Abstract: The present invention is directed to cinnolinyl and quinolinyl pyrazol-4-yl-pyridine compounds which are allosteric modulators of the M4 muscarinic acetylcholine receptor. The present invention is also directed to uses of the compounds described herein in the potential treatment or prevention of neurological and psychiatric disorders and diseases in which M4 muscarinic acetylcholine receptors are involved. The present invention is also directed to compositions comprising these compounds. The present invention is also directed to uses of these compositions in the potential prevention or treatment of such diseases in which M4 muscarinic acetylcholine receptors are involved.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that implement depth-aware object move operations for digital image editing. For instance, in some embodiments, the disclosed systems determine a first object depth for a first object portrayed within a digital image and a second object depth for a second object portrayed within the digital image. Additionally, the disclosed systems move the first object to create an overlap area between the first object and the second object within the digital image. Based on the first object depth and the second object depth, the disclosed systems modify the digital image to occlude the first object or the second object within the overlap area.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that implement perspective-aware object move operations for digital image editing. For instance, in some embodiments, the disclosed systems determine a vanishing point associated with a digital image portraying an object. Additionally, the disclosed systems detect one or more user interactions for moving the object within the digital image. Based on moving the object with respect to the vanishing point, the disclosed systems perform a perspective-based resizing of the object within 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 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 presently disclosed subject matter provides for antigen-recognizing receptors that specifically target uPAR and cells comprising such uPAR-targeted antigen-recognizing receptors. The presently disclosed subject matter further provides uses of the uPAR-targeted antigen-recognizing receptors for treatment.

Abstract: A data management system (DMS) may facilitate an investigation procedure for a set of one or more virtual machines (VMs) hosted in a first environment. The DMS may receive an indication of a selection of one or more sets of VMs and corresponding snapshots for the investigation procedure. The corresponding snapshots may be stored in a second environment, and each snapshot may be associated with a version of a respective set of VMs. The DMS may mount the one or more sets of VMs to one or more testing environments different than the first and second environments. The mounting may use the snapshots stored in the second environment to provide the testing environments with query access to respective versions of the sets of VMs hosted in the first environment. The DMS may perform query operations between the first environment and the testing environments as part of the investigation procedure.

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 presently disclosed subject matter provides for antigen-recognizing receptors that specifically target uPAR and cells comprising such uPAR-targeted antigen-recognizing receptors. The presently disclosed subject matter further provides uses of the uPAR-targeted antigen-recognizing receptors for treatment.

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 liquid dispensing system for dispensing two or more liquids of different composition, viscosity, solubility and/or miscibility at high filling speeds into a container through a unitary dispensing nozzle to improve homogeneous mixing of such liquids, while said nozzle is an integral piece free of any movable parts.

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 printing system is disclosed. The printing system includes at least one physical memory device to store defective print element determination logic and one or more processors coupled with the at least one physical memory device to execute the defective print element determination logic to receive a print image comprising evaluation marks and locator marks applied to a print medium by a plurality of pel forming elements according to print instructions and identify pel forming elements associated with print defect pels in the print image among the plurality of pel forming elements based on the evaluation marks, the locator marks and the print instructions.

Abstract: The present disclosure includes methods and systems for generating digital predictive models by progressively sampling a repository of data samples. In particular, one or more embodiments of the disclosed systems and methods identify initial attributes for predicting a target attribute and utilize the initial attributes to identify a coarse sample set. Moreover, the disclosed systems and methods can utilize the coarse sample set to identify focused attributes pertinent to predicting the target attribute. Utilizing the focused attributes, the disclosed systems and methods can identify refined data samples and utilize the refined data samples to identify final attributes and generate a digital predictive model.

Abstract: The present invention provides anti-gliadin antibodies and antibody fragments, and polypeptides encoding the antibodies or fragment. Also disclosed are methods and kits for the use of such antibodies, fragments, or polypeptides in detection of gliadin. Further provided are heavy chain and light chain variable sequences and associated sequences of complementarity-determining regions (CDRs).

Abstract: A diagnostic system for model governance is presented. The diagnostic system includes an auto-encoder to monitor model suitability for both supervised and unsupervised models. When applied to unsupervised models, the diagnostic system can provide a reliable indication on model degradation and recommendation on model rebuild. When applied to supervised models, the diagnostic system can determine the most appropriate model for the client based on a reconstruction error of a trained auto-encoder for each associated model. An auto-encoder can determine outliers among subpopulations of consumers, as well as support model go-live inspections.

Abstract: Aspects of the present disclosure generally relate to a swimming pool having an internal lighting system. Certain embodiments may include an inflatable swimming pool including a wall and a base. The wall may include one or more inflatable chambers. One or more lighting elements may be interior to one or more of the inflatable chambers. The one or more lighting elements may be able to emit a plurality of colors. A color and/or intensity of the lighting elements may be controlled in accordance with a control command.

Abstract: A prosthetic system for implantation between upper and lower vertebrae having an upper joint component and a lower joint component. The joint is adapted for implantation within a disc space between the upper and lower vertebrae, allowing the upper and lower vertebrae to move relative to one another. The system further includes a bridge component extending posteriorly from the lower joint component and from the disc space, with the bridge component having a lower contact surface configured for engaging a resected bone surface of a pedicle of the lower vertebrae. The distal end of the bridge component comprises a connection component adapted to receive a fastener.