, in one or more embodiments, the disclosed systems detect, via a graphical user interface of a client device, a user selection of an object portrayed within a digital image. The disclosed systems determine, in response to detecting the user selection of the object, a relationship between the object and an additional object portrayed within the digital image. The disclosed systems receive one or more user interactions for modifying the object. The disclosed systems modify the digital image in response to the one or more user interactions by modifying the object and the additional object based on the relationship between the object and the additional 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 instance, in one or more embodiments, the disclosed systems generate utilizing a segmentation neural network, an object mask for each object of a plurality of objects of a digital image. The disclosed systems detect a first user interaction with an object in the digital image displayed via a graphical user interface. The disclosed systems surface, via the graphical user interface, the object mask for the object in response to the first user interaction. The disclosed systems perform an object-aware modification of the digital image in response to a second user interaction with the object mask for the object.

Abstract: Systems and methods for image processing are described. Embodiments of the present disclosure receive an image comprising a first region that includes content and a second region to be inpainted. Noise is then added to the image to obtain a noisy image, and a plurality of intermediate output images are generated based on the noisy image using a diffusion model trained using a perceptual loss. The intermediate output images predict a final output image based on a corresponding intermediate noise level of the diffusion model. The diffusion model then generates the final output image based on the intermediate output image. The final output image includes inpainted content in the second region that is consistent with the content in the first region.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing to synthesize shadows for object(s). For instance, in one or more embodiments, the disclosed systems receive a digital image depicting a scene. The disclosed systems access an object mask of the object depicting in the digital image. The disclosed systems further combine the object mask, the digital image, and a noise representation to generate a combined representation. Moreover, the disclosed systems generate a shadow for the object from the combined representation and further generates the modified digital image by combining the shadow with the digital image.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing to remove a shadow for an object. For instance, in one or more embodiments, the disclosed systems receive a digital image depicting a scene. The disclosed systems access a shadow mask of the shadow in a first location. Further, the disclosed systems generate the modified digital image without the shadow by generating a fill for the first location that preserves a visible location of the first location. Moreover, the disclosed systems generate the digital image without the shadow for the object by combining the fill with the digital image.

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 instance, in one or more embodiments, the disclosed systems provide, for display within a graphical user interface of a client device, a digital image displaying a plurality of objects, the plurality of objects comprising a plurality of different types of objects. The disclosed systems generate, utilizing a segmentation neural network and without user input, an object mask for objects of the plurality of objects. The disclosed systems determine, utilizing a distractor detection neural network, a classification for the objects of the plurality of objects. The disclosed systems remove at least one object from the digital image, based on classifying the at least one object as a distracting object, by deleting the object mask for the at least one object.

Abstract: A device for administering oxygen therapy to a patient comprises a gas intake valve; a primary flow path connecting the gas intake valve to a gas output connector, the primary flow path comprising a flow controller configured to adjust a first flow rate through the primary flow path, wherein the flow controller is in electronic communication with a processor and memory; at least one physiological sensor communicatively coupled to the processor performing a method comprising: receiving a target oxygen saturation level; receiving at least one measured physiological parameter from the at least one physiological sensor; analyzing the at least one measured physiological parameter to determine a predicted oxygen saturation level of a patient for a first time window; and adjusting the first flow rate with the flow controller to bring the predicted oxygen saturation level within a threshold value of the target oxygen saturation level.

Abstract: Provided herein are engineered hMPV F proteins. In some aspects, the engineered F proteins exhibit enhanced conformational stability and/or antigenicity. Methods are also provided for use of the engineered F proteins as diagnostics, in screening platforms, and/or in vaccine compositions.

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 invention relates to imidazopyridines of Formula (I) and pharmaceutically acceptable salts thereof, wherein R0 to R5 are as defined in the description; to their use in medicine; to compositions containing them; to processes for their preparation; and to intermediates used in such processes. The benzimidazoles of Formula (I) are ITK inhibitors and are therefore potentially useful in the treatment of a wide range of disorders including, atopic dermatitis.